test/cli-docstring-example-validation
1190 Commits
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eb4e6f59d9
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Merge branch 'master' into feature/m5-subplan-actor
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da21881c0c
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Merge branch 'master' into feature/m5-subplan-actor | ||
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6ca7712585
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Merge branch 'master' into feature/m5-subplan-actor | ||
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ef65996ca2
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fix(actor): address code review findings on plan_subplan tool
- 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 |
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4ad51561fc |
perf(tests): optimize medium-slow BDD features (10-100s tier)
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 |
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0bbec4b77e |
perf(tests): optimize the 8 slowest BDD feature files
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 |
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a8f7ed57cb |
perf(tests): reduce per-feature startup cost with shared fixtures and lazy imports
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 |
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9f6fb667c2
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feat(subplan): execute and merge subplans
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Implement SubplanExecutionService and SubplanMergeService to enable parent plans to decompose work into coordinated child subplans with configurable execution modes (sequential, parallel, dependency-ordered) and merge strategies (git_three_way, sequential_apply, fail_on_conflict, last_wins). - SubplanExecutionService: schedules subplan execution with retry support via SubplanFailureHandler, max_parallel limits, fail_fast semantics, and topological DAG ordering for dependency mode - SubplanMergeService: wraps sandbox merge infrastructure to combine subplan sandbox outputs using the configured merge strategy - BDD tests: 21 scenarios covering all execution modes, merge strategies, validation, and integration flows - Robot tests: 11 integration test cases with helper module - ASV benchmarks: performance benchmarks for execution and merge - Documentation: reference guide in docs/reference/subplans.md ISSUES CLOSED: #184 |
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7c4663b8ee |
feat(config): add config service with multi-level resolution
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Implement the complete configuration system with multi-level resolution chain, typed key registry, and CLI integration per specification. ConfigService changes: - Expand _build_catalog() to register all 102 spec-aligned config keys across 8 groups: core (14), server (4), actor (5), plan (8), sandbox (5), index (12), context (43), provider (11) - Each key carries exact dotted-dash name, Python type, default value, explicit env var name per spec, project-scopability flag, and description - Fix _env_name() to convert dots and dashes to underscores - Provider keys use standard env var names (e.g., OPENAI_API_KEY) CLI commands rewiring: - Rewrite config set/get/list to use ConfigService instead of Settings - Add --verbose flag to config get showing full 5-level resolution chain - Add --project flag to config set/get/list for project-scoped overrides - Support both glob and regex patterns in config list - Validate keys against ConfigService registry with actionable errors - Retain backward-compatible helper functions delegating to ConfigService Documentation: - Add docs/reference/config_resolution.md covering resolution chain, all 102 config keys, CLI commands, TOML format, and provider credentials Testing: - Update all 4 Behave feature files and step definitions to use new spec-aligned key names, env vars, and defaults (119 scenarios passing) - Add robot/config_resolution.robot with 10 integration test cases - Add benchmarks/config_resolution_bench.py with 8 time + 2 memory suites ISSUES CLOSED: #258 |
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2eb31a598c |
test(coverage): add Behave BDD tests for 8 under-covered modules
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Added targeted Behave BDD feature files and step definitions to improve unit test coverage for: - decision_service.py: Full coverage of all 7 service methods (18 scenarios) - plan_apply_service.py: Branch coverage for handle_merge_failure (2 scenarios) - plan_executor.py: Edge cases for rollback, checkpoint, and parse_steps (15 scenarios) - cli/commands/plan.py: Uncovered region lines 1950-2273 (23 scenarios) - repositories.py: Remaining missed branches and lines (14 scenarios) - sandbox/checkpoint.py: Full coverage of CheckpointManager (26 scenarios) - langgraph/bridge.py: Remaining uncovered lines and branches (10 scenarios) - cli/commands/config.py: Safety net to maintain 100% coverage (42 scenarios) Total: 150 new scenarios, 596 steps, all passing. Also fixed a step definition collision in plan_lifecycle_coverage by renaming "the delete result should be false" to "the plan delete result should be false". ISSUES CLOSED: #475 |
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53455275ba
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feat(automation): add autonomy guardrails and audit trail
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Add runtime autonomy constraints (max steps, tool budget, required confirmations) and a structured audit trail for plan execution. New domain models: - AutonomyGuardrails: enforces step limits, tool budgets, and confirmation gates with validators and check methods - GuardrailAuditEntry: records each enforcement event with timestamp, event type, guard name, result, reason, and context - GuardrailAuditTrail: ordered collection of audit entries persisted to plan metadata New service: - AutonomyGuardrailService: high-level service for configuring guardrails per plan, checking constraints, recording audit entries, and serializing/restoring state via plan metadata Tests: - Behave: 69 scenarios covering model validation, step/budget/ confirmation checks, audit trail recording, and service operations - Robot: 8 test cases for autonomy guardrail CLI flag smoke testing - ASV: 6 benchmark suites measuring enforcement overhead Documentation: - Updated docs/reference/automation_profiles.md with guardrail fields, enforcement behavior, audit trail schema, and event type reference ISSUES CLOSED: #204 |
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64af753aab
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feat(security): add permission system
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Implemented namespace/project/plan/skill permission model with role bindings (owner/admin/editor/viewer) and default deny policy. Added enforcement hooks at CLI/service boundaries that are server-only; local mode returns permissive defaults. Includes role enums, permission check service, role matrix documentation. Includes Behave BDD scenarios, Robot integration tests, ASV benchmarks, and reference documentation. ISSUES CLOSED: #344 |
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a2be3e67b0
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feat(validation): add semantic validation service
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Added SemanticValidationService with built-in Python checks for syntax errors, missing imports, broken references, dependency cycles, API misuse, and missing symbols. Implemented SemanticRuleRegistry for extensible validator registration. Integrated with ValidationPipeline as informational by default. Added per-project/per-plan config keys, severity mapping (info/warn/error), output schema normalization, and file-hash-based caching. Includes Behave BDD scenarios, Robot integration tests, ASV benchmarks, and reference documentation. ISSUES CLOSED: #207 |
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38e75342a9 |
refactor: merge from master
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This code is a merge from master. |
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465683fb6b |
fix(test): stabilize retry_with_timeout scenario
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Patch time.monotonic alongside time.sleep in the retry timeout step so stop_after_delay cannot elapse due to wall-clock overhead on busy CI runners. The fake monotonic clock advances by 1µs per call, keeping elapsed time well under the 0.01s timeout while preserving retry semantics. Closes #200 |
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e3a93bf32c |
Merge branch 'master' into feature/m5-acms-smoke
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158a99c543 |
Merge branch 'master' into feature/m6-autonomy-smoke
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de8c33cb4a |
fix(test): use source-module patch target for get_container
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Revert module-level import refactor and instead patch at cleveragents.application.container.get_container — matching the established pattern used by all existing context CLI tests. Lazy imports inside each function re-read from the source module, so patching there intercepts correctly. Closes #200 |
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0ca1303927 |
feat(sandbox): add checkpoint and rollback hooks
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Introduce a lightweight checkpoint/rollback system for sandbox state during plan execute and apply flows. CheckpointManager snapshots the sandbox working directory before each phase and can restore it on failure, giving the execution engine a reliable undo mechanism. Key changes: - SandboxCheckpoint model, Checkpointable protocol, and CheckpointManager in infrastructure/sandbox/checkpoint.py - PlanExecutor gains optional checkpoint_manager with pre/post execute hooks and automatic rollback on failure - PlanApplyService gains optional checkpoint_manager with pre-apply checkpoint and rollback helper - 12 BDD scenarios (features/sandbox_checkpoints.feature) - 5 Robot Framework smoke tests (robot/sandbox_checkpoint_smoke.robot) - ASV benchmarks for creation, rollback, and listing operations - Reference documentation in docs/reference/sandbox.md ISSUES CLOSED: #183 |
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c9782637d9 |
Merge branch 'master' into feature/m5-acms-smoke
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c129f4c3f0 |
fix(test): address PR #470 review feedback
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- Add CHANGELOG.md entry for M6 autonomy acceptance suite - Split m6_autonomy_acceptance_steps.py (774 lines) into m6_facade_steps.py (398 lines) and m6_guardrails_steps.py (399 lines) to comply with the project's 500-line guideline Closes #211 |
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75c628793b |
fix(test): correct M5 smoke patch targets and pattern matching
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Fix 4 errored scenarios: patch get_container instead of the lazily-
imported ContextService (which is not a module-level attribute of
cleveragents.cli.commands.context).
Fix project context show (line 112): mock _get_namespaced_project_repo
to return a repo (not a tuple), mock get_container for session_factory,
and mock _read_policy to bypass DB access.
Fix context exclusion pattern (line 152): replace fnmatch.fnmatch with
PurePosixPath.match for proper ** glob handling and use a path with a
leading directory segment.
Also fix context list empty assertion to match actual CLI output
('No files in context' rather than 'No context'), and patch
Path.exists for the add command so the mock service is reached.
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f90cf24617 |
Merge branch 'master' into feature/m6-autonomy-smoke
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348c230bc5 |
test(e2e): add M6 autonomy acceptance suite
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Add comprehensive M6 autonomy acceptance test suites covering the ACP local-mode facade, autonomy guardrails, automation profile resolution, event queue pub/sub, HTTP transport stub, and version negotiation. Behave suite (52 scenarios): - ACP facade dispatch for all 11 operations - Guard enforcement (denylist, allowlist, budget, call limit, write/apply) - Automation profile built-in validation and custom creation - Profile resolution precedence (plan > action > project > global) - Event queue lifecycle (publish, subscribe, unsubscribe, close) - HTTP transport stub rejection in local mode - ACP version negotiation (accept/reject) - Model validation (AcpRequest, AcpResponse, AcpEvent, AcpErrorDetail) Robot integration suite (11 tests): - Facade session/plan lifecycle, unknown operation error - Event queue publish/subscribe, transport stub, version negotiation - Guard denylist/budget enforcement, profile resolution - Fixture loading, full end-to-end flow ASV benchmarks (5 suites): - Facade dispatch, guard evaluation, profile resolution - Event queue operations, fixture loading Fixtures: acp_facade_flows.json, autonomy_guardrails.json, automation_profiles.json Closes #211 |
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ece5e61725 |
test(e2e): add M5 ACMS + context suites
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7235d46ade |
feat(skill): persist flattened tool sets
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Add Alembic migration m4_002_skill_flattened_tools to extend the skills table with five new columns: flattened_tools_json, includes_json, capability_summary_json, yaml_text, and flattening_hash (SHA-256). A defence-in-depth uniqueness constraint (uq_skills_name) is also added. Update SkillModel with the new column definitions and extend SkillRepository with update_flattened_tools(), get_flattened_tools(), needs_refresh(), recompute_flattening_hash(), and invalidate_cached_summaries() methods. The existing update() method now nulls all cached fields on mutation (hash-based invalidation). All new repository methods follow the session-factory pattern with @database_retry and flush-but-don-t-commit semantics. Structured logging via structlog records cache updates and invalidations. Database schema docs updated with the new skills table columns and a persistence-field-to-domain-model mapping table. Tests: - 6 Behave scenarios covering create, invalidation, hash staleness, refresh recomputation, uniqueness constraint, and namespace filtering - 2 Robot Framework smoke tests (round-trip and invalidation) - 3 ASV benchmarks (persist, refresh check, namespace list) ISSUES CLOSED: #166 |
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c9abb45adf
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test(coverage): add Behave BDD scenarios for 9 under-covered modules
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Added 246 new BDD scenarios across 9 feature files to improve unit test coverage for modules that were either entirely untested or had significant coverage gaps: - lock_service_coverage.feature (27 scenarios): validation branches, TTL boundaries, re-entrant acquisition, rollback on exceptions - plan_apply_service_coverage.feature (54 scenarios): operation labels, diff rendering (plain/rich/json), artifact building, validation gate, changeset resolution and cleanup - plan_executor_coverage.feature (51 scenarios): step parsing, execute actor integration, strategize/execute guards, stub retry/recovery, decision tree construction - skill_cli_coverage_r3.feature (22 scenarios): tools refresh, list/show JSON fallback, capability summary errors, remove confirmation - changeset_repository_coverage.feature (39 scenarios): entry/tool repos validation, database error wrapping, domain conversion, SQLite store CRUD operations - repositories_coverage.feature (20 scenarios): get_by_name/namespace errors, list_available filters, delete with ActionInUseError, plan update with invariants/processing_state/error_details - sandbox_copy_on_write_coverage.feature (12 scenarios): create OSError wrapping, get_path state transitions, commit edge cases, rollback errors, cleanup with missing paths - bridge_coverage.feature (8 scenarios): __del__ suppression, async task cancellation, execute_graph message type handling, stream config, state checkpointer - plan_cli_coverage.feature (13 scenarios): legacy apply/list/cd paths, use-action with estimation/invariant actors, lifecycle-apply guards, status errors, error recovery display All 246 scenarios (1105 steps) pass. Step definitions use unique prefixes to prevent ambiguous step conflicts with existing tests. ISSUES CLOSED: #467 |
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a074b4846f
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fix(provider): remove FakeListLLM defaults
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Remove FakeListLLM as a silent fallback in agent graph constructors (plan_generation.py, context_analysis.py, auto_debug.py). All three now raise ValueError when llm=None, making missing-provider errors explicit. Add Settings.mock_providers flag and validate_provider_availability() method. Update container.get_ai_provider() to check Settings.mock_providers first, with env-var fallback for backward compatibility. Add resolve_provider_by_name() helper to the provider registry and export it from cleveragents.providers. Add structlog trace logging to ProviderRegistry.get_default_provider_type() to record selection reasoning. Update all existing behave step files, robot tests, and benchmarks that relied on the implicit FakeListLLM default to pass an explicit LLM instance instead. Add new BDD tests (features/provider_fixes.feature with 17 scenarios), Robot Framework integration tests (robot/provider_detection_smoke.robot), and ASV benchmarks (benchmarks/provider_selection_bench.py). ISSUES CLOSED: #323 |
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9af9ff8d95
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Merge branch 'master' into feature/m4-skill-registry-refresh
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174d1dc334
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Merge branch 'master' into feature/m4-skill-registry-cli
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4c4bd74d94
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Merge branch 'master' into feature/m3-agent-skills-loader
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2b5b73c689
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Merge branch 'master' into feature/m5-subplan-actor
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b888afab71
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feat(actor): add plan_subplan tool and decision emission
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Add builtin/plan-subplan tool for strategy actors to emit SUBPLAN_SPAWN or SUBPLAN_PARALLEL_SPAWN decisions when decomposing a plan into child plans. Implements all acceptance criteria from issue #198: - SubplanPayload (Pydantic) validates goal, resource_scopes/project_ref (at least one required), merge_strategy, max_parallel (1-50), parallel flag, dependencies, and context_view override. - Defaults: merge_strategy=git_three_way, max_parallel=5, parallel=False, dependencies=[]. Omitted fields inherit sensible values automatically. - make_plan_subplan_spec(decision_service=None) factory supports optional DecisionService injection for persistent decision recording. - _build_rationale() generates human-readable rationale text (goal, scope, execution mode, dependencies, context_view) surfaced in plan explain. - register_subplan_tool() added to tool/builtins/__init__.py for bulk registration. PLAN_SUBPLAN_SPEC exported as the default ready-to-use spec. - Actor YAML example (examples/actors/strategy_with_subplan.yaml) with annotated serial and parallel spawn payload examples. - Behave BDD: 20 scenarios, 70 steps covering validation, defaults, decision type, rationale, service injection, registry, and ToolRunner. - Robot Framework: 9 smoke tests via robot/plan_subplan_tool.robot. - ASV benchmarks: benchmarks/subplan_actor_tool_bench.py (5 suites). - Coverage: 100% on subplan_tool.py. Lint, typecheck, and security clean. ISSUES CLOSED: #198 |
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a0f56228e2
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Merge branch 'master' into feature/m3-mcp-adapter
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120274da99 |
feat(di): wire decision services
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Create DecisionService application-layer service that wraps DecisionRepository with structured logging and UnitOfWork transaction management. Wire DecisionService and PlanLifecycleService into the DI container as Factory providers. Inject DecisionService into PlanLifecycleService so that phase transitions automatically record decisions: start_strategize records a strategy_choice decision and start_execute records an implementation_choice decision. Decision recording is optional and never blocks lifecycle transitions. Add Behave feature (5 scenarios), Robot Framework smoke tests (2 test cases), ASV benchmarks (3 benchmark classes), and DI reference documentation. ISSUES CLOSED: #173 |
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493e5cf8a1 |
fix(security): wire read_only through ExecuteStubActor and replace stubs with real tests
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- Add read_only kwarg to ExecuteStubActor.execute(), propagated to ChangeSetCapture; PlanExecutor._run_execute_with_stub passes plan.read_only through the execution path (P1 #2 fix) - Replace CLI fail-fast and Action-Skill stub scenarios with real ExecuteStubActor spy test and SkillContext.enforce_write_guard integration tests (P2 #1 fix) - Update docs: remove unimplemented Layer 5 (Action-Skill), add ExecuteStubActor wiring description, fix test command (P2 #2 fix) ISSUES CLOSED: #322 |
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2b09568cfa |
feat(security): enforce read-only actions
Tighten ToolRuntime._enforce_capabilities() to block ANY tool with writes=True when plan_read_only is set, removing the not-cap.read_only loophole that allowed certain write tools through. Tool name is now always included in the ToolAccessDeniedError message. Add read_only flag to ChangeSetCapture with ReadOnlyViolationError raised when write-capable tools are wrapped on a read-only plan. Add CLI fail-fast guards on plan execute and plan apply commands that abort before calling the service layer if plan.read_only is True. SkillContext.enforce_write_guard() already included tool name correctly and required no changes. Includes 18 Behave scenarios (90 steps), Robot integration tests, ASV benchmarks, and docs/reference/read_only_actions.md. ISSUES CLOSED: #322 |
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ffdd2f2b19 |
Merge branch 'master' into develop-brent-5
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32b81793a2 |
refactor(test): rename decision persistence files to avoid conflict with master
Rename our serialization-focused decision persistence suites to *_serialization to avoid add/add conflicts with the repository-based decision persistence suites that landed on master independently: - decision_persistence.feature -> decision_persistence_serialization.feature - decision_persistence_steps.py -> decision_persistence_serialization_steps.py - decision_persistence_bench.py -> decision_persistence_serialization_bench.py - decision_persistence.robot -> decision_persistence_serialization.robot - helper_decision_persistence.py -> helper_decision_persistence_serialization.py Updated robot helper path, step docstring, and testing.md references. |
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76db58414a
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Merge branch 'master' into feature/m3-agent-skills-loader
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f8bc02869a
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Merge branch 'master' into feature/m3-agent-skills-loader
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c406781b86 |
fix(security): address PR #435 review feedback
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P0: reject register() after close_all() with RuntimeError. P1: catch CancelledError in close_all(), use WeakKeyDictionary for cancellation_reasons to prevent memory leak, guard StateManager update_state/reset/load_checkpoint/time_travel after close(). P2: contextlib.suppress in __del__ for partial construction, re-cancel pending tasks in cleanup_tasks_async, handle late tasks added during await window, guard AcpEventQueue.publish() after close with _is_closed flag and is_closed property, fix ASV TimeRegisterBatch crash. Tests: 5 new Behave scenarios (T1-T4 + is_closed), log handler and event loop cleanup in after_scenario (T5-T6). Docs: async_safety.md updated for register-after-close and state mutation guards. ISSUES CLOSED: #321 |
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5d5d3fde2c |
fix(security): close async resources and leaks
Add AsyncResourceTracker (core/async_cleanup.py) providing a central registry for async resources with timeout-bounded close_all(), async context manager support, and a __del__ finalizer that logs leaked resources by name. Enhance LangGraphBridge with cleanup_tasks_async() that awaits in-flight tasks with a deadline instead of fire-and-forget cancel(). Add cancellation_reasons dict to trace why tasks were cancelled. Add StateManager.close() to properly release checkpoint file handles and complete the RxPY BehaviorSubject. Add AcpEventQueue.close() to dispose all subscriptions. Includes 14 Behave scenarios (67 steps), Robot integration tests, ASV benchmarks, and docs/reference/async_safety.md. ISSUES CLOSED: #321 |
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27bef69ddd |
feat(decision): add decision persistence
Add decision persistence layer with DecisionRepository, DecisionModel, and Alembic migration. Includes tree queries (BFS traversal via deque, path-to-root), superseded lookup, ordered decision path retrieval, concrete Decision type annotations (via TYPE_CHECKING), and comprehensive test coverage (Behave BDD, Robot Framework, ASV benchmarks). Updated database_schema.md, CHANGELOG.md, and CONTRIBUTORS.md. ISSUES CLOSED: #171 |
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595cfd172f
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Merge branch 'master' into feature/m3-mcp-adapter
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b25a886df8
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feat(skill): add MCP refresh hooks
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Implement SkillRegistry.refresh(name) and refresh_all() to recompute flattened tool sets on demand. Wire MCPToolAdapter.dispatch_notification() to MCPRefreshHook, which debounces rapid notifications/tools/list_changed bursts into a single refresh_all() call (default 0.5 s window). Add safeguard that skips tool-ref validation when no ToolRegistry is configured, emitting a single WARNING with recovery steps. Introduce immutable SkillRefreshResult (refreshed/failed/skipped counts) with to_summary() and merge() for CLI and log output. New files: - src/cleveragents/skills/refresh.py (SkillRefreshResult) - src/cleveragents/mcp/refresh_hook.py (MCPRefreshHook) - features/skill_refresh.feature (19 Behave scenarios) - features/steps/skill_refresh_steps.py - robot/skill_refresh.robot (10 Robot tests) - robot/helper_skill_refresh.py - benchmarks/skill_refresh_bench.py (ASV benchmarks) - docs/reference/skill_refresh.md Modified: - src/cleveragents/skills/registry.py (refresh, refresh_all) - src/cleveragents/mcp/adapter.py (notification listener API) - src/cleveragents/skills/__init__.py (export SkillRefreshResult) - src/cleveragents/mcp/__init__.py (export MCPRefreshHook) - CHANGELOG.md ISSUES CLOSED #168 |
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c40ea014dc
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feat(cli): add skill tools and refresh commands
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Implemented agents skill refresh command to recompute tool flattening and sync MCP-backed skills. Enhanced skill list/show/tools outputs with capability summary fields. - agents skill refresh <name>|--all to recompute flattening - Enhanced skill list/show/tools with capability summary and tool counts - Added --format json/yaml schemas for refresh output - CLI errors for nonexistent skills and MCP sync failures - Behave tests (skill_cli.feature), Robot tests (skill_cli.robot) - ASV benchmarks (skill_cli_bench.py) for CLI overhead baseline - Updated docs/reference/skill_cli.md with refresh command examples - Documented refresh side effects and caching behavior ISSUES CLOSED: #167 |
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cb82fc51df
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feat(skill): add agent skills loader
Implemented AgentSkillSpec loader that parses SKILL.md frontmatter and progressive disclosure sections (discover/activate/deactivate) into structured SkillStep objects with stable 1-based ordering. Mapped Agent Skills to AgentSkillToolDescriptor with namespaced naming (namespace/short_name), source="agent_skill", read-only defaults, and AgentSkillResourceSlot bindings for scripts/, references/, and assets/ directories. All resource slots are unconditionally read_only. Added explicit validation for missing frontmatter fields (name, description) and invalid namespace format with actionable error messages. Added docs/reference/agent_skills.md covering folder layout, SKILL.md parsing rules, progressive disclosure model, and tool mapping. Added Behave scenarios covering valid/invalid SKILL.md parsing, namespaced naming, step ordering, missing frontmatter errors, progressive disclosure lifecycle, tool mapping, and resource binding slots. Added Robot Framework integration tests using the deploy-to-staging example skill folder (robot/agent_skills_loader.robot). Added ASV benchmarks for parsing throughput, folder load, progressive disclosure lifecycle, and resource listing (benchmarks/agent_skills_loader_bench.py). ISSUES CLOSED: #160 |
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519e26fb02
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Merge branch 'master' into feature/m3-mcp-adapter
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b8d7c4c893
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Merge branch 'master' into feature/m2-actor-yaml
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