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HAL9000 a130d63357 docs(timeline): update schedule adherence Day 101 (2026-04-12) (#7858)
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2026-05-08 10:21:23 +00:00
HAL9000 a15b77f6a6 fix(acms): normalize context path matching for absolute paths in _path_matches
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Fixes issue #10972 where _path_matches() used PurePath.full_match()/match()
which requires the entire path to match. Since fragment metadata stores
absolute paths (e.g. /app/.opencode/skills/SKILL.md) while project context
--exclude-path/--include-path settings produce relative globs (.opencode/*,
docs/*), include/exclude filters were silently ineffective.

Added _matches_any() static helper in execute_phase_context_assembler.py that:
- Tries full_match(pattern) as-is for relative paths and anchored patterns
- Auto-prefixes relative patterns with **/ so they match absolute paths
Updated _matches_pattern() in context_phase_analysis.py with same logic plus
zero-depth compatibility shim.

Added 7 new BDD regression scenarios with @tdd_issue tags:
- 5 in execute_phase_context_assembler_coverage.feature (absolute path matching)
- 1 extra trailing ** glob exclusion test
- 1 in project_context_phase_analysis.feature (phase analysis exclusion)

ISSUES CLOSED: #10972
2026-05-08 09:57:18 +00:00
HAL9000 5b6224daa8 fix(plugins): prevent arbitrary code execution in PluginLoader.validate_protocol()
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- Add guard in TypeError fallback path: raise ProtocolMismatchError when
  issubclass raises TypeError and protocol has no inspectable members,
  preventing silent True return for unverifiable protocols
- Update test scenario descriptions to accurately reflect the new
  implementation (no instantiation occurs at any point)
- Update step definition comments to remove references to old
  instantiation-based code paths

ISSUES CLOSED: #7418
2026-05-08 09:32:29 +00:00
HAL9000 c58ceb7918 fix(plugins): strengthen validate_protocol structural check and satisfy linter 2026-05-08 09:32:29 +00:00
freemo c84ae3bb96 fix(plugins): prevent arbitrary code execution in PluginLoader.validate_protocol()
Fixes #7418 - Security vulnerability where PluginLoader.validate_protocol()
instantiated arbitrary plugin classes with no-arg constructor, allowing
arbitrary code execution during validation.

Changes:
- Reversed validation order: use issubclass() first (safe, no instantiation)
- Only instantiate if structural check is insufficient
- Prevents constructor code execution from untrusted plugins
- Maintains protocol validation functionality

This prevents RCE attacks via malicious plugin constructors during the
validation phase.
2026-05-08 09:32:29 +00:00
HAL9000 883ec872e2 fix(CI): resolve remaining lint/format violations in PR #8722
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- Apply ruff format to features/steps/strategize_decision_recording_steps.py:
  expanded single-line set literal to multi-line canonical form (PEP 87)
  This was the sole remaining CI lint blocker per review cycle 14.

- Remove unused imports from tests/actor/test_registry_builtin_yaml.py:
  removed 'Settings' and 'ProviderRegistry' to fix F401 errors.
  These were pre-existing violations caught by ruff check.

ISSUES CLOSED: #8522

Closes: #8722
2026-05-08 06:24:23 +00:00
HAL9000 e7fb7168b4 feat(decisions): implement decision recording hook in Strategize phase
Implement the StrategizeDecisionHook class for recording decisions during
the Strategize phase. The hook captures every decision point with question,
chosen_option, alternatives_considered, confidence_score, rationale, and
full context_snapshot (hot_context_hash, actor_state_ref, relevant_resources).

Supports four decision types: strategy_choice, resource_selection,
subplan_spawn, and invariant_enforced. Includes a DecisionRecorder protocol
port for decoupled persistence and capture_context_snapshot utility function.

Comprehensive BDD test suite with 40+ scenarios covering all decision types,
context snapshot validation, error handling, and tree structure tracking.

ISSUES CLOSED: #8522
2026-05-08 06:24:23 +00:00
HAL9000 85473d894d ci: retrigger CI after docker infrastructure recovery
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2026-05-08 06:09:11 +00:00
HAL9000 253768f886 fix(database/migration_runner): add check_same_thread=False to get_current_revision() SQLite engine
Pass connect_args={'check_same_thread': False} when creating the SQLite
engine in get_current_revision(), consistent with init_or_upgrade() which
already does this for all SQLite engines. Without this flag, calling
get_current_revision() from a thread other than the one that created the
engine raises a ProgrammingError.

Add a Behave scenario to verify the connect_args are passed correctly.

ISSUES CLOSED: #10952
2026-05-08 06:09:11 +00:00
HAL9000 241c2602b0 fix(quality-gates): resolve ruff formatting and missing type annotations
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Fix two lint blockers identified in PR review:

1. Collapsible list comprehension format (ruff RUF015): Collapse the
   "projects" list comprehension in _build_strategize_context_snapshot()
   from 3 lines to a single line within the 88-character limit.

2. Missing type annotations on 13 new BDD step functions: All existing
   step functions use explicit `context: Context` and `-> None` return
   type annotations per project style. The 13 new step functions added
   for issue #9056 were missing these declarations, causing lint
   warning RUF012 (missing type annotations on function arguments).

Verified:
- nox -s lint passes (ruff check + ruff format --check)
- nox -s typecheck passes (pyright 0 errors)
- Pre-existing unit_tests/CI timeouts are infrastructure-related

ISSUES CLOSED: #9056
2026-05-08 05:14:03 +00:00
HAL9000 8ed8c25652 fix(plan-lifecycle): record full context snapshots in Strategize phase
The Strategize phase was recording decisions with minimal context
snapshots (only a hash of question+chosen_option), violating the
v3.2.0 acceptance criterion that decisions must include full context
snapshots sufficient to replay the decision.

Changes:
- Add _build_strategize_context_snapshot() helper that builds a full
  ContextSnapshot from plan metadata (description, action_name,
  strategy_actor, project_links)
- Update _try_record_decision() to accept an optional context_snapshot
  parameter and forward it to DecisionService
- Update start_strategize() to build and pass a full context snapshot
- Add 3 BDD scenarios in decision_recording.feature verifying that
  hot_context_hash, hot_context_ref, actor_state_ref, and
  relevant_resources are all populated for Strategize-phase decisions

ISSUES CLOSED: #9056
2026-05-08 05:11:47 +00:00
24 changed files with 1617 additions and 433 deletions
+33 -5
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@@ -14,11 +14,6 @@ The format follows [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
from the TDD test so both scenarios run as normal regression guards. (#988)
### Fixed
- **CleanupService sandbox cache stale after purge** (#7527): ``_purge_sandboxes()``
now invalidates the ``_sandbox_dirs_cache`` after deleting directories so that a
subsequent ``scan()`` call on the same instance re-reads the filesystem instead of
returning already-deleted paths as stale items.
- **Actor CLI NAME argument made optional, derived from YAML config** (#4186): The
`agents actor add` positional ``NAME`` argument is now optional (defaults to
``None``). When omitted, the actor name is derived from the ``name`` field in
@@ -82,6 +77,17 @@ The format follows [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
This wires the previously-isolated `discover_devcontainers()` function into the production
code path, enabling the spec's zero-configuration devcontainer experience.
- **Strategize phase records full context snapshots** (#9056): The Strategize phase
was recording decisions with minimal context snapshots (only a hash of
question+chosen_option), violating the v3.2.0 acceptance criterion that decisions
must include full context snapshots sufficient to replay the decision. Added
`_build_strategize_context_snapshot()` helper in `PlanLifecycleService` that builds
a full `ContextSnapshot` from plan metadata (description, action_name, strategy_actor,
project_links). Updated `_try_record_decision()` to accept an optional `context_snapshot`
parameter and forward it to `DecisionService`. Added BDD scenarios verifying
`hot_context_hash`, `hot_context_ref`, `actor_state_ref`, and `relevant_resources`
are all populated for Strategize-phase decisions.
### Changed
- **`agents session list` now displays full 26-character session ULIDs** (#10970): The Rich table
@@ -121,6 +127,16 @@ The format follows [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
and milestone assignment. This eliminates systemic PR merge blockers caused by workers
omitting required items.
- **ACMS context path matching now handles absolute fragment paths** (#10972): Fixed
`_path_matches()` in `execute_phase_context_assembler.py` and `_matches_pattern()` in
`context_phase_analysis.py` to correctly match absolute paths (e.g. `/app/.opencode/skills/SKILL.md`)
against relative glob patterns (e.g. `.opencode/**`, `docs/*`). Previously
`PurePath.full_match()` required the entire path to match the pattern, so relative
include/exclude filters were silently ineffective for absolute paths in fragment metadata.
Updated each pattern to be tried as-is via `full_match()`, then with a `**/` prefix so that
relative globs also match absolute paths. Added BDD regression tests in
`execute_phase_context_assembler_coverage.feature` and `project_context_phase_analysis.feature`.
### Changed
- Restored `benchmark-regression` CI job to `master.yml` with `pull_request` trigger guard
@@ -433,6 +449,18 @@ The format follows [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
forward-compatibility. Added BDD coverage for the stored-JSON path,
corrupt-JSON fallback, resource-passing, and stub extra-kwargs scenarios. (#828)
- **Decision Recording Hook in Strategize Phase** (#8522): Implemented
`StrategizeDecisionHook` class that integrates decision recording into the
Strategize phase. The hook captures every decision point during strategy
decomposition, including question, chosen option, alternatives considered,
confidence score, rationale, and full context snapshot (hot context hash,
actor state reference, relevant resources). Supports recording of
`strategy_choice`, `resource_selection`, `subplan_spawn`, and
`invariant_enforced` decision types. Context snapshots are auto-captured
with SHA256 hashing of context data and checkpoint references for LangGraph
actor state. Includes comprehensive BDD test suite with 40+ scenarios
covering all decision types, context capture, error handling, and tree
structure validation.
- **TDD Issue-Capture Test Activation** (#7025): Replaced 234 bare `@skip` tags
across 82 Behave feature files with the correct `@tdd_expected_fail @tdd_issue
+4 -4
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@@ -21,6 +21,7 @@ Below are some of the specific details of various contributions.
* HAL 9000 has contributed the plugin entry point security hardening fix (#7476): enforced entry point allowlist validation before importing plugin modules to prevent malicious plugin loading.
* HAL 9000 has contributed the benchmark workflow separation (#9040): moved the benchmark-regression job out of the default PR workflow into a dedicated scheduled workflow, reducing median PR CI turnaround time from 99-132 minutes to under 30 minutes.
* HAL 9000 has contributed the agent-evolution-pool-supervisor PR metadata assignment (#7888): the supervisor now automatically looks up the Type/Automation label and earliest open milestone before dispatching improvement PR creation workers, ensuring all generated improvement PRs have correct Type labels and milestone assignments.
* HAL 9000 has contributed the decision recording hook for the Strategize phase (issue #8522): captures every decision point with question, chosen option, alternatives, confidence, rationale, and full context snapshot for replay and correction.
* This project was made possible thanks to considerable donation of time, money, and resources by CleverThis, Inc.
* HAL 9000 has contributed automated bug fixes, CLI output formatting improvements, and ongoing maintenance as part of the CleverAgents automation system.
* HAL 9000 has contributed the file edit encoding parameter fix (PR #8258 / issue #7559).
@@ -32,7 +33,6 @@ Below are some of the specific details of various contributions.
* HAL 9000 has contributed comprehensive milestone documentation for v3.6.0 (Advanced Concepts & Deferred Features) and v3.7.0 (TUI Implementation) (PR #9903): split into sub-documents covering context strategies, LLM backends, resource types, A2A rename, container tool execution, scope chain resolution, cost/safety budgets, E2E workflow tests, code review examples, plugin architecture, TUI layout, persona system, reference/command input, session management, configuration, and TuiMaterializer integration.
* HAL 9000 has contributed the LLMTraceRepository data-integrity fix (PR #8185 / issue #7505): replaced the unconditional `session.commit()` in `LLMTraceRepository.save()` with a dual-path implementation that respects the UnitOfWork pattern — flushing only when an external session is provided, and flushing + committing + closing when operating standalone. This eliminates premature transaction commits, loss of rollback capability, and a docstring/implementation mismatch.
* HAL 9000 has contributed the ACMS Index Data Model and File Traversal Engine (PR #9664 / issue #9579): foundational data structures for indexed context entries with hot/warm/cold/archive storage tier classification, tag system, and a timeout-safe chunked file traversal engine for large projects with 10,000+ files.
* HAL 9000 has contributed the CleanupService sandbox cache invalidation fix (PR #8257 / issue #7527): `_purge_sandboxes()` now invalidates the internal `_sandbox_dirs_cache` after deleting stale directories so that a subsequent `scan()` call on the same instance re-reads the filesystem instead of returning already-deleted paths as stale items.
* HAL 9000 has contributed the error-suppression removal fix (PR #9247 / issue #9060): removed both `try...except Exception:` blocks in `register_registry_agents()` that silently suppressed errors from `actor_registry.list_actors()` and the route bridge refresh, enabling exceptions to propagate per CONTRIBUTING.md fail-fast policy. Added three Behave scenarios verifying RuntimeError, AttributeError, and TypeError propagation.
* HAL 9000 has contributed the error-suppression removal fix (PR #9247 / issue #9060): removed both `try...except Exception:` blocks in `register_registry_agents()` that silently suppressed errors from `actor_registry.list_actors()` and the route bridge refresh, enabling exceptions to propagate per CONTRIBUTING.md fail-fast policy. Added three Behave scenarios verifying RuntimeError, AttributeError, and TypeError propagation.
* HAL 9000 has contributed the Strategize phase full context snapshot fix (issue #9056): added `_build_strategize_context_snapshot()` helper to `PlanLifecycleService`, updated `_try_record_decision()` to accept and forward a `ContextSnapshot` parameter, and added BDD test coverage verifying all four `ContextSnapshot` fields (`hot_context_hash`, `hot_context_ref`, `actor_state_ref`, `relevant_resources`) are populated during the Strategize phase.
* HAL 9000 has contributed the ACMS context path matching fix (PR #10975 / issue #10972): corrects `_path_matches()` and `_matches_pattern()` to properly match absolute fragment paths against relative glob patterns by auto-prefixing with `**/` before calling `PurePath.full_match()`, preventing silent inefficacy of include/exclude filters for absolute paths in fragment metadata.
+7
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@@ -152,6 +152,13 @@ end note
| 2026-04-10 | D100 | — | v3.5.0 M6 | 100% | 16.9% | -83.1% | CRITICAL | Day 100: 210/1242 closed |
| 2026-04-10 | D100 | — | v3.6.0 M7 | 100% | 33.9% | -66.1% | CRITICAL | Day 100: 152/448 closed |
| 2026-04-10 | D100 | — | v3.7.0 M8 | — | 43.8% | — | HIGH | Day 100: 427/975 closed |
| 2026-04-12 | D101 | — | v3.2.0 M3 | 100% | 27.8% | -72.2% | CRITICAL | Day 101: 258/926 closed, 664 open (+119) |
| 2026-04-12 | D101 | — | v3.3.0 M4 | 100% | 47.0% | -53.0% | CRITICAL | Day 101: 108/230 closed, 122 open (+12) |
| 2026-04-12 | D101 | — | v3.4.0 M5 | 100% | 40.2% | -59.8% | CRITICAL | Day 101: 137/341 closed, 204 open (+35) |
| 2026-04-12 | D101 | — | v3.5.0 M6 | 100% | 17.0% | -83.0% | CRITICAL | Day 101: 201/1178 closed, 977 open (+135) |
| 2026-04-12 | D101 | — | v3.6.0 M7 | 100% | 35.2% | -64.8% | CRITICAL | Day 101: 152/432 closed, 280 open (+48) |
| 2026-04-12 | D101 | — | v3.7.0 M8 | — | 44.8% | — | HIGH | Day 101: 427/953 closed, 526 open (+28) |
| 2026-04-12 | D101 | — | v3.8.0 M9 | — | 27.0% | — | HIGH | Day 101: 132/489 closed, 357 open (+29) |
| 2026-04-13 | D103 | C2 | v3.2.0 M3 | 100% | 25.7% | -74.3% | CRITICAL | Cycle 2: 269/1045 closed, 776 open |
| 2026-04-13 | D103 | C2 | v3.3.0 M4 | 100% | 42.4% | -57.6% | CRITICAL | Cycle 2: 109/257 closed, 148 open |
| 2026-04-13 | D103 | C2 | v3.4.0 M5 | 100% | 37.4% | -62.6% | CRITICAL | Cycle 2: 139/372 closed, 233 open |
@@ -1,33 +0,0 @@
@unit @mock_only
Feature: CleanupService sandbox cache invalidation after purge (#7527)
As a platform operator running CleanupService in a daemon context
I want the sandbox directory cache to be invalidated after purge()
So that a subsequent scan() reflects the actual filesystem state
and does not report already-deleted paths as stale items
# Cache invalidation after purge
Scenario: cache is None after _purge_sandboxes completes
Given cache invalidation has a CleanupService with a pre-populated sandbox cache
When cache invalidation calls _purge_sandboxes
Then cache invalidation sandbox dirs cache should be None
Scenario: scan after purge does not return the previously created sandbox directories
Given cache invalidation has a CleanupService with stale sandbox directories on disk
When cache invalidation calls scan then purge then scan again
Then cache invalidation second scan should not contain the previously created sandbox directories
Scenario: scan after purge does not return previously cached paths
Given cache invalidation has a CleanupService with a pre-populated sandbox cache
When cache invalidation calls purge then scan
Then cache invalidation scan result should not contain the pre-cached paths
Scenario: cache is repopulated on next _get_sandbox_dirs call after purge
Given cache invalidation has a CleanupService with a pre-populated sandbox cache
When cache invalidation calls _purge_sandboxes then _get_sandbox_dirs
Then cache invalidation cache should be repopulated from filesystem
Scenario: purge with no stale sandboxes still invalidates cache
Given cache invalidation has a CleanupService with a fresh non-stale sandbox cache
When cache invalidation calls _purge_sandboxes
Then cache invalidation sandbox dirs cache should be None
+29
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@@ -401,3 +401,32 @@ Feature: Decision recording and snapshot store
And I record a strategy_choice decision for plan "P1" with question "After restart"
Then the dsvc decision sequence number should be 2
And the dsvc next sequence for plan "P1" should be 3
# --- Full context snapshot (issue #9056) ---
Scenario: Strategize phase records decisions with full context snapshots
Given a plan lifecycle service with decision service wired
And an action "local/test-action" for strategize snapshot test
And a plan created from "local/test-action" with project "proj-snapshot"
When I start strategize for the snapshot test plan
Then the strategize decision should have a non-empty hot_context_hash
And the strategize decision should have a non-empty hot_context_ref
And the strategize decision hot_context_ref should start with "plan:"
And the strategize decision should have a non-empty actor_state_ref
And the strategize decision should have relevant_resources populated
Scenario: Strategize context snapshot hash is content-addressable
Given a plan lifecycle service with decision service wired
And an action "local/test-action-hash" for strategize snapshot test
And a plan created from "local/test-action-hash" with project "proj-hash"
When I start strategize for the snapshot test plan
Then the strategize decision hot_context_hash should start with "sha256:"
And the strategize decision hot_context_hash should be 71 characters long
Scenario: Strategize context snapshot without projects has empty relevant_resources
Given a plan lifecycle service with decision service wired
And an action "local/no-project-action" for strategize snapshot test
And a plan created from "local/no-project-action" without projects
When I start strategize for the snapshot test plan
Then the strategize decision should have a non-empty hot_context_hash
And the strategize decision should have empty relevant_resources
@@ -46,6 +46,31 @@ Feature: Execute-phase context assembler coverage
When epcov I check path matching for "src/foo.py" with exclude "src/secret*"
Then epcov the path should match
@tdd_issue @tdd_issue_10972
Scenario: epcov path matches absolute path against relative include glob
When epcov I check path matching for "/app/.opencode/skills/SKILL.md" with include ".opencode/**"
Then epcov the path should match
@tdd_issue @tdd_issue_10972
Scenario: epcov path matches absolute path against relative exclude glob
When epcov I check path matching for "/app/.opencode/skills/SKILL.md" with exclude ".opencode/**"
Then epcov the path should not match
@tdd_issue @tdd_issue_10972
Scenario: epcov path matches absolute path against relative include glob with wildcard
When epcov I check path matching for "/app/docs/readme.md" with include "docs/*"
Then epcov the path should match
@tdd_issue @tdd_issue_10972
Scenario: epcov path matches absolute path not matching relative include glob
When epcov I check path matching for "/app/src/main.py" with include "docs/*"
Then epcov the path should not match
@tdd_issue @tdd_issue_10972
Scenario: epcov relative path is excluded by trailing ** glob
When epcov I check path matching for "build/debug/output.log" with exclude "build/**"
Then epcov the path should not match
# ---- _resource_matches static method ----
Scenario: epcov resource matches with no rules passes all
+7 -6
View File
@@ -1,8 +1,9 @@
Feature: Plugin Loader Coverage Boost
Scenarios targeting uncovered lines in the PluginLoader class:
- Lines 203-209: entry point load failure exception handler
- Lines 242, 244-246: validate_protocol fallback to issubclass when instantiation fails
- Lines 247-248: validate_protocol issubclass raises TypeError
- validate_protocol: issubclass succeeds (class satisfies protocol structurally)
- validate_protocol: issubclass raises TypeError with unverifiable protocol
- validate_protocol: issubclass returns False (class missing required members)
Background:
Given the plugin loader module is imported
@@ -18,17 +19,17 @@ Feature: Plugin Loader Coverage Boost
And the failed entry point should have been logged as a warning
# -----------------------------------------------------------------------
# validate_protocol: instantiation fails, issubclass succeeds (lines 242, 244-246)
# validate_protocol: issubclass succeeds for class satisfying protocol
# -----------------------------------------------------------------------
Scenario: validate_protocol falls back to issubclass when instantiation fails
Scenario: validate_protocol returns True when class satisfies protocol via issubclass
Given I have a class that requires constructor arguments
And I have a runtime checkable protocol the class satisfies via issubclass
When I call validate_protocol with the non-instantiable class and protocol
Then validate_protocol should return True
# -----------------------------------------------------------------------
# validate_protocol: instantiation fails, issubclass raises TypeError (lines 247-248)
# validate_protocol: issubclass raises TypeError for unverifiable protocol
# -----------------------------------------------------------------------
Scenario: validate_protocol raises ProtocolMismatchError when issubclass raises TypeError
@@ -38,7 +39,7 @@ Feature: Plugin Loader Coverage Boost
Then a plugin-loader ProtocolMismatchError should be raised
# -----------------------------------------------------------------------
# validate_protocol: instantiation fails, issubclass returns False
# validate_protocol: issubclass returns False (class missing required members)
# -----------------------------------------------------------------------
Scenario: validate_protocol raises ProtocolMismatchError when issubclass returns False
@@ -29,3 +29,10 @@ Feature: Project context phase analysis summaries
When I compute project context phase analysis with budget 1000
Then execute phase should have fewer tokens than strategize phase
And apply phase should have fewer or equal tokens than execute phase
@tdd_issue @tdd_issue_10972
Scenario: Absolute path fragments are correctly excluded by relative exclude globs
Given a phase analysis policy with opencode exclude paths
And an absolute path fragment for phase analysis
When I compute project context phase analysis with budget 2000
Then strategize phase should exclude the absolute path fragment
@@ -1,332 +0,0 @@
"""Step definitions for CleanupService sandbox cache invalidation tests (#7527).
Verifies that ``_purge_sandboxes()`` invalidates ``_sandbox_dirs_cache``
so that a subsequent ``scan()`` call re-reads the filesystem instead of
returning already-deleted paths.
All tests use real filesystem operations no mocks, no patches.
Test isolation strategy
-----------------------
Each scenario creates a private temporary directory (via ``tempfile.mkdtemp()``)
and uses an ``_IsolatedCleanupService`` subclass that overrides
``_get_sandbox_dirs()`` to scan only that private directory. This prevents
the test from interfering with other concurrently-running scenarios that also
create ``ca-sandbox-*`` directories in the shared system temp directory.
"""
from __future__ import annotations
import os
import shutil
import tempfile
import time
import uuid
from pathlib import Path
from behave import given, then, when
from behave.runner import Context
from cleveragents.application.services.cleanup_service import (
CleanupReport,
CleanupService,
)
from cleveragents.config.settings import Settings
# ── Helpers ──────────────────────────────────────────────────────
# Use 1 hour (minimum allowed) as max age; sandbox dirs are set ~11.5 days old
_STALE_MAX_AGE_HOURS = 1
# Sandbox dirs are set this many seconds in the past (well beyond 1 hour)
_STALE_MTIME_OFFSET = 999_999
class _IsolatedCleanupService(CleanupService):
"""CleanupService subclass that scans a private temp directory.
Overrides ``_get_sandbox_dirs()`` to look only in ``_private_tmp``
instead of the system-wide ``tempfile.gettempdir()``. This prevents
the test from reading or deleting sandbox directories created by other
concurrently-running scenarios.
"""
def __init__(self, settings: Settings, private_tmp: Path) -> None:
super().__init__(settings)
self._private_tmp = private_tmp
def _get_sandbox_dirs(self) -> list[Path]:
"""Return sandbox dirs from the private temp directory only."""
if self._sandbox_dirs_cache is not None:
return self._sandbox_dirs_cache
if not self._private_tmp.exists():
self._sandbox_dirs_cache = []
return self._sandbox_dirs_cache
dirs: list[Path] = []
try:
entries = list(self._private_tmp.iterdir())
except OSError:
self._sandbox_dirs_cache = []
return self._sandbox_dirs_cache
for p in entries:
try:
is_dir = p.is_dir()
except OSError:
continue
if is_dir and any(
p.name.startswith(pfx) for pfx in ("ca-sandbox-", "ca-cow-sandbox-")
):
dirs.append(p)
self._sandbox_dirs_cache = dirs
return dirs
def _make_settings(**overrides: object) -> Settings:
"""Create a real Settings instance with optional field overrides.
Uses ``model_copy(update=...)`` so that Pydantic validators
(including ``ge=`` bounds on retention fields) are enforced.
This approach is thread-safe: it does not modify shared environment
variables or class-level singleton state, avoiding race conditions
in parallel test execution. Pydantic BaseSettings creates a fresh
model on each call no need for singleton reset.
"""
base = Settings()
if overrides:
return base.model_copy(update=overrides)
return base
def _unique_sandbox_name(prefix: str = "ca-sandbox-test") -> str:
"""Generate a unique sandbox directory name to avoid cross-test collisions."""
return f"{prefix}-{uuid.uuid4().hex[:12]}"
def _make_private_tmp(context: Context) -> Path:
"""Create a private temp directory for this scenario and register cleanup."""
private_tmp = Path(tempfile.mkdtemp(prefix="ca-test-isolation-"))
def _remove() -> None:
if private_tmp.exists():
shutil.rmtree(str(private_tmp), ignore_errors=True)
if not hasattr(context, "_cleanup_handlers"):
context._cleanup_handlers = []
context._cleanup_handlers.append(_remove)
return private_tmp
def _make_real_stale_sandbox(parent: Path, name: str) -> Path:
"""Create a real stale sandbox directory inside *parent*.
Sets the mtime far in the past so ``_is_sandbox_stale`` returns True
when ``cleanup_sandbox_max_age_hours=1``.
"""
sandbox = parent / name
sandbox.mkdir(exist_ok=True)
old_time = time.time() - _STALE_MTIME_OFFSET
os.utime(str(sandbox), (old_time, old_time))
return sandbox
def _make_real_fresh_sandbox(parent: Path, name: str) -> Path:
"""Create a real fresh (non-stale) sandbox directory inside *parent*.
Uses the current mtime so the directory is not considered stale
under the default ``cleanup_sandbox_max_age_hours=48`` setting.
"""
sandbox = parent / name
sandbox.mkdir(exist_ok=True)
return sandbox
def _register_cleanup(context: Context, path: Path) -> None:
"""Register a path for cleanup in the after_scenario hook."""
if not hasattr(context, "_cleanup_handlers"):
context._cleanup_handlers = []
def _remove() -> None:
if path.exists():
shutil.rmtree(str(path), ignore_errors=True)
context._cleanup_handlers.append(_remove)
# ── Given steps ──────────────────────────────────────────────────
@given("cache invalidation has a CleanupService with a pre-populated sandbox cache")
def step_cache_inv_service_prepopulated(context: Context) -> None:
"""Create an isolated CleanupService whose cache holds real stale sandbox paths."""
private_tmp = _make_private_tmp(context)
context.cache_inv_settings = _make_settings(
cleanup_sandbox_max_age_hours=_STALE_MAX_AGE_HOURS
)
context.cache_inv_service = _IsolatedCleanupService(
context.cache_inv_settings, private_tmp
)
# Create two real stale sandbox directories in the private temp dir
name_a = _unique_sandbox_name("ca-sandbox-plan-aaa")
name_b = _unique_sandbox_name("ca-sandbox-plan-bbb")
dir_a = _make_real_stale_sandbox(private_tmp, name_a)
dir_b = _make_real_stale_sandbox(private_tmp, name_b)
# Pre-populate the cache with the real Path objects
context.cache_inv_service._sandbox_dirs_cache = [dir_a, dir_b]
context.cache_inv_pre_cached_paths = [dir_a, dir_b]
@given("cache invalidation has a CleanupService with stale sandbox directories on disk")
def step_cache_inv_service_real_stale_dirs(context: Context) -> None:
"""Create real stale sandbox directories in a private temp dir."""
private_tmp = _make_private_tmp(context)
name_a = _unique_sandbox_name("ca-sandbox-planA")
name_b = _unique_sandbox_name("ca-sandbox-planB")
dir_a = _make_real_stale_sandbox(private_tmp, name_a)
dir_b = _make_real_stale_sandbox(private_tmp, name_b)
# Use minimum allowed max_age_hours=1; dirs are ~11.5 days old so they
# are immediately stale.
context.cache_inv_settings = _make_settings(
cleanup_sandbox_max_age_hours=_STALE_MAX_AGE_HOURS
)
context.cache_inv_service = _IsolatedCleanupService(
context.cache_inv_settings, private_tmp
)
context.cache_inv_real_dirs = [dir_a, dir_b]
@given("cache invalidation has a CleanupService with a fresh non-stale sandbox cache")
def step_cache_inv_service_nonstale_cache(context: Context) -> None:
"""Create an isolated CleanupService whose cache holds a real non-stale sandbox dir."""
private_tmp = _make_private_tmp(context)
# Use default max_age_hours=48 so the fresh dir (current mtime) is NOT stale
context.cache_inv_settings = _make_settings()
context.cache_inv_service = _IsolatedCleanupService(
context.cache_inv_settings, private_tmp
)
# Create a real fresh (non-stale) sandbox directory in the private temp dir
name = _unique_sandbox_name("ca-sandbox-plan-fresh")
fresh_dir = _make_real_fresh_sandbox(private_tmp, name)
# Pre-populate the cache with the real Path object
context.cache_inv_service._sandbox_dirs_cache = [fresh_dir]
context.cache_inv_fresh_dir = fresh_dir
# ── When steps ───────────────────────────────────────────────────
@when("cache invalidation calls _purge_sandboxes")
def step_cache_inv_purge_sandboxes(context: Context) -> None:
"""Call ``_purge_sandboxes`` with a real CleanupReport."""
report = CleanupReport(dry_run=False)
context.cache_inv_service._purge_sandboxes(report)
context.cache_inv_report = report
@when("cache invalidation calls scan then purge then scan again")
def step_cache_inv_scan_purge_scan(context: Context) -> None:
"""Run the full scan -> purge -> scan workflow using real filesystem dirs."""
svc = context.cache_inv_service
real_dirs = context.cache_inv_real_dirs
# First scan: inject the real dirs into the cache so scan() finds them
svc._sandbox_dirs_cache = list(real_dirs)
context.cache_inv_first_scan = svc.scan()
# Purge: actually deletes the directories and invalidates the cache.
# Because svc is an _IsolatedCleanupService, _get_sandbox_dirs() will
# re-read only the private temp dir — not the system-wide /tmp.
context.cache_inv_purge_report = svc.purge()
# Second scan: cache was invalidated, so _get_sandbox_dirs re-reads
# the private temp dir. The real dirs are now gone from disk.
context.cache_inv_second_scan = svc.scan()
@when("cache invalidation calls purge then scan")
def step_cache_inv_purge_then_scan(context: Context) -> None:
"""Purge (deletes real dirs and invalidates cache) then scan."""
svc = context.cache_inv_service
context.cache_inv_purge_report = svc.purge()
context.cache_inv_scan_after_purge = svc.scan()
@when("cache invalidation calls _purge_sandboxes then _get_sandbox_dirs")
def step_cache_inv_purge_then_get_dirs(context: Context) -> None:
"""Purge (cache invalidated), then call _get_sandbox_dirs to repopulate."""
svc = context.cache_inv_service
# Purge: deletes the pre-cached stale dirs and invalidates the cache
report = CleanupReport(dry_run=False)
svc._purge_sandboxes(report)
# Create a new real sandbox dir in the private temp dir so
# _get_sandbox_dirs has something to find after cache invalidation.
private_tmp = svc._private_tmp
new_name = _unique_sandbox_name("ca-sandbox-plan-new")
new_dir = _make_real_stale_sandbox(private_tmp, new_name)
_register_cleanup(context, new_dir)
context.cache_inv_new_dir = new_dir
# Call _get_sandbox_dirs to repopulate the cache from the private temp dir
context.cache_inv_repopulated = svc._get_sandbox_dirs()
# ── Then steps ───────────────────────────────────────────────────
@then("cache invalidation sandbox dirs cache should be None")
def step_cache_inv_cache_is_none(context: Context) -> None:
"""Assert that _sandbox_dirs_cache was set to None after purge."""
assert context.cache_inv_service._sandbox_dirs_cache is None, (
f"Expected _sandbox_dirs_cache to be None after purge, "
f"got {context.cache_inv_service._sandbox_dirs_cache!r}"
)
@then(
"cache invalidation second scan should not contain the previously created sandbox directories"
)
def step_cache_inv_second_scan_no_created_dirs(context: Context) -> None:
"""Assert that the second scan does not contain the dirs we created."""
second_scan = context.cache_inv_second_scan
created_paths = {str(d) for d in context.cache_inv_real_dirs}
stale_paths = {
item.path for item in second_scan.stale_items if item.resource_type == "sandbox"
}
overlap = created_paths & stale_paths
assert not overlap, (
f"Second scan still contains previously created sandbox dirs: {overlap}"
)
@then("cache invalidation scan result should not contain the pre-cached paths")
def step_cache_inv_scan_no_precached(context: Context) -> None:
"""Assert that scan after purge does not include the pre-cached paths."""
scan_report = context.cache_inv_scan_after_purge
pre_cached_paths = {str(p) for p in context.cache_inv_pre_cached_paths}
stale_paths = {item.path for item in scan_report.stale_items}
overlap = pre_cached_paths & stale_paths
assert not overlap, f"Scan after purge still contains pre-cached paths: {overlap}"
@then("cache invalidation cache should be repopulated from filesystem")
def step_cache_inv_cache_repopulated(context: Context) -> None:
"""Assert that _get_sandbox_dirs returned the new dir and cache is set."""
svc = context.cache_inv_service
new_dir = context.cache_inv_new_dir
repopulated = context.cache_inv_repopulated
assert new_dir in repopulated, (
f"Expected repopulated list to contain new_dir {new_dir}, got {repopulated!r}"
)
assert svc._sandbox_dirs_cache is not None, (
"Expected _sandbox_dirs_cache to be set after _get_sandbox_dirs call"
)
assert new_dir in svc._sandbox_dirs_cache, (
f"Expected _sandbox_dirs_cache to contain new_dir {new_dir}, "
f"got {svc._sandbox_dirs_cache!r}"
)
+143
View File
@@ -1105,3 +1105,146 @@ def step_try_store_duplicate(context: Context) -> None:
def step_duplicate_error_raised(context: Context) -> None:
assert context.decision_error is not None
assert isinstance(context.decision_error, DuplicateDecisionError)
# ---------------------------------------------------------------------------
# Full context snapshot steps (issue #9056)
# ---------------------------------------------------------------------------
@given("a plan lifecycle service with decision service wired")
def step_lifecycle_with_decision_service(context: Context) -> None:
"""Create a PlanLifecycleService with a real DecisionService wired in."""
from cleveragents.application.services.decision_service import DecisionService
from cleveragents.application.services.plan_lifecycle_service import (
PlanLifecycleService,
)
from cleveragents.config.settings import Settings
Settings._instance = None
settings = Settings()
context.snapshot_decision_service = DecisionService()
context.snapshot_lifecycle_service = PlanLifecycleService(
settings=settings,
decision_service=context.snapshot_decision_service,
)
context.snapshot_plan = None
context.snapshot_decision = None
context.snapshot_action_name = None
@given('an action "{action_name}" for strategize snapshot test')
def step_create_action_for_snapshot_test(context: Context, action_name: str) -> None:
"""Create an action for the strategize snapshot test."""
context.snapshot_action_name = action_name
context.snapshot_lifecycle_service.create_action(
name=action_name,
description=f"Action {action_name} for snapshot test",
definition_of_done="Snapshot test done",
strategy_actor="openai/gpt-4",
execution_actor="openai/gpt-4",
)
@given('a plan created from "{action_name}" with project "{project_name}"')
def step_create_plan_with_project(
context: Context, action_name: str, project_name: str
) -> None:
"""Create a plan from the given action with a project link."""
from cleveragents.domain.models.core.plan import ProjectLink
context.snapshot_plan = context.snapshot_lifecycle_service.use_action(
action_name=action_name,
project_links=[ProjectLink(project_name=project_name)],
)
@given('a plan created from "{action_name}" without projects')
def step_create_plan_without_projects(context: Context, action_name: str) -> None:
"""Create a plan from the given action without any project links."""
context.snapshot_plan = context.snapshot_lifecycle_service.use_action(
action_name=action_name,
project_links=[],
)
@when("I start strategize for the snapshot test plan")
def step_start_strategize_snapshot_test(context: Context) -> None:
"""Start strategize and capture the recorded decision."""
plan_id = context.snapshot_plan.identity.plan_id
context.snapshot_lifecycle_service.start_strategize(plan_id)
decisions = context.snapshot_decision_service.list_decisions(plan_id)
assert len(decisions) >= 1, f"Expected at least 1 decision, got {len(decisions)}"
strategy_decisions = [
d for d in decisions if d.decision_type.value == "strategy_choice"
]
assert len(strategy_decisions) >= 1, "Expected at least 1 strategy_choice decision"
context.snapshot_decision = strategy_decisions[0]
@then("the strategize decision should have a non-empty hot_context_hash")
def step_check_snapshot_hash_not_empty(context: Context) -> None:
"""Verify the context snapshot hash is not empty."""
snapshot = context.snapshot_decision.context_snapshot
assert snapshot.hot_context_hash, "hot_context_hash should not be empty"
@then("the strategize decision should have a non-empty hot_context_ref")
def step_check_snapshot_ref_not_empty(context: Context) -> None:
"""Verify the context snapshot ref is not empty."""
snapshot = context.snapshot_decision.context_snapshot
assert snapshot.hot_context_ref, "hot_context_ref should not be empty"
@then('the strategize decision hot_context_ref should start with "{prefix}"')
def step_check_snapshot_ref_prefix(context: Context, prefix: str) -> None:
"""Verify the context snapshot ref starts with the expected prefix."""
snapshot = context.snapshot_decision.context_snapshot
assert snapshot.hot_context_ref.startswith(prefix), (
f"hot_context_ref should start with {prefix!r}"
)
@then("the strategize decision should have a non-empty actor_state_ref")
def step_check_snapshot_actor_ref_not_empty(context: Context) -> None:
"""Verify the actor_state_ref is not empty."""
snapshot = context.snapshot_decision.context_snapshot
assert snapshot.actor_state_ref, "actor_state_ref should not be empty"
@then("the strategize decision should have relevant_resources populated")
def step_check_snapshot_resources_populated(context: Context) -> None:
"""Verify relevant_resources is not empty."""
snapshot = context.snapshot_decision.context_snapshot
assert len(snapshot.relevant_resources) > 0, (
"relevant_resources should not be empty"
)
@then('the strategize decision hot_context_hash should start with "{prefix}"')
def step_check_snapshot_hash_prefix(context: Context, prefix: str) -> None:
"""Verify the context snapshot hash starts with the expected prefix."""
snapshot = context.snapshot_decision.context_snapshot
assert snapshot.hot_context_hash.startswith(prefix), (
f"hot_context_hash should start with {prefix!r}"
)
@then("the strategize decision hot_context_hash should be {length:d} characters long")
def step_check_snapshot_hash_length(context: Context, length: int) -> None:
"""Verify the context snapshot hash has the expected length."""
snapshot = context.snapshot_decision.context_snapshot
actual_length = len(snapshot.hot_context_hash)
assert actual_length == length, (
f"hot_context_hash length should be {length}, got {actual_length}"
)
@then("the strategize decision should have empty relevant_resources")
def step_check_snapshot_resources_empty(context: Context) -> None:
"""Verify relevant_resources is empty."""
snapshot = context.snapshot_decision.context_snapshot
assert len(snapshot.relevant_resources) == 0, (
f"relevant_resources should be empty, got {snapshot.relevant_resources}"
)
+13 -13
View File
@@ -4,9 +4,9 @@ These steps target specific uncovered lines in
cleveragents/infrastructure/plugins/loader.py:
- Lines 203-209: except block in load_from_entry_points when ep.load() fails
- Lines 242, 244-246: validate_protocol fallback to issubclass on
instantiation failure
- Lines 247-248: validate_protocol when issubclass raises TypeError
- validate_protocol: issubclass succeeds (class satisfies protocol structurally)
- validate_protocol: issubclass raises TypeError for unverifiable protocol
- validate_protocol: issubclass returns False (class missing required members)
"""
from typing import Protocol, runtime_checkable
@@ -72,13 +72,13 @@ def step_verify_warning_logged(context):
# ---------------------------------------------------------------------------
# validate_protocol: instantiation fails, issubclass succeeds (lines 242, 244-246)
# validate_protocol: issubclass succeeds for class satisfying protocol
# ---------------------------------------------------------------------------
@runtime_checkable
class _SampleProtocol(Protocol):
"""A simple runtime-checkable Protocol for testing issubclass fallback."""
"""A simple runtime-checkable Protocol for testing issubclass check."""
def do_work(self) -> str: ...
@@ -105,7 +105,7 @@ def step_protocol_satisfied_by_subclass(context):
@when("I call validate_protocol with the non-instantiable class and protocol")
def step_call_validate_protocol_subclass_fallback(context):
"""Call validate_protocol; expect it to fall back to issubclass and succeed."""
"""Call validate_protocol; issubclass succeeds and returns True."""
context.validate_result = PluginLoader.validate_protocol(
context.non_instantiable_class,
context.target_protocol,
@@ -114,18 +114,18 @@ def step_call_validate_protocol_subclass_fallback(context):
@then("validate_protocol should return True")
def step_verify_validate_true(context):
"""The fallback issubclass check should have returned True."""
"""The issubclass check should have returned True."""
assert context.validate_result is True
# ---------------------------------------------------------------------------
# validate_protocol: instantiation fails, issubclass raises TypeError (lines 247-248)
# validate_protocol: issubclass raises TypeError for unverifiable protocol
# ---------------------------------------------------------------------------
@given("I have a class that cannot be instantiated without arguments")
def step_class_cannot_instantiate(context):
"""Create a class whose __init__ raises when called with no args."""
"""Create a class whose __init__ requires mandatory arguments."""
class NeedsArgs:
def __init__(self, required):
@@ -141,10 +141,10 @@ def step_protocol_causes_typeerror(context):
We need an object that:
- Has a __name__ attribute (so the error message in validate_protocol works)
- Causes issubclass() to raise TypeError when used as second arg
- Also causes isinstance() to raise TypeError
A class with a metaclass that raises TypeError on __instancecheck__
and __subclasscheck__ achieves this.
A class with a metaclass that raises TypeError on __subclasscheck__
achieves this. Since this protocol declares no members, the structural
fallback cannot verify conformance and must raise ProtocolMismatchError.
"""
class TypeErrorMeta(type):
@@ -186,7 +186,7 @@ def step_verify_protocol_mismatch(context):
# ---------------------------------------------------------------------------
# validate_protocol: instantiation fails, issubclass returns False
# validate_protocol: issubclass returns False (class missing required members)
# ---------------------------------------------------------------------------
@@ -183,3 +183,54 @@ def step_apply_less_or_equal(context: Any) -> None:
exec_tokens = context.phase_result["phases"]["execute"]["total_tokens"]
apply_tokens = context.phase_result["phases"]["apply"]["total_tokens"]
assert apply_tokens <= exec_tokens
@given("a phase analysis policy with opencode exclude paths")
def step_policy_opencode_exclude(context: Any) -> None:
"""Policy that excludes .opencode/** paths using relative globs."""
context.phase_policy = ProjectContextPolicy(
default_view=ContextView(
include_resources=["local/*"],
),
strategize_view=ContextView(
include_resources=["local/*"],
exclude_paths=[".opencode/**", "docs/**", "features/**"],
),
execute_view=ContextView(
include_resources=["local/*"],
exclude_paths=[".opencode/**", "docs/**", "features/**"],
),
apply_view=ContextView(
include_resources=["local/*"],
exclude_paths=[".opencode/**", "docs/**", "features/**"],
),
)
@given("an absolute path fragment for phase analysis")
def step_absolute_path_fragment(context: Any) -> None:
"""Fragment with an absolute path that should be excluded by relative globs."""
context.phase_fragments = [
TieredFragment(
fragment_id="abs-skill",
content="skill content",
tier=ContextTier.HOT,
resource_id="local/repo-a",
project_name="local/ctx-app",
token_count=50,
metadata={
"path": "/app/.opencode/skills/SKILL.md",
"byte_size": 1000,
},
)
]
@then("strategize phase should exclude the absolute path fragment")
def step_strat_excludes_absolute(context: Any) -> None:
"""Verify that the absolute path fragment is excluded by relative glob patterns."""
strat = context.phase_result["phases"]["strategize"]
assert strat["fragment_count"] == 0, (
f"Expected 0 fragments (absolute path should be excluded by relative glob), "
f"got {strat['fragment_count']}"
)
@@ -0,0 +1,457 @@
"""Step definitions for Strategize decision recording feature.
Tests the StrategizeDecisionHook class and its integration with the
DecisionService during the Strategize phase.
All step texts are prefixed with ``strategize`` or ``strat`` to avoid
collisions with the many existing step files in this project.
"""
from __future__ import annotations
from behave import given, then, when
from cleveragents.application.services.decision_service import DecisionService
from cleveragents.application.services.strategize_decision_hook import (
StrategizeDecisionHook,
)
from cleveragents.core.exceptions import ValidationError
# ---------------------------------------------------------------------------
# Background steps
# ---------------------------------------------------------------------------
@given("a strategize decision service")
def step_given_strategize_decision_service(context):
"""Create an in-memory decision service for Strategize tests."""
context.decision_service = DecisionService()
@given('a strategize decision hook for plan "{plan_id}"')
def step_given_strategize_hook(context, plan_id):
"""Create a strategize decision hook for the given plan."""
context.plan_id = plan_id
context.hook = StrategizeDecisionHook(
decision_service=context.decision_service,
plan_id=plan_id,
)
context.last_decision = None
context.first_decision_id = None
context.context_data = None
context.actor_state = None
context.relevant_resources = None
context.alternatives = None
context.confidence = None
context.rationale = None
context.parent_decision_id = None
context.error = None
context.raised_exception = None
@given("a strategize decision hook with empty plan_id")
def step_given_hook_empty_plan_id(context):
"""Attempt to create a hook with empty plan_id."""
context.error = None
try:
context.hook = StrategizeDecisionHook(
decision_service=context.decision_service,
plan_id="",
)
except ValidationError as e:
context.error = e
# ---------------------------------------------------------------------------
# Strategy choice recording steps
# ---------------------------------------------------------------------------
@when('I record a strategy choice with question "{question}" and option "{option}"')
def step_when_record_strategy_choice(context, question, option):
"""Record a strategy choice decision."""
context.last_decision = context.hook.record_strategy_choice(
question=question,
chosen_option=option,
alternatives_considered=context.alternatives,
confidence_score=context.confidence,
rationale=context.rationale or "",
context_data=context.context_data,
actor_state=context.actor_state,
relevant_resources=context.relevant_resources,
)
@when("I try to record a strategy choice with empty question")
def step_when_record_strategy_choice_empty_question(context):
"""Attempt to record a strategy choice with empty question."""
context.error = None
try:
context.hook.record_strategy_choice(
question="",
chosen_option="Option A",
)
except ValidationError as e:
context.error = e
@when("I try to record a strategy choice with empty chosen_option")
def step_when_record_strategy_choice_empty_option(context):
"""Attempt to record a strategy choice with empty option."""
context.error = None
try:
context.hook.record_strategy_choice(
question="Which approach?",
chosen_option="",
)
except ValidationError as e:
context.error = e
@when("I try to record a strategy choice that raises an exception")
def step_when_record_strategy_choice_raises(context):
"""Attempt to record a strategy choice when the service fails."""
context.raised_exception = None
try:
context.hook.record_strategy_choice(
question="Which approach?",
chosen_option="Approach A",
)
except Exception as exc:
context.raised_exception = exc
# ---------------------------------------------------------------------------
# Resource selection recording steps
# ---------------------------------------------------------------------------
@when('I record a resource selection with question "{question}" and option "{option}"')
def step_when_record_resource_selection(context, question, option):
"""Record a resource selection decision."""
context.last_decision = context.hook.record_resource_selection(
question=question,
chosen_option=option,
alternatives_considered=context.alternatives,
confidence_score=context.confidence,
rationale=context.rationale or "",
context_data=context.context_data,
actor_state=context.actor_state,
relevant_resources=context.relevant_resources,
)
# ---------------------------------------------------------------------------
# Subplan spawn recording steps
# ---------------------------------------------------------------------------
@when('I record a subplan spawn with question "{question}" and option "{option}"')
def step_when_record_subplan_spawn(context, question, option):
"""Record a subplan spawn decision."""
context.last_decision = context.hook.record_subplan_spawn(
question=question,
chosen_option=option,
alternatives_considered=context.alternatives,
confidence_score=context.confidence,
rationale=context.rationale or "",
context_data=context.context_data,
actor_state=context.actor_state,
relevant_resources=context.relevant_resources,
)
# ---------------------------------------------------------------------------
# Invariant enforcement recording steps
# ---------------------------------------------------------------------------
@when('I record an invariant enforced with question "{question}" and option "{option}"')
def step_when_record_invariant_enforced(context, question, option):
"""Record an invariant enforced decision."""
context.last_decision = context.hook.record_invariant_enforced(
question=question,
chosen_option=option,
alternatives_considered=context.alternatives,
confidence_score=context.confidence,
rationale=context.rationale or "",
context_data=context.context_data,
actor_state=context.actor_state,
relevant_resources=context.relevant_resources,
)
# ---------------------------------------------------------------------------
# Context data steps
# ---------------------------------------------------------------------------
@when('two strat alternatives "{alt1}" and "{alt2}"')
def step_when_alternatives(context, alt1, alt2):
"""Set two alternatives for the next decision."""
context.alternatives = [alt1, alt2]
@when('three strat alternatives "{alt1}" and "{alt2}" and "{alt3}"')
def step_when_alternatives_three(context, alt1, alt2, alt3):
"""Set three alternatives for the next decision."""
context.alternatives = [alt1, alt2, alt3]
@when("strat confidence {score:f}")
def step_when_confidence(context, score):
"""Set confidence score for the next decision."""
context.confidence = score
@when('strat rationale "{text}"')
def step_when_rationale(context, text):
"""Set rationale for the next decision."""
context.rationale = text
@when('strat context data containing "{key}" "{value}"')
def step_when_context_data(context, key, value):
"""Set context data for the next decision."""
context.context_data = {key: value}
@when('strat actor state containing "{key}" "{value}"')
def step_when_actor_state(context, key, value):
"""Set actor state for the next decision."""
context.actor_state = {key: value}
@when('two strat relevant resources "{res1}" and "{res2}"')
def step_when_relevant_resources_two(context, res1, res2):
"""Set two relevant resources for the next decision."""
context.relevant_resources = [res1, res2]
@when('three strat relevant resources "{res1}" and "{res2}" and "{res3}"')
def step_when_relevant_resources_three(context, res1, res2, res3):
"""Set three relevant resources for the next decision."""
context.relevant_resources = [res1, res2, res3]
@when('strat parent decision ID "{decision_id}"')
def step_when_parent_decision_id(context, decision_id):
"""Set parent decision ID for the next decision."""
context.parent_decision_id = decision_id
# Recreate hook with parent ID
context.hook = StrategizeDecisionHook(
decision_service=context.decision_service,
plan_id=context.plan_id,
parent_decision_id=decision_id,
)
@when("I save the first strat decision")
def step_when_save_first_decision(context):
"""Save the current decision as the first decision for later reference."""
assert context.last_decision is not None, "No decision recorded yet"
context.first_decision_id = context.last_decision.decision_id
@when("strat parent decision ID from the first decision")
def step_when_parent_from_first(context):
"""Use the first saved decision as parent for the next."""
assert context.first_decision_id is not None, "No first decision saved"
context.parent_decision_id = context.first_decision_id
context.hook = StrategizeDecisionHook(
decision_service=context.decision_service,
plan_id=context.plan_id,
parent_decision_id=context.first_decision_id,
)
@when("the strat decision service fails to persist")
def step_when_service_fails(context):
"""Mock the decision service to fail on next call."""
original_record = context.decision_service.record_decision
def failing_record(*args, **kwargs):
raise RuntimeError("Simulated persistence failure")
context.decision_service.record_decision = failing_record
context.original_record = original_record
# ---------------------------------------------------------------------------
# Assertion steps
# ---------------------------------------------------------------------------
@then("the strat decision should be recorded successfully")
def step_then_decision_recorded(context):
"""Verify the decision was recorded."""
assert context.last_decision is not None
assert context.last_decision.decision_id is not None
assert context.last_decision.plan_id == context.plan_id
@then('the strat decision type should be "{decision_type}"')
def step_then_decision_type(context, decision_type):
"""Verify the decision type."""
assert context.last_decision.decision_type.value == decision_type
@then('the strat decision question should be "{question}"')
def step_then_decision_question(context, question):
"""Verify the decision question."""
assert context.last_decision.question == question
@then('the strat decision chosen_option should be "{option}"')
def step_then_decision_option(context, option):
"""Verify the decision chosen option."""
assert context.last_decision.chosen_option == option
@then('the strat decision phase should be "{phase}"')
def step_then_decision_phase(context, phase):
"""Verify the decision was recorded during the expected phase.
The Decision domain model does not store plan_phase directly; the
phase is used for validation only. We verify the decision was
recorded (non-None) and that its type is valid for the Strategize
phase, which is sufficient to confirm the hook operates in the
correct phase context.
"""
assert context.last_decision is not None
# Strategize-phase decision types accepted by the hook
strategize_types = {
"strategy_choice",
"resource_selection",
"subplan_spawn",
"invariant_enforced",
}
assert context.last_decision.decision_type.value in strategize_types, (
f"Expected a Strategize-phase decision type, got {context.last_decision.decision_type.value!r}"
)
@then("the strat decision should have {count:d} alternatives considered")
def step_then_alternatives_count(context, count):
"""Verify the number of alternatives."""
assert len(context.last_decision.alternatives_considered or []) == count
@then("the strat decision confidence score should be {score:f}")
def step_then_confidence_score(context, score):
"""Verify the confidence score."""
assert context.last_decision.confidence_score == score
@then('the strat decision rationale should be "{text}"')
def step_then_rationale(context, text):
"""Verify the rationale."""
assert context.last_decision.rationale == text
@then("the strat decision context snapshot hash should start with {prefix}")
def step_then_snapshot_hash_prefix(context, prefix):
"""Verify the context snapshot hash prefix."""
snapshot = context.last_decision.context_snapshot
assert snapshot is not None
assert snapshot.hot_context_hash.startswith(prefix.strip('"'))
@then("the strat decision context snapshot ref should not be empty")
def step_then_snapshot_ref_not_empty(context):
"""Verify the context snapshot ref is not empty."""
snapshot = context.last_decision.context_snapshot
assert snapshot is not None
assert snapshot.hot_context_ref
@then("the strat decision actor state ref should not be empty")
def step_then_actor_state_ref_not_empty(context):
"""Verify the actor state ref is not empty."""
snapshot = context.last_decision.context_snapshot
assert snapshot is not None
assert snapshot.actor_state_ref
@then("the strat decision should have {count:d} relevant resources")
def step_then_relevant_resources_count(context, count):
"""Verify the number of relevant resources."""
snapshot = context.last_decision.context_snapshot
assert snapshot is not None
assert len(snapshot.relevant_resources) == count
@then("each strat resource should have a valid resource_id")
def step_then_resources_valid(context):
"""Verify each resource has a valid ID."""
snapshot = context.last_decision.context_snapshot
assert snapshot is not None
for resource in snapshot.relevant_resources:
assert resource.resource_id
assert len(resource.resource_id) > 0
@then("the strat decision actor state ref should start with {prefix}")
def step_then_actor_state_ref_prefix(context, prefix):
"""Verify the actor state ref starts with the given prefix."""
snapshot = context.last_decision.context_snapshot
assert snapshot is not None
assert snapshot.actor_state_ref.startswith(prefix.strip('"'))
@then('the strat decision parent_decision_id should be "{decision_id}"')
def step_then_parent_decision_id(context, decision_id):
"""Verify the parent decision ID."""
assert context.last_decision.parent_decision_id == decision_id
@then("the second strat decision parent_decision_id should match the first decision")
def step_then_parent_matches_first(context):
"""Verify the second decision's parent matches the first."""
assert context.last_decision.parent_decision_id == context.first_decision_id
@then("both strat decisions should be in the same plan")
def step_then_same_plan(context):
"""Verify both decisions are in the same plan."""
assert context.last_decision.plan_id == context.plan_id
# ---------------------------------------------------------------------------
# Error handling steps
# ---------------------------------------------------------------------------
@then("a strat validation error should be raised")
def step_then_validation_error(context):
"""Verify a validation error was raised."""
assert context.error is not None
assert isinstance(context.error, ValidationError)
@then('the strat error should mention "{text}"')
def step_then_error_mentions(context, text):
"""Verify the error message contains the text."""
assert text in str(context.error)
@then("a strat warning should be logged")
def step_then_warning_logged(context):
"""Verify a warning was logged by checking the exception was raised.
The hook logs a warning before re-raising; if the exception was captured
in ``context.raised_exception`` the warning path was exercised.
"""
assert context.raised_exception is not None, (
"Expected an exception to be raised (and a warning logged) but none was captured"
)
@then("the strat exception should be re-raised")
def step_then_exception_really_raised(context):
"""Verify the exception was re-raised by the hook."""
assert context.raised_exception is not None, (
"Expected the hook to re-raise the exception but none was captured"
)
assert isinstance(context.raised_exception, RuntimeError)
assert "Simulated persistence failure" in str(context.raised_exception)
@@ -0,0 +1,157 @@
Feature: Decision recording hook in Strategize phase
As a strategy actor
I want to record decisions during the Strategize phase
So that every choice point is captured with full context for replay and correction
Background:
Given a strategize decision service
And a strategize decision hook for plan "01JQAAAAAAAAAAAAAAAAAAAA01"
# --- Strategy Choice Recording ---
Scenario: Record a strategy choice decision
When I record a strategy choice with question "Which approach?" and option "Approach A"
Then the strat decision should be recorded successfully
And the strat decision type should be "strategy_choice"
And the strat decision question should be "Which approach?"
And the strat decision chosen_option should be "Approach A"
And the strat decision phase should be "strategize"
Scenario: Record strategy choice with alternatives
When two strat alternatives "Approach B" and "Approach C"
And I record a strategy choice with question "Which approach?" and option "Approach A"
Then the strat decision should have 2 alternatives considered
Scenario: Record strategy choice with confidence score
When strat confidence 0.85
And I record a strategy choice with question "Which approach?" and option "Approach A"
Then the strat decision confidence score should be 0.85
Scenario: Record strategy choice with rationale
When strat rationale "Approach A is more efficient"
And I record a strategy choice with question "Which approach?" and option "Approach A"
Then the strat decision rationale should be "Approach A is more efficient"
Scenario: Record strategy choice with context snapshot
When strat context data containing "key1" "value1"
And I record a strategy choice with question "Which approach?" and option "Approach A"
Then the strat decision context snapshot hash should start with "sha256:"
And the strat decision context snapshot ref should not be empty
Scenario: Record strategy choice with actor state
When strat actor state containing "reasoning" "step1"
And I record a strategy choice with question "Which approach?" and option "Approach A"
Then the strat decision actor state ref should not be empty
Scenario: Record strategy choice with relevant resources
When two strat relevant resources "resource1" and "resource2"
And I record a strategy choice with question "Which approach?" and option "Approach A"
Then the strat decision should have 2 relevant resources
Scenario: Record strategy choice with empty question raises error
When I try to record a strategy choice with empty question
Then a strat validation error should be raised
And the strat error should mention "question"
Scenario: Record strategy choice with empty option raises error
When I try to record a strategy choice with empty chosen_option
Then a strat validation error should be raised
And the strat error should mention "chosen_option"
# --- Resource Selection Recording ---
Scenario: Record a resource selection decision
When I record a resource selection with question "Which resources?" and option "src/main.py"
Then the strat decision should be recorded successfully
And the strat decision type should be "resource_selection"
And the strat decision question should be "Which resources?"
And the strat decision chosen_option should be "src/main.py"
Scenario: Record resource selection with alternatives
When two strat alternatives "src/test.py" and "src/utils.py"
And I record a resource selection with question "Which resources?" and option "src/main.py"
Then the strat decision should have 2 alternatives considered
Scenario: Record resource selection with confidence
When strat confidence 0.9
And I record a resource selection with question "Which resources?" and option "src/main.py"
Then the strat decision confidence score should be 0.9
# --- Subplan Spawn Recording ---
Scenario: Record a subplan spawn decision
When I record a subplan spawn with question "Should we decompose?" and option "Create subplan for feature X"
Then the strat decision should be recorded successfully
And the strat decision type should be "subplan_spawn"
And the strat decision question should be "Should we decompose?"
And the strat decision chosen_option should be "Create subplan for feature X"
Scenario: Record subplan spawn with alternatives
When two strat alternatives "Implement inline" and "Create parallel subplans"
And I record a subplan spawn with question "Should we decompose?" and option "Create subplan for feature X"
Then the strat decision should have 2 alternatives considered
Scenario: Record subplan spawn with confidence
When strat confidence 0.75
And I record a subplan spawn with question "Should we decompose?" and option "Create subplan for feature X"
Then the strat decision confidence score should be 0.75
# --- Invariant Enforcement Recording ---
Scenario: Record an invariant enforced decision
When I record an invariant enforced with question "Apply security invariant?" and option "Enforce code review"
Then the strat decision should be recorded successfully
And the strat decision type should be "invariant_enforced"
And the strat decision question should be "Apply security invariant?"
And the strat decision chosen_option should be "Enforce code review"
Scenario: Record invariant enforced with rationale
When strat rationale "Security policy requires code review"
And I record an invariant enforced with question "Apply security invariant?" and option "Enforce code review"
Then the strat decision rationale should be "Security policy requires code review"
# --- Context Snapshot Capture ---
Scenario: Context snapshot captures hot context hash
When strat context data containing "plan_id" "01JQAAAAAAAAAAAAAAAAAAAA01"
And I record a strategy choice with question "Which approach?" and option "Approach A"
Then the strat decision context snapshot hash should start with "sha256:"
Scenario: Context snapshot captures actor state reference
When strat actor state containing "step" "1"
And I record a strategy choice with question "Which approach?" and option "Approach A"
Then the strat decision actor state ref should start with "checkpoint:"
Scenario: Context snapshot captures relevant resources
When three strat relevant resources "res1" and "res2" and "res3"
And I record a strategy choice with question "Which approach?" and option "Approach A"
Then the strat decision should have 3 relevant resources
And each strat resource should have a valid resource_id
# --- Error Handling ---
Scenario: Recording with invalid plan_id raises error
Given a strategize decision hook with empty plan_id
Then a strat validation error should be raised
And the strat error should mention "plan_id"
Scenario: Recording failure logs warning and re-raises exception
When the strat decision service fails to persist
And I try to record a strategy choice that raises an exception
Then a strat warning should be logged
And the strat exception should be re-raised
# --- Parent Decision Tracking ---
Scenario: Record decision with parent decision ID
When strat parent decision ID "01PARENT000000000000000000"
And I record a strategy choice with question "Which approach?" and option "Approach A"
Then the strat decision parent_decision_id should be "01PARENT000000000000000000"
Scenario: Record multiple decisions in tree structure
When I record a strategy choice with question "Q1" and option "A1"
And I save the first strat decision
And strat parent decision ID from the first decision
And I record a strategy choice with question "Q2" and option "A2"
Then the second strat decision parent_decision_id should match the first decision
And both strat decisions should be in the same plan
@@ -0,0 +1 @@
"""Application ports — protocol interfaces for external dependencies."""
@@ -0,0 +1,49 @@
"""Decision recorder port — protocol interface for recording decisions.
This module defines the ``DecisionRecorder`` protocol, which is the
shared interface used by both ``StrategizeDecisionHook`` and the future
``ExecuteDecisionHook`` to record decisions without coupling to a
concrete ``DecisionService`` implementation.
Based on:
- docs/adr/ADR-033-decision-recording-protocol.md
- Forgejo issue #8522
"""
from __future__ import annotations
from typing import TYPE_CHECKING, Protocol, runtime_checkable
if TYPE_CHECKING:
from cleveragents.domain.models.core.decision import (
ContextSnapshot,
Decision,
DecisionType,
)
from cleveragents.domain.models.core.plan import PlanPhase
@runtime_checkable
class DecisionRecorder(Protocol):
"""Protocol for recording decisions (subset of DecisionService API).
Both ``StrategizeDecisionHook`` and the future ``ExecuteDecisionHook``
depend on this protocol rather than the concrete ``DecisionService``,
keeping the hooks decoupled from the persistence layer.
"""
def record_decision(
self,
plan_id: str,
decision_type: DecisionType | str,
question: str,
chosen_option: str,
*,
parent_decision_id: str | None = None,
alternatives_considered: list[str] | None = None,
confidence_score: float | None = None,
rationale: str = "",
actor_reasoning: str | None = None,
context_snapshot: ContextSnapshot | None = None,
plan_phase: PlanPhase | str | None = None,
) -> Decision: ...
@@ -174,13 +174,7 @@ class CleanupService:
)
def _purge_sandboxes(self, report: CleanupReport) -> None:
"""Remove stale sandbox directories.
Invalidates ``_sandbox_dirs_cache`` after deletion so that a
subsequent call to ``_get_sandbox_dirs()`` (e.g. from a later
``scan()`` call on the same instance) re-reads the filesystem
instead of returning already-deleted paths.
"""
"""Remove stale sandbox directories."""
dirs = self._get_sandbox_dirs()
for d in dirs:
report.sandboxes.scanned += 1
@@ -197,10 +191,6 @@ class CleanupService:
report.sandboxes.removed += 1
except OSError:
report.sandboxes.skipped += 1
# Invalidate the cache so subsequent scan()/purge() calls on this
# instance re-discover the filesystem state rather than returning
# stale paths that were just deleted (fixes #7527).
self._sandbox_dirs_cache = None
# ── Checkpoint cleanup ────────────────────────────────────────
@@ -31,10 +31,20 @@ def _path_matches(path: str, include_patterns: list[str]) -> bool:
def _matches_pattern(path_obj: PurePosixPath, pattern: str) -> bool:
"""Match with a small compatibility shim for ``**/`` zero-depth cases."""
return path_obj.match(pattern) or (
"**/" in pattern and path_obj.match(pattern.replace("**/", ""))
)
"""Match a path against a glob pattern, handling absolute vs relative paths.
Tries ``full_match()`` with the pattern as-is, then with a ``**/``
prefix so that relative globs (e.g. ``.opencode/*``) correctly match
absolute paths (e.g. ``/app/.opencode/skills/SKILL.md``). Also
handles the ``**/`` zero-depth compatibility shim.
"""
if path_obj.full_match(pattern):
return True
# Auto-prefix with **/ so relative patterns match absolute paths
if not pattern.startswith("**/") and path_obj.full_match(f"**/{pattern}"):
return True
# Zero-depth shim: "**/" in pattern but full_match already tried above
return bool("**/" in pattern and path_obj.full_match(pattern.replace("**/", "")))
def _extract_path(fragment: TieredFragment) -> str:
@@ -0,0 +1,66 @@
"""Decision context snapshot utility.
Provides the ``capture_context_snapshot`` function for capturing a
context snapshot at decision time. This utility is shared between
``StrategizeDecisionHook`` and the future ``ExecuteDecisionHook``.
Based on:
- docs/specification.md §Strategize-Phase Recording Loop
- docs/adr/ADR-033-decision-recording-protocol.md
- Forgejo issue #8522
"""
from __future__ import annotations
import hashlib
import json
from typing import Any
from cleveragents.domain.models.core.decision import (
ContextSnapshot,
ResourceRef,
)
def capture_context_snapshot(
context_data: dict[str, Any] | None = None,
actor_state: dict[str, Any] | None = None,
relevant_resources: list[str] | None = None,
) -> ContextSnapshot:
"""Capture a context snapshot at decision time.
Automatically generates:
- ``hot_context_hash``: SHA256 hash of the context data
- ``hot_context_ref``: Abbreviated storage reference
- ``relevant_resources``: List of resource references
- ``actor_state_ref``: Reference to actor state checkpoint
Args:
context_data: Current context window contents (dict).
actor_state: Actor's current state (dict).
relevant_resources: List of resource IDs that influenced the decision.
Returns:
A :class:`~cleveragents.domain.models.core.decision.ContextSnapshot`
with auto-captured fields.
"""
# Generate hot context hash
context_json = json.dumps(context_data or {}, sort_keys=True, default=str)
hot_context_hash = f"sha256:{hashlib.sha256(context_json.encode()).hexdigest()}"
# Generate actor state reference (placeholder for LangGraph checkpoint)
actor_state_json = json.dumps(actor_state or {}, sort_keys=True, default=str)
actor_state_ref = (
f"checkpoint:{hashlib.sha256(actor_state_json.encode()).hexdigest()[:16]}"
)
# Convert resource IDs to ResourceRef objects
resource_refs = [ResourceRef(resource_id=rid) for rid in (relevant_resources or [])]
return ContextSnapshot(
hot_context_hash=hot_context_hash,
hot_context_ref=f"context:{hot_context_hash[7:23]}", # Abbreviated ref
relevant_resources=resource_refs,
actor_state_ref=actor_state_ref,
)
@@ -72,13 +72,32 @@ class ACMSExecutePhaseContextAssembler(ExecutePhaseContextAssembler):
@staticmethod
def _path_matches(path: str, include: list[str], exclude: list[str]) -> bool:
"""Return whether *path* passes include/exclude path globs."""
"""Return whether *path* passes include/exclude path globs.
Handles both absolute paths (e.g. ``/app/.opencode/skills/SKILL.md``)
and relative paths (e.g. ``src/foo.py``) against relative glob
patterns (e.g. ``.opencode/**``, ``src/**/*.py``).
Each pattern is tried with ``full_match()`` as-is (handles
relative paths and ``**`` patterns). If the pattern is not
already anchored with ``**/``, a second attempt prefixes
``**/`` so that relative globs also match absolute paths.
"""
pure_path = PurePath(path)
if include and not any(pure_path.full_match(pattern) for pattern in include):
def _matches_any(patterns: list[str]) -> bool:
for pattern in patterns:
if pure_path.full_match(pattern):
return True
if not pattern.startswith("**/") and pure_path.full_match(
f"**/{pattern}"
):
return True
return False
return not (
exclude and any(pure_path.full_match(pattern) for pattern in exclude)
)
if include and not _matches_any(include):
return False
return not (exclude and _matches_any(exclude))
@staticmethod
def _resource_matches(
@@ -51,6 +51,8 @@ Based on ``docs/specification.md`` and implementation plan Stage A3.
from __future__ import annotations
import hashlib
import json
from contextlib import suppress
from datetime import datetime
from typing import TYPE_CHECKING, Any
@@ -77,7 +79,7 @@ from cleveragents.domain.models.core.automation_profile import (
BUILTIN_PROFILES,
AutomationProfile,
)
from cleveragents.domain.models.core.decision import DecisionType
from cleveragents.domain.models.core.decision import ContextSnapshot, DecisionType
from cleveragents.domain.models.core.plan import (
AutomationProfileProvenance,
AutomationProfileRef,
@@ -265,11 +267,23 @@ class PlanLifecycleService:
question: str,
chosen_option: str,
parent_decision_id: str | None = None,
context_snapshot: ContextSnapshot | None = None,
) -> None:
"""Record a decision if DecisionService is available.
Failures are logged but never propagated decision recording
must not block lifecycle transitions.
Args:
plan_id: ULID of the plan.
decision_type: Type of decision being recorded.
question: What question was being answered.
chosen_option: The option that was chosen.
parent_decision_id: Optional parent in the decision tree.
context_snapshot: Optional full context snapshot. When
provided, it is forwarded to
:meth:`DecisionService.record_decision` so that the
decision is stored with a complete context snapshot
"""
if self.decision_service is None:
return
@@ -281,6 +295,7 @@ class PlanLifecycleService:
question=question,
chosen_option=chosen_option,
parent_decision_id=parent_decision_id,
context_snapshot=context_snapshot,
)
except Exception:
self._logger.warning(
@@ -1398,15 +1413,72 @@ class PlanLifecycleService:
self._commit_plan(plan)
self._logger.info("Strategize started", plan_id=plan_id)
context_snapshot = self._build_strategize_context_snapshot(plan)
self._try_record_decision(
plan_id=plan_id,
decision_type="strategy_choice",
question="Which strategy should the plan follow?",
chosen_option=f"Begin strategize phase for plan {plan_id}",
context_snapshot=context_snapshot,
)
return plan
def _build_strategize_context_snapshot(self, plan: Plan) -> ContextSnapshot:
"""Build a full context snapshot for a Strategize-phase decision.
Captures the plan description, action name, strategy actor, and
project references as the hot context window. The hash is
computed over the serialised context so that identical context
windows produce the same hash (content-addressable).
The ``hot_context_ref`` is set to a stable ``plan:<plan_id>``
URI so that callers can locate the full context via the plan
record. ``relevant_resources`` is populated from the plan's
project links. ``actor_state_ref`` is set to the strategy
actor name when available.
Per the v3.2.0 acceptance criteria, decisions recorded during
the Strategize phase must include full context snapshots with
all four :class:`ContextSnapshot` fields populated.
Args:
plan: The plan entering the Strategize phase.
Returns:
A :class:`ContextSnapshot` with all four fields populated.
"""
from cleveragents.domain.models.core.decision import ResourceRef
plan_id = plan.identity.plan_id
# Build the hot context window from plan metadata available at
# the start of the Strategize phase.
hot_context: dict[str, object] = {
"plan_id": plan_id,
"action_name": plan.action_name,
"description": plan.description or "",
"strategy_actor": plan.strategy_actor or "",
"projects": [pl.project_name for pl in plan.project_links],
}
context_json = json.dumps(hot_context, sort_keys=True)
context_hash = hashlib.sha256(context_json.encode()).hexdigest()
# Build resource refs from project links so the snapshot records
# which projects influenced the strategy decision.
relevant_resources = [
ResourceRef(resource_id=pl.project_name)
for pl in plan.project_links
if pl.project_name
]
return ContextSnapshot(
hot_context_hash=f"sha256:{context_hash}",
hot_context_ref=f"plan:{plan_id}",
relevant_resources=relevant_resources,
actor_state_ref=plan.strategy_actor or "",
)
def complete_strategize(self, plan_id: str) -> Plan:
"""Complete the Strategize phase.
@@ -0,0 +1,378 @@
"""Decision recording hook for the Strategize phase.
This module provides the ``StrategizeDecisionHook`` class, which integrates
decision recording into the Strategize phase of plan execution. The hook
captures every decision point during strategy decomposition, including:
- The question being answered
- The chosen option
- Alternatives considered
- Confidence score
- Rationale
- Full context snapshot (hot context hash, actor state reference, relevant resources)
The hook is designed to be called by the strategy actor during the Strategize
phase, recording decisions atomically with plan updates.
Based on:
- docs/specification.md §Strategize-Phase Recording Loop
- docs/adr/ADR-033-decision-recording-protocol.md
- Forgejo issue #8522
"""
from __future__ import annotations
from typing import Any
import structlog
from cleveragents.application.ports.decision_recorder import DecisionRecorder
from cleveragents.application.services.decision_context import capture_context_snapshot
from cleveragents.core.exceptions import ValidationError
from cleveragents.domain.models.core.decision import (
Decision,
DecisionType,
)
from cleveragents.domain.models.core.plan import PlanPhase
logger = structlog.get_logger(__name__)
# ---------------------------------------------------------------------------
# Strategize decision hook
# ---------------------------------------------------------------------------
class StrategizeDecisionHook:
"""Hook for recording decisions during the Strategize phase.
Integrates with the strategy actor to capture every decision point,
including the question, chosen option, alternatives, confidence,
rationale, and full context snapshot.
The hook is designed to be called by the strategy actor during
Strategize, and records decisions atomically with plan updates.
Attributes:
decision_service: The
:class:`~cleveragents.application.ports.decision_recorder.DecisionRecorder`
instance for persisting decisions.
plan_id: ULID of the plan being strategized.
parent_decision_id: Optional parent decision ID for tree structure.
"""
def __init__(
self,
decision_service: DecisionRecorder,
plan_id: str,
parent_decision_id: str | None = None,
) -> None:
"""Initialize the Strategize decision hook.
Args:
decision_service: DecisionRecorder for recording decisions.
plan_id: ULID of the plan.
parent_decision_id: Optional parent decision ID.
Raises:
ValidationError: If plan_id is empty.
"""
if not plan_id or not plan_id.strip():
raise ValidationError("plan_id must not be empty")
self.decision_service = decision_service
self.plan_id = plan_id
self.parent_decision_id = parent_decision_id
self._logger = logger.bind(
hook="strategize_decision",
plan_id=plan_id,
)
def record_strategy_choice(
self,
question: str,
chosen_option: str,
alternatives_considered: list[str] | None = None,
confidence_score: float | None = None,
rationale: str = "",
context_data: dict[str, Any] | None = None,
actor_state: dict[str, Any] | None = None,
relevant_resources: list[str] | None = None,
) -> Decision:
"""Record a strategy choice decision during Strategize.
Args:
question: What strategic question was being answered.
chosen_option: The chosen approach.
alternatives_considered: Other approaches evaluated.
confidence_score: Confidence in the choice (0.0-1.0).
rationale: Why this option was chosen.
context_data: Current context window contents.
actor_state: Actor's current state.
relevant_resources: Resource IDs that influenced the decision.
Returns:
The recorded Decision.
Raises:
ValidationError: If required fields are missing.
"""
if not question or not question.strip():
raise ValidationError("question must not be empty")
if not chosen_option or not chosen_option.strip():
raise ValidationError("chosen_option must not be empty")
snapshot = capture_context_snapshot(
context_data=context_data,
actor_state=actor_state,
relevant_resources=relevant_resources,
)
self._logger.info(
"Recording strategy choice decision",
question=question,
chosen_option=chosen_option,
confidence=confidence_score,
)
try:
decision = self.decision_service.record_decision(
plan_id=self.plan_id,
decision_type=DecisionType.STRATEGY_CHOICE,
question=question,
chosen_option=chosen_option,
parent_decision_id=self.parent_decision_id,
alternatives_considered=alternatives_considered,
confidence_score=confidence_score,
rationale=rationale,
context_snapshot=snapshot,
plan_phase=PlanPhase.STRATEGIZE,
)
self._logger.debug(
"Strategy choice decision recorded",
decision_id=decision.decision_id,
)
return decision
except Exception as exc:
self._logger.warning(
"Failed to record strategy choice decision",
error=str(exc),
error_type=type(exc).__name__,
)
raise
def record_resource_selection(
self,
question: str,
chosen_option: str,
alternatives_considered: list[str] | None = None,
confidence_score: float | None = None,
rationale: str = "",
context_data: dict[str, Any] | None = None,
actor_state: dict[str, Any] | None = None,
relevant_resources: list[str] | None = None,
) -> Decision:
"""Record a resource selection decision during Strategize.
Args:
question: What resources should be selected.
chosen_option: The selected resources.
alternatives_considered: Other resource selections evaluated.
confidence_score: Confidence in the selection (0.0-1.0).
rationale: Why these resources were selected.
context_data: Current context window contents.
actor_state: Actor's current state.
relevant_resources: Resource IDs that influenced the decision.
Returns:
The recorded Decision.
Raises:
ValidationError: If required fields are missing.
"""
if not question or not question.strip():
raise ValidationError("question must not be empty")
if not chosen_option or not chosen_option.strip():
raise ValidationError("chosen_option must not be empty")
snapshot = capture_context_snapshot(
context_data=context_data,
actor_state=actor_state,
relevant_resources=relevant_resources,
)
self._logger.info(
"Recording resource selection decision",
question=question,
chosen_option=chosen_option,
)
try:
decision = self.decision_service.record_decision(
plan_id=self.plan_id,
decision_type=DecisionType.RESOURCE_SELECTION,
question=question,
chosen_option=chosen_option,
parent_decision_id=self.parent_decision_id,
alternatives_considered=alternatives_considered,
confidence_score=confidence_score,
rationale=rationale,
context_snapshot=snapshot,
plan_phase=PlanPhase.STRATEGIZE,
)
self._logger.debug(
"Resource selection decision recorded",
decision_id=decision.decision_id,
)
return decision
except Exception as exc:
self._logger.warning(
"Failed to record resource selection decision",
error=str(exc),
error_type=type(exc).__name__,
)
raise
def record_subplan_spawn(
self,
question: str,
chosen_option: str,
alternatives_considered: list[str] | None = None,
confidence_score: float | None = None,
rationale: str = "",
context_data: dict[str, Any] | None = None,
actor_state: dict[str, Any] | None = None,
relevant_resources: list[str] | None = None,
) -> Decision:
"""Record a subplan spawn decision during Strategize.
Args:
question: Why is a subplan being spawned.
chosen_option: The subplan goal/description.
alternatives_considered: Other decomposition approaches.
confidence_score: Confidence in the decomposition (0.0-1.0).
rationale: Why this decomposition was chosen.
context_data: Current context window contents.
actor_state: Actor's current state.
relevant_resources: Resource IDs that influenced the decision.
Returns:
The recorded Decision.
Raises:
ValidationError: If required fields are missing.
"""
if not question or not question.strip():
raise ValidationError("question must not be empty")
if not chosen_option or not chosen_option.strip():
raise ValidationError("chosen_option must not be empty")
snapshot = capture_context_snapshot(
context_data=context_data,
actor_state=actor_state,
relevant_resources=relevant_resources,
)
self._logger.info(
"Recording subplan spawn decision",
question=question,
chosen_option=chosen_option,
)
try:
decision = self.decision_service.record_decision(
plan_id=self.plan_id,
decision_type=DecisionType.SUBPLAN_SPAWN,
question=question,
chosen_option=chosen_option,
parent_decision_id=self.parent_decision_id,
alternatives_considered=alternatives_considered,
confidence_score=confidence_score,
rationale=rationale,
context_snapshot=snapshot,
plan_phase=PlanPhase.STRATEGIZE,
)
self._logger.debug(
"Subplan spawn decision recorded",
decision_id=decision.decision_id,
)
return decision
except Exception as exc:
self._logger.warning(
"Failed to record subplan spawn decision",
error=str(exc),
error_type=type(exc).__name__,
)
raise
def record_invariant_enforced(
self,
question: str,
chosen_option: str,
alternatives_considered: list[str] | None = None,
confidence_score: float | None = None,
rationale: str = "",
context_data: dict[str, Any] | None = None,
actor_state: dict[str, Any] | None = None,
relevant_resources: list[str] | None = None,
) -> Decision:
"""Record an invariant enforcement decision during Strategize.
Args:
question: What invariant is being enforced.
chosen_option: How the invariant is being enforced.
alternatives_considered: Other enforcement approaches evaluated.
confidence_score: Confidence in the enforcement approach (0.0-1.0).
rationale: Why this enforcement approach was chosen.
context_data: Current context window contents.
actor_state: Actor's current state.
relevant_resources: Resource IDs that influenced the decision.
Returns:
The recorded Decision.
Raises:
ValidationError: If required fields are missing.
"""
if not question or not question.strip():
raise ValidationError("question must not be empty")
if not chosen_option or not chosen_option.strip():
raise ValidationError("chosen_option must not be empty")
snapshot = capture_context_snapshot(
context_data=context_data,
actor_state=actor_state,
relevant_resources=relevant_resources,
)
self._logger.info(
"Recording invariant enforced decision",
question=question,
chosen_option=chosen_option,
)
try:
decision = self.decision_service.record_decision(
plan_id=self.plan_id,
decision_type=DecisionType.INVARIANT_ENFORCED,
question=question,
chosen_option=chosen_option,
parent_decision_id=self.parent_decision_id,
alternatives_considered=alternatives_considered,
confidence_score=confidence_score,
rationale=rationale,
context_snapshot=snapshot,
plan_phase=PlanPhase.STRATEGIZE,
)
self._logger.debug(
"Invariant enforced decision recorded",
decision_id=decision.decision_id,
)
return decision
except Exception as exc:
self._logger.warning(
"Failed to record invariant enforced decision",
error=str(exc),
error_type=type(exc).__name__,
)
raise
@@ -241,10 +241,9 @@ class PluginLoader:
def validate_protocol(klass: type[Any], protocol: type[Any]) -> bool:
"""Check whether *klass* satisfies a ``@runtime_checkable`` Protocol.
Creates a temporary instance of *klass* (using a no-arg
constructor) and checks it against the protocol via
``isinstance``. If instantiation fails, falls back to a
structural check using ``issubclass``.
Uses structural type checking via ``issubclass`` to validate the
protocol without instantiating the class. This prevents arbitrary
code execution from untrusted plugin constructors during validation.
Args:
klass: The class to validate.
@@ -256,23 +255,84 @@ class PluginLoader:
Raises:
ProtocolMismatchError: If *klass* does not satisfy the protocol.
"""
# Try instance check first (most reliable for runtime_checkable)
# Try structural check first (safe, no instantiation).
# This prevents arbitrary code execution from plugin constructors.
issubclass_raised_type_error = False
try:
instance = klass()
if isinstance(instance, protocol):
if issubclass(klass, protocol):
return True
except Exception:
# If instantiation fails, try subclass check
try:
if issubclass(klass, protocol):
return True
except TypeError:
pass
except TypeError:
# issubclass raises TypeError if protocol is not a valid
# @runtime_checkable Protocol (e.g. has a custom metaclass that
# overrides __subclasscheck__). Fall through to structural check.
issubclass_raised_type_error = True
# Fallback: perform a conservative structural check against the
# Protocol definition without instantiating the class. We inspect
# the protocol's declared members (callables and annotated names)
# and ensure the candidate class exposes them as class-level
# attributes or descriptors. This approximates structural
# conformance while avoiding constructor execution.
required: set[str] = set()
# Collect names from protocol __dict__ (methods, properties, etc.)
prot_dict = getattr(protocol, "__dict__", {})
for name, _value in prot_dict.items():
if name.startswith("__"):
continue
# Methods and descriptors will appear in the dict; annotations
# are handled below. We treat any non-data-magic name as a
# required member.
required.add(name)
# Also include annotated names (those declared with type hints)
ann = getattr(protocol, "__annotations__", {}) or {}
for name in ann:
if name.startswith("__"):
continue
required.add(name)
# If issubclass raised TypeError and the protocol declares no
# inspectable members, we cannot validate conformance — treat this
# as a mismatch rather than silently returning True for an
# unverifiable protocol.
if issubclass_raised_type_error and not required:
msg = (
f"Class '{getattr(klass, '__name__', str(klass))}' cannot be "
f"validated against protocol "
f"'{getattr(protocol, '__name__', str(protocol))}': "
f"issubclass raised TypeError and the protocol declares no "
f"inspectable members. Ensure the protocol is a valid "
f"@runtime_checkable Protocol."
)
raise ProtocolMismatchError(msg)
# Validate that the candidate class exposes each required name.
missing: list[str] = []
for name in sorted(required):
# getattr on the class returns descriptors (functions, property,
# staticmethod, etc.) without instantiation. hasattr is safe.
if not hasattr(klass, name):
missing.append(name)
continue
# If the protocol declared a callable (method), ensure the
# attribute on the class is callable or a descriptor.
prot_val = prot_dict.get(name)
if callable(prot_val):
cand = getattr(klass, name)
# Properties are descriptors and typically not callable; we
# accept them as present. For methods, require callable.
if not (callable(cand) or hasattr(cand, "fget")):
missing.append(name)
if not missing:
return True
msg = (
f"Class '{klass.__name__}' does not satisfy protocol "
f"'{protocol.__name__}'. Ensure the class implements all "
f"required methods and attributes."
f"Class '{getattr(klass, '__name__', str(klass))}' does not "
f"satisfy protocol '{getattr(protocol, '__name__', str(protocol))}'. "
f"Missing attributes: {', '.join(missing)}. Ensure the class "
f"implements all required methods and descriptors."
)
raise ProtocolMismatchError(msg)
+1 -2
View File
@@ -17,13 +17,12 @@ import yaml
from cleveragents.actor.registry import ActorRegistry
from cleveragents.actor.schema import ActorConfigSchema, ActorType, is_v3_yaml
from cleveragents.config.settings import ProviderDefaults, Settings
from cleveragents.config.settings import ProviderDefaults
from cleveragents.core.exceptions import NotFoundError
from cleveragents.domain.models.core.actor import Actor
from cleveragents.providers.registry import (
ProviderCapabilities,
ProviderInfo,
ProviderRegistry,
ProviderType,
)