Add CrossPlanCorrectionService that implements the four child-plan-state-
dependent behaviours from the specification when a correction's affected
subtree includes child plans:
- Not yet started → cancel the child plan
- In progress → cancel + rollback sandbox to pre-child-plan state
- Completed but not applied → cancel + rollback sandbox
- Already applied → reject the correction (CorrectionRejection)
Key additions:
- ChildPlanState enum classifying child plans into 4 states
- CorrectionRejection result type with reason and affected applied plan IDs
- CascadeAction/CascadeResult models for cascade operation tracking
- CorrectionStatus.REJECTED for rejected corrections
- Atomic cascade-or-rollback: all child plan actions succeed or the
entire cascade is rolled back
- Protocol-based dependency injection (ChildPlanLookup, ChildPlanCanceller,
SandboxRollbacker) for testability
- execute_correction_with_cascade() integrates with CorrectionService flow
Testing:
- 24 Behave BDD scenarios in cross_plan_correction.feature
- 8 Robot Framework end-to-end smoke tests
- ASV benchmarks for cascade performance with varying child plan counts
ISSUES CLOSED: #547
Add InvariantReconciliationActor that runs at the start of the Strategize
phase to reconcile invariants from four scopes (global, project, action,
plan). The actor detects conflicts, resolves them using specificity-based
precedence (plan > action > project > global), honours non_overridable
global invariants, records invariant_enforced decisions, and produces a
reconciled InvariantSet.
Changes:
- New: src/cleveragents/actor/reconciliation.py
- InvariantReconciliationActor class with collect_invariants() and run()
- reconcile_invariants() pure function
- ScopeInvariants, ConflictRecord, ReconciliationResult dataclasses
- Modified: src/cleveragents/domain/models/core/invariant.py
- Added non_overridable: bool field to Invariant model
- New: features/invariant_reconciliation_actor.feature (26 BDD scenarios)
- New: features/steps/invariant_reconciliation_actor_steps.py
- New: robot/invariant_reconciliation_actor.robot
- New: robot/helper_invariant_reconciliation.py
- New: benchmarks/invariant_reconciliation_bench.py
Closes#549
Add TDD-style failing tests that verify the built-in git-checkout resource
type is available after initialization. Tests assert the correct expected
behavior: after agents init, the git-checkout type should exist in the
registry and 'agents resource add git-checkout' should succeed.
Tests are expected to fail until bug #524 is fixed, because
bootstrap_builtin_types() is never called during initialization. The fix
branch should be based on this branch so the fix commit inherits these tests.
Files added:
- features/resource_type_bootstrap_git.feature (2 Behave scenarios)
- features/steps/resource_type_bootstrap_git_steps.py (step definitions)
- robot/resource_type_bootstrap_git.robot (Robot Framework smoke test)
ISSUES CLOSED: #553
Implement the runtime execution engine for validation tool wrapping,
as specified in docs/specification.md § Tool Wrapping.
WrappedToolExecutor resolves wraps references and delegates execution
to wrapped tools, supporting composable wrapping chains with cycle
detection and depth limiting (max 10 levels).
ArgumentMapper translates arguments between wrapper and wrapped tool
schemas using the argument_mapping configuration. Supports both
forwarded parameter names and literal fixed values.
TransformExecutor runs user-supplied transform functions in a
sandboxed Python environment with restricted builtins (no imports,
no filesystem, no network access). Validates that transforms return
proper validation-format dicts with a passed boolean.
Wired into the tool package public API via tool/__init__.py exports.
All new error types (WrappedToolNotFoundError, WrappingCycleError,
WrappingDepthExceededError, TransformExecutionError) provide clear
diagnostic messages.
Tests: 20 Behave scenarios covering argument mapping, transform
execution, simple/chained delegation, error handling, and sandbox
restrictions. 8 Robot Framework integration smoke tests. ASV
benchmarks for delegation overhead measurement.
ISSUES CLOSED: #543
Implement sandbox_boundary(r) function that walks up containment edges
in the resource DAG to the nearest sandboxable ancestor, enabling
resources sharing a boundary to share one sandbox instance.
Changes:
- Add boundary.py: is_sandbox_boundary(), sandbox_boundary(),
compute_sandbox_domains(), BoundaryCache (thread-safe, per-execution)
- Update SandboxManager: resolve_sandbox_key() and
get_or_create_sandbox_for_resource() key by (plan_id, boundary_id)
instead of (plan_id, resource_id); boundary cache lifecycle methods
- Define "sandboxable" via ResourceCapabilities.sandboxable + non-none
sandbox_strategy as per specification section 24659-24674
- Export new symbols from sandbox __init__.py
- Add vulture whitelist entries for new public API
Tests:
- 26 Behave BDD scenarios (features/sandbox_boundary_algebra.feature)
- 5 Robot Framework integration tests (robot/sandbox_boundary_algebra.robot)
- ASV benchmarks for boundary walk, domain grouping, and cache performance
ISSUES CLOSED: #548
Extended _compute_affected_subtree() to BFS over both the structural tree
(parent-child plan relationships) and decision_dependencies edges (influence
DAG). The algorithm performs a single O(V+E) BFS pass that unions neighbors
from both edge sources, using a visited set for cycle detection to guard
against data corruption.
Decision creation now supports dependency_decision_ids parameter in
record_decision() which populates the in-memory influence DAG store.
get_influence_edges() returns the adjacency list format consumed by
CorrectionService.
All public CorrectionService methods (analyze_impact, execute_revert,
execute_correction, generate_dry_run_report) accept an optional
influence_edges parameter while remaining backward-compatible (defaults
to None, preserving structural-only traversal when not provided).
Key design decisions:
- Single BFS pass over union of structural + influence edges rather than
separate traversals, ensuring O(V+E) complexity and consistent visit order
- Cycle detection via visited set with warning log (not an error) since
cycles indicate data corruption, not a programming error
- Influence edge logging: traversal emits count of influence edges processed
for observability
- Backward-compatible API: existing callers that only pass decision_tree
continue to work identically
ISSUES CLOSED: #542
Wire all four project context CLI commands (inspect, simulate, set, show)
to live ACMS pipeline services via ContextTierService and CRP models.
- context inspect: queries ContextTierService for tier metrics and
per-project fragments with filtering by strategy/focus/breadth/depth
- context simulate: dry-run context assembly using CRP models with
configurable token budget and assembly strategies
- context set: 12 new ACMS pipeline options (hot_max_tokens,
warm_max_decisions, cold_max_decisions, summary_max_tokens,
temporal_scope, auto_refresh, focus_area, breadth, depth,
assembly_strategy, retrieval_strategy, summary_strategy)
- context show: displays ACMS pipeline configuration alongside policy
- `context inspect` displayed global tier fragment counts (hot/warm/cold)
across all projects instead of counts for the target project only.
Add `ContextTierService.get_scoped_metrics(project_names)` which uses
`ScopedBackendView` to filter fragment counts to the specified projects
while keeping hit/miss counters as global service-level cache metrics.
Update `context_inspect()` to call `get_scoped_metrics([project])`
instead of `get_metrics()`.
- `context simulate --focus` accepted focus URIs and passed them to the
`ContextRequest` model but never used them to filter the fragment list,
making the `--focus` flag a no-op.
Add focus URI filtering in `_simulate_context_assembly()` after
`get_scoped_view()` — filters `project_fragments` by matching each
fragment's `resource_id` against the supplied focus URIs.
Also fixes redaction false positives for hot_max_tokens and
summary_max_tokens keys, and Rich Console line-wrapping in test
output that caused JSON parse failures.
Includes 28 new Behave BDD scenarios for wiring coverage, updated
Robot Framework integration tests, and reference documentation.
ISSUES CLOSED: #499
Implement safety profile resolution and enforcement in the tool
execution pipeline, replacing the NotImplementedError stub with
working precedence logic and runtime safety checks.
Core changes:
- resolve_safety_profile() now resolves plan > action > project >
global precedence, returning the highest-priority non-None profile
(or DEFAULT_SAFETY_PROFILE with GLOBAL provenance when all None)
- ToolExecutionContext gains an optional safety_profile field
- ToolRuntime._enforce_capabilities() extended with three new checks:
* Unsafe tool gating: blocks tools with unsafe=True when profile
has allow_unsafe_tools=False (ToolSafetyViolationError)
* Skill category allow-list: blocks tools whose skill category
is not in allowed_skill_categories (ToolSafetyViolationError)
* Checkpoint requirement: OR-combines ctx.require_checkpoints
with safety_profile.require_checkpoints
- New ToolSafetyViolationError in tool error hierarchy
Test coverage:
- 30 updated BDD scenarios in safety_profile.feature (resolve
precedence replaces NotImplementedError stub test)
- 24 new BDD scenarios in safety_profile_enforcement.feature
- 9 Robot Framework integration smoke tests
- 4 ASV benchmark suites (construction, serialization, resolution,
provenance enum)
All nox sessions pass (typecheck 0 errors, unit_tests 7735 scenarios
0 failures, coverage 97%, integration_tests 9/9 passed, benchmarks
complete).
ISSUES CLOSED: #345
Add LLMTrace Pydantic v2 domain model with all required fields (trace_id,
plan_id, decision_id, actor, provider, model, prompt_tokens, completion_tokens,
cost_usd, latency_ms, tool_calls, context_hash, streaming, retry_count, error).
Define 14 OperationalMetricKey values (PLAN_DURATION_MS, PLAN_TOTAL_COST_USD,
PLAN_DECISION_COUNT, ACTOR_INVOCATION_COUNT, ACTOR_LATENCY_MS,
TOOL_INVOCATION_COUNT, TOOL_ERROR_RATE, CONTEXT_BUILD_TIME_MS,
CONTEXT_TOKEN_COUNT, LLM_CALL_COUNT, LLM_TOTAL_TOKENS, LLM_TOTAL_COST_USD,
LLM_AVG_LATENCY_MS, SUBPLAN_COUNT) with MetricEntry model and MetricCollector.
Add llm_traces database table (LLMTraceModel) with LLMTraceRepository for
persistence. TraceService provides recording, querying, metric computation,
plan lifecycle hooks, and optional LangSmith forwarding when
LANGCHAIN_TRACING_V2=true.
Wired into DI container as trace_service. Includes 28 Behave BDD scenarios,
6 Robot Framework smoke tests, 3 ASV benchmark suites, and reference
documentation.
Fix pre-existing cli_core server_mode test flake by mocking
resolve_server_mode in test steps to avoid stale config file interference.
Closes#500
Add hierarchical decomposition with 4+ levels and bounded context per
subplan. Implement decomposition heuristics (max_files_per_subplan,
max_tokens_per_subplan, language/dir clustering). Add dependency closure
computation for large graphs and DAG execution ordering. Add bounded
dependency closure with cutoff thresholds and memoization for 10K+
files. Record decomposition decisions in DecisionService
(strategy_choice + subplan_spawn entries).
New modules:
- decomposition_models.py: DecompositionConfig, DecompositionNode,
DecompositionResult, DependencyEdge, DependencyGraph
- decomposition_clustering.py: ClusteringStrategy with directory,
language, and size clustering plus deterministic sort
- decomposition_graph.py: DependencyClosureComputer with bounded
closure, topological sort, cycle detection, and memoization
- decomposition_service.py: DecompositionService orchestrating
hierarchy building and decision recording
Settings: planner_max_depth, planner_max_files_per_subplan,
planner_max_tokens_per_subplan, planner_min_files_per_subplan
Closes#205
Add domain models, application service, CLI integration, and full test
coverage for multi-project subplan orchestration.
New components:
- MultiProjectMetadata, ProjectScope, ProjectDependency domain models
- MultiProjectService for creating/managing multi-project plans
- CLI display of multi-project metadata in plan commands
- Behave BDD tests (20 scenarios), Robot Framework integration tests,
ASV benchmarks, and reference documentation
Also fixes pre-existing test flakiness in cli_core, core_cli_commands,
cli_plan_context_commands, and helper_server_stubs caused by environment
leakage and path-with-spaces issues.
ISSUES CLOSED: #199
Add ExecutionEnvironment enum (host/container) to domain models, implement
execution environment resolution with priority chain (tool > plan > project
> default), wire the tool runner to check execution_environment before
execution, and add CLI flags to plan use/execute and project context set.
When container is selected but no container resource is available, a clear
ContainerUnavailableError is raised with an actionable message.
Closes#512
- Update event_bus_steps.py to call record_decision() with individual
parameters (plan_id, decision_type, question, chosen_option, rationale)
instead of passing a Decision object, matching the master branch API
- Remove ctx.test_decision construction from DecisionService setup steps
as it is no longer needed with the new signature
- Update robot/helper_event_bus.py decision_service_emits_event() to use
the new record_decision() parameter signature
- All 9 Robot Framework event bus tests passing
- Behave scenarios at lines 125 and 131 now passing
Fixes event bus test failures after master merge.
- Fix CHANGELOG EventType count from 40 to 38 and add missing domains
(invariant, context) for accurate documentation
- Document correlation_id field as spec extension for request traceability
in DomainEvent model
- Add thread safety documentation to ReactiveEventBus and LoggingEventBus
noting single-threaded design and external sync requirements
- Document _persist_audit deferral in ReactiveEventBus.emit() explaining
audit logging via handler subscription or LoggingEventBus following
single-responsibility principle
- Replace bare MagicMock() with create_autospec(Settings, instance=True)
at 5 locations for type-safe test mocking
- Replace nested bare MagicMock for UnitOfWork with create_autospec at 3
locations to prevent silent breakage on API changes
All changes maintain backward compatibility. No linter errors.
- Fix rationale test to assert goal text appears in rationale rather than
only checking non-empty (P1-1)
- Align side_effects value to specification: use ["spawn_subplan"] instead
of ["emit_decision"] per docs/specification.md §18259 (P2-1)
- Remove dead TYPE_CHECKING import guard that contained only pass (P2-2)
- Replace frozenset with tuple for _VALID_CONTEXT_VIEWS to ensure
deterministic JSON schema enum ordering and eliminate CI noise (P2-3)
- Simplify validation error message and schema unpacking now that
context_view values are in a pre-sorted tuple
Behave steps, benchmarks, vulture whitelist, and docs referenced
renamed methods (get_decisions_for_plan, get_decision_tree). Updated
to use the actual API names (list_decisions, get_tree) and the kwargs
record_decision signature.
ISSUES CLOSED: #172
- Remove global _PLAN_ID; generate per-step plan IDs on context (#8)
- Fix sham orphan test; build children_map from all decisions (#1)
- Delete dead constants; use _PATCH_RESUME_SVC_MOD in resume steps (#2)
- Remove dead _resolve_active_plan_id mock from _invoke_correct (#5)
- Make --mode/--guidance required Typer options (#3)
- Show alternatives by default; remove --show-alternatives flag (#4)
- Strengthen weak assertions on depth-limit and show-superseded (#6)
- Add negative assertions for error type conflation (#7)
ISSUES CLOSED: #174
Cover CLI-level code paths for plan explain, tree, correct, resume,
revert, and read-only guards that were unreached by existing unit tests.
Raises plan.py diff-coverage from 69% to 99.7% (1 line remaining).
- Add justification to type: ignore comments in build_decision_tree
- Remove Any from step file signatures, use object instead
- Strengthen non-existent decision test to verify ID exclusion
- Fix O(n²×d) depth computation in table view with dict lookup
- Fix orphan root detection in rich-view to match BFS logic
- Add type annotations to Robot helper dispatch dict
- Deduplicate import json in explain_decision_cmd
ISSUES CLOSED: #174
Add `plan explain` and `plan tree` CLI commands that format decision
trees in json/yaml/table/rich formats. Flags control views for
superseded decisions, context snapshots, and reasoning details.
- plan explain <decision_id>: renders a single decision with optional
--show-context, --show-reasoning, --show-alternatives flags
- plan tree <plan_id>: renders full decision tree with optional
--show-superseded and --depth flags
- BFS tree building uses collections.deque (no list.pop(0))
- Behave BDD scenarios (14 scenarios, 54 steps)
- Robot Framework smoke tests with helper script
- ASV benchmarks for explain formatting and tree operations
- Updated docs/reference/plan_cli.md and CHANGELOG.md
ISSUES CLOSED: #174
Wire all AcpLocalFacade operation handlers to their corresponding
application services via constructor-injected service dependencies:
- session.create/close delegate to SessionService
- plan.create/execute/status/diff/apply delegate to PlanLifecycleService
- registry.list_tools delegates to ToolRegistry
- registry.list_resources delegates to ResourceRegistryService
- event.subscribe delegates to AcpEventQueue
- context.get returns stub pending ACMS ContextAssemblyPipeline
Add domain-to-ACP error code mapping via map_domain_error() translating
ResourceNotFoundError to NOT_FOUND, ValidationError to VALIDATION_ERROR,
PlanError to PLAN_ERROR, BusinessRuleViolation to INVALID_STATE, and
other domain exceptions to their corresponding ACP error codes.
Handlers gracefully fall back to stub responses when services are absent.
Includes 21 Behave scenarios (features/acp_facade_wiring.feature) and
9 Robot Framework integration tests (robot/acp_facade_wiring.robot).
Updated docs/reference/acp.md with wired operation details, service
key table, and error code taxonomy.
ISSUES CLOSED: #501
Implemented SkeletonCompressorService for ACMS context inheritance, producing
compressed context representations for propagation from parent plans to child
plans. Key design decisions and implementation details:
- SkeletonMetadata (frozen Pydantic model): records ratio, original_tokens,
compressed_tokens, and source_decision_ids for full auditability of each
compression pass. Persisted on Plan.skeleton_metadata.
- SkeletonCompressorService: stateless service accepting a list of
ContextFragment objects and a skeleton_ratio in [0.0, 1.0]. Fragments are
sorted by relevance descending with a stable secondary sort on fragment_id
to guarantee deterministic output. Token budget is original_tokens*(1-ratio);
fragments are greedily selected until budget is exhausted.
- Ratio semantics: 0.0 = no compression (pass-through), 1.0 = maximum
compression (single top fragment only), None = default 0.3.
- Integration: Plan model gains optional skeleton_metadata field exposed in
as_cli_dict() under the 'skeleton' key. Service registered in DI container
as skeleton_compressor_service (Singleton, stateless).
- Tests: 22 BDD scenarios (features/skeleton_compressor.feature) covering
ratio validation, stable ordering, metadata correctness, edge cases, and
plan model integration. 6 Robot Framework smoke tests. ASV benchmark suites
at 10/100/1000 fragment scales.
- Documentation: docs/reference/skeleton_compressor.md with ratio table,
algorithm description, metadata schema, and multi-decision plan example.
ISSUES CLOSED: #194
Implemented the Backend Abstraction Layer (BAL) for the Advanced Context
Management System, following the specification in docs/specification.md
Section ACMS > Backend Abstraction Layer and ADR-014.
Key additions:
- TextBackend protocol with search(query, scope, max_results) returning
list[TextResult], and TextResult frozen dataclass (uko_uri, content,
score, metadata fields)
- VectorBackend protocol with similarity_search(embedding, scope, top_k)
returning list[VectorResult], and VectorResult frozen dataclass
- GraphBackend protocol with sparql_query(query, scope),
get_triples(subject), and traverse(start, depth) methods returning
GraphResult frozen dataclass (triples, metadata fields)
- In-memory stub backends (InMemoryTextBackend, InMemoryVectorBackend,
InMemoryGraphBackend) that validate arguments and return empty results,
serving as development placeholders and test doubles
- DI container registration as configurable Singletons with provider
selection via override_providers()
- Behave BDD feature (35 scenarios / 83 steps) covering protocol
compliance, argument validation, result immutability, and DI resolution
- Robot Framework smoke tests (6 tests) for integration verification
- ASV benchmarks for stub query overhead and instantiation time
- Reference documentation at docs/reference/acms_backends.md
Design decisions:
- Used @runtime_checkable Protocol for structural subtyping, consistent
with existing ResourceHandler pattern
- Used frozen dataclasses (not Pydantic) for result types to minimize
overhead in the hot path of context assembly
- scope parameter typed as frozenset[str] for immutability and hashability
- Stubs registered as default Singletons; production backends swap via DI
ISSUES CLOSED: #498
Added three new built-in resource types: container-instance,
devcontainer-instance, and devcontainer-file. The devcontainer-instance
type inherits from container-instance per ADR-042 and is auto-discovered
when git-checkout or fs-directory resources contain .devcontainer/
directories per ADR-043.
Implementation includes:
- DevcontainerHandler extending BaseResourceHandler with snapshot strategy
- Auto-discovery module scanning .devcontainer/devcontainer.json and
root .devcontainer.json with JSON validation
- CLI support for devcontainer-instance and container-instance via
agents resource add with --path and --image flags
- Behave feature with 22 scenarios covering manual registration,
auto-discovery, invalid JSON handling, and protocol conformance
- Robot integration tests with 10 test cases for CLI round-trip and
DAG hierarchy validation
- ASV benchmarks measuring discovery throughput with varying subdirectory
counts, handler resolver cache performance, and result construction
- Reference documentation at docs/reference/devcontainer_resources.md
ISSUES CLOSED: #511
Add SafetyProfile domain model with configurable safety constraints
(checkpoint, human approval, cost limits, retry limits, skill
categories, sandbox requirement). Integrate into Action model with
from_config/as_cli_dict support, and persist via LifecycleActionModel
safety_profile_json column.
Include resolve_safety_profile() stub that raises NotImplementedError
for local mode, signalling that real enforcement is deferred.
Add comprehensive test coverage:
- 20 BDD scenarios in features/safety_profile.feature
- 6 Robot Framework smoke tests
- 5 ASV benchmark suites (11 timing functions)
Add docs/reference/safety_profile.md reference documentation.
ISSUES CLOSED: #332
Add --project flag to config set, config get, and config list CLI
commands, enabling per-project configuration overrides stored under
[project."<name>"] TOML tables in the global config file.
Project-scoped resolution slots between environment variable and global
levels in the ConfigService resolution chain. config list --project
shows only overrides for the named project with source annotations.
Implementation:
- ConfigService: add set_project_value() and get_project_overrides()
methods for TOML-backed project-scoped persistence and retrieval
- CLI config commands: wire --project flag through set, get, and list
subcommands; project-scoped list filters to overrides only
- Database persistence: project-scoped config stored as alternative
backend for projects not using TOML
- Documentation: update docs/reference/config_resolution.md with
project-scopable key lists, CLI examples, precedence diagram, and
non-scopable key rejection behavior
Tests:
- Behave: 12 BDD scenarios in features/config_project_scope.feature
covering set/get/list, precedence over global defaults, and
non-scopable key rejection
- Robot: 5 integration smoke tests in robot/config_project_scope.robot
for end-to-end project-scoped round-trip verification
- ASV: benchmarks/config_project_scope_bench.py measuring resolution
overhead with project scope active
All nox quality gates pass: lint, typecheck, unit_tests (7522 scenarios),
integration_tests (Config Project Scope suite passed), and coverage at
98% line rate (threshold 97%).
Closes#259
Add protocol stubs for remote server communication infrastructure:
- ServerClient: Health check and version negotiation protocol
- RemoteExecutionClient: Remote plan execution and status protocol
- AuthClient: Authentication and token management protocol
- StubServerClient/StubRemoteExecutionClient/StubAuthClient: Stub
implementations raising NotImplementedError for all methods
- ServerConnectionConfig: Validated config model (server_url, namespace,
auth_token_ref, tls_verify)
- Config keys: core.server_url, core.server_namespace, core.server_tls_verify
- CLI: agents connect <url> stub command with explicit warning
- CLI: agents info shows Server Mode (disabled/stubbed)
ISSUES CLOSED: #201
Add SubplanService for building child plans from DecisionService spawn
entries and SubplanConfig. The service validates resource scopes, merge
strategies, and max_parallel bounds before spawning.
Key additions:
- SubplanService: Orchestrates child plan creation from spawn entries
- SpawnMetadata: Persisted metadata (spawn_decision_id, parent/root
plan IDs, execution mode) for status output
- Spawn validation: Checks resource scopes, merge strategy, and
parallelism bounds before spawning
- Documentation: subplan_service.md with spawn workflow and lifecycle
ISSUES CLOSED: #197
- Return parent_decision_id in handler result dict and add meaningful
assertion to the corresponding Behave scenario (B1)
- Add ULID format validators to SubplanPayload for plan_id, dependencies,
and parent_decision_id, consistent with Decision model validation (S1)
- Add non-empty string validator for resource_scopes items (S2)
- Narrow broad except Exception to except (ValidationError, ValueError)
so programming errors surface as real failures (S3)
- Document strategy_with_subplan.yaml in actors_examples.md and assert
it is referenced in the "Verify all examples are documented" scenario (B2)
ISSUES CLOSED: #198
Cap time.sleep and asyncio.sleep globally at 10ms in before_all to
eliminate retry/backoff waits (tenacity wait_fixed, retry_auto_debug
exponential backoff). Save originals as time._original_sleep and
asyncio._original_sleep for tests that need real wall-clock delays
(CircuitBreaker recovery, debounce timers, validation timeouts).
Enhance template-DB patch: add "db." prefix to _SCENARIO_DB_PREFIXES
and check db_path.stat().st_size > 0 so 0-byte auto-created SQLite
files receive the template copy instead of falling through to real
migrations.
Replace subprocess.run CLI invocations with typer.testing.CliRunner
in module_coverage, main_coverage_complete, and coverage_extras step
files, eliminating ~6s Python cold-start overhead per call.
Switch plan_persistence and action_persistence to in-memory SQLite by
default; only cross-restart scenarios use file-based via an explicit
Given step.
Replace MigrationRunner.run_migrations with Base.metadata.create_all
in plan_service_steps for freshly created in-memory engines.
Removed leftover debug comment in environment.py.
Total tier runtime: 565s -> 21s (96% reduction), 20 features all
under 5s behave-internal time.
ISSUES CLOSED: #480
Optimized the 8 features accounting for 64% of total BDD test runtime
(1,505s of 2,352s):
- features/environment.py: Added _ensure_template_db() for direct behave
invocations, expanded _SCENARIO_DB_PREFIXES to include "test_" for
step-file-created DBs, added @mock_only tag support to skip
unnecessary DB setup.
- features/plan_commands_coverage.feature: Added @mock_only tag (fully
mocked, no DB needed).
- features/plan_service.feature: 14 actor-resolution scenarios now use
lightweight in-memory plan service instead of heavyweight file-based
DB + project init.
- features/steps/plan_service_steps.py: New
step_create_lightweight_plan_service for actor-resolution tests.
- features/steps/services_coverage_steps.py: Extracted 3 helper functions
to consolidate 8 near-identical Given steps (~200 lines of duplicated
boilerplate removed).
Per-feature results: services_coverage 245s->2.8s (99%), context_service
215s->2.1s (99%), project_service 140s->0.7s (99%), plan_service
215s->4.6s (98%), core_cli_commands 113s->4.2s (96%), cli_streaming
213s->6.4s (97%), plan_commands_coverage 116s->20s (83%),
cli_plan_context_commands 248s->31.6s (87%).
ISSUES CLOSED: #479
Created scripts/create_template_db.py that builds a pre-migrated SQLite
template database using Base.metadata.create_all() + alembic stamp
(~5ms for 34 tables, vs ~0.5-3s x 25 Alembic migrations per scenario).
Nox unit_tests and coverage_report sessions generate the template before
test execution and propagate CLEVERAGENTS_TEMPLATE_DB env var to all
workers.
features/environment.py before_all() installs a monkey-patch on
MigrationRunner.init_or_upgrade that copies the template for fresh
scenario temp DBs, falling through to real migrations for :memory:,
existing files, and migration-runner unit tests.
Quick wins: sleep(0.5) -> sleep(0.05) in cli_streaming wait step;
removed redundant Background re-declaration in cli_streaming.feature
scenario 7.
ISSUES CLOSED: #483
freemo
brent.edwards
Luis Mendes
aditya
khyari hamza