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Author	SHA1	Message	Date
freemo	4e7bb5ae4e	build: more explicit on how to run the script	2026-04-17 17:27:11 -04:00
freemo	47d630599a	build: further clarified how to get the PRs using the scripts	2026-04-17 17:07:58 -04:00
freemo	6153da8deb	build: trying to improve skill comprehension of scripts	2026-04-17 16:53:33 -04:00
freemo	e8f06fa433	build: made invocation of scripts more explicit	2026-04-17 16:32:37 -04:00
freemo	17bbe20376	Revert "build: adding auto-agents-system as a task as well as a skill." ... This reverts commit 5c8b5a84d2.	2026-04-17 16:28:28 -04:00
freemo	5c8b5a84d2	build: adding auto-agents-system as a task as well as a skill.	2026-04-17 16:19:00 -04:00
freemo	fe95acb856	build: added more clarification for loading scripts	2026-04-17 16:02:21 -04:00
freemo	6ed9dbc2e7	build: expanded capabilities (permissions) of the git rebaser subagent	2026-04-17 15:45:54 -04:00
freemo	555509c609	build: tweaked reasoning level on pr-merge related agents	2026-04-17 15:34:56 -04:00
freemo	aaeecd1616	build: reduced cost of models for merging by picking cheaper models	2026-04-17 15:26:49 -04:00
freemo	868fdeff8a	build: seperated out the actual rebase and conflict resolution to its own specialized subagent	2026-04-17 15:03:24 -04:00
HAL9000	66850665b7	fix(sandbox): split oversized step file and update CONTRIBUTORS.md ... Split checkpoint_manager_coverage_steps.py (692 lines) into three focused modules to comply with the 500-line file limit: - checkpoint_manager_coverage_steps.py: model, protocol, manager init, create_checkpoint, _snapshot_directory, and _cleanup_snapshot steps (408 lines) - checkpoint_manager_rollback_steps.py: rollback_to, list_checkpoints, and delete_checkpoint branch steps (283 lines) - checkpoint_manager_bug7488_steps.py: Bug #7488 sandbox_path auto-stored-in-metadata steps (59 lines) Also updated CONTRIBUTORS.md to document HAL 9000's contribution for bug fix #7488 as required by CONTRIBUTING.md guidelines. ISSUES CLOSED: #7488	2026-04-17 18:34:16 +00:00
HAL9000	beceb183d0	fix(sandbox): store sandbox_path in checkpoint metadata to enable rollback ... CheckpointManager.create_checkpoint() computed sandbox_path from sandbox.context.sandbox_path but never stored it in the metadata dict. This caused rollback_to() to always find metadata.get('sandbox_path') returning None, silently skip the rollback, and return False. The fix adds sandbox_path to the metadata dict immediately after it is resolved from the sandbox context, before the SandboxCheckpoint is constructed. rollback_to() can now retrieve the path and correctly restore the sandbox filesystem state. Added two new BDD scenarios to checkpoint_manager_coverage.feature: - Verifies sandbox_path is automatically stored in metadata on create - Verifies rollback succeeds without manually supplying sandbox_path ISSUES CLOSED: #7488	2026-04-17 18:33:39 +00:00
freemo	d6fca18c01	build: broke the 4 stage pr merge cycle into a 6 stage cycle and eliminating PRs that arent stale and need review	2026-04-17 14:20:40 -04:00
CoreRasurae	0c5b140d29	fix(database): include alembic files in package distribution ... Move alembic configuration and migration files from repository root into the Python package structure to ensure they are included in the wheel distribution. This fix resolves the FileNotFoundError when running `agents init` in Docker containers or any environment using the built wheel distribution. Changes: - Move alembic/ directory from repo root to src/cleveragents/infrastructure/database/migrations/ - Move alembic.ini to the same new location and update script_location setting - Update MigrationRunner._find_alembic_ini() to search from the new canonical location within the package - Update create_template_db.py to point to the new alembic.ini location - Update documentation references to reflect new migration file locations - Create __init__.py for migrations package - The env.py file is imported when running tests that verify all modules can be imported without errors. However, context.config is only available when alembic is actually running migrations, not during normal module imports. This caused an AttributeError when the test tried to import the migrations.env module. - Fix by using getattr() with a default value to safely access context.config, and guard all code that uses config with None checks. This allows the module to be safely imported while still functioning correctly during migrations. Testing: - Verified MigrationRunner can locate alembic.ini in new location - Tested agents init succeeds in creating project with database - Template database creation works correctly - All migration tests should pass without changes Alembic files now follow standard Python packaging conventions, making them automatically included in wheel distributions without special configuration. ISSUES CLOSED: #4180	2026-04-17 17:40:00 +00:00
freemo	11ba77cf73	build: fix to get mroe predicatable behavior out of pr-merge-worker	2026-04-17 13:35:25 -04:00
freemo	5762f92583	build: tweaked the pr-merge agents to ensure they use the skill scripts more consistently	2026-04-17 13:00:24 -04:00
freemo	afa4ebd19b	build: fixed up the systems skill so it now provides better access to information about scripts to ensure more consistent usage	2026-04-17 12:50:46 -04:00
hamza.khyari	1663750b78	Merge pull request 'fix(checkpoint): wire CheckpointManager into PlanExecutor execution path' (#4218) from bugfix/checkpoint-wiring into master ... Reviewed-on: #4218 Reviewed-by: Jeffrey Phillips Freeman <jeffrey.freeman@cleverthis.com>	2026-04-17 11:58:50 +00:00
hamza.khyari	bdd1ea4f3a	fix(checkpoint): wire CheckpointManager into PlanExecutor execution path ... CheckpointManager was never wired into PlanExecutor — the CLI factory constructed PlanExecutor without a checkpoint_manager (defaulted to None), silently skipping all checkpoint hooks. Fix: - Register CheckpointManager as Singleton in DI container - Resolve container singleton in _get_plan_executor() and pass to PlanExecutor constructor - Bridge infra→domain: _try_create_checkpoint() now persists last_checkpoint_id on the plan via _commit_plan(), raises PlanError if persistence fails - Default checkpointable=True for writable+sandboxable resources and write-capable tools (model_validators on ResourceCapabilities and ToolCapability) - Validate that non-writable/non-sandboxable resources cannot be checkpointable (ValueError guard) - Add post-execute A2A facade notification using plan.status to avoid duplicate execute→execute transition errors Tests: - 10 Behave scenarios covering DI wiring, singleton identity, checkpoint creation, plan metadata update, rollback, graceful fallback, no-arg constructor, capability defaults (positive + 2 negative) - Updated consolidated_resource, consolidated_skill, and Robot helper_skill_flatten for new checkpointable defaults ISSUES CLOSED: #1253	2026-04-17 11:46:38 +00:00
hurui200320	e2b127b7e5	fix(e2e): replace naive OpenAI key-presence check with live API probe in E2E suite setups ... The existing actor-selection logic in several E2E suite setups checked only whether OPENAI_API_KEY was present (non-empty). A valid key that has hit its quota limit passes that check but fails at runtime with HTTP 429, causing the test to fail even though Anthropic credits are available. Changes: - Add robot/e2e/check_openai_key.py: stdlib-only (urllib.request) script that sends a minimal chat-completion request ('Hi', max_tokens=1, gpt-4o-mini) to the OpenAI API. Exits 0 on HTTP 200; exits 1 for quota (429), auth (401), network errors, or any other failure. - Add 'Resolve LLM Actor' keyword to robot/e2e/common_e2e.resource: runs the probe script via ${PYTHON} and returns the openai_model argument (default openai/gpt-4o) on success, or the anthropic_model argument (default anthropic/claude-sonnet-4-20250514) on failure. Skips the probe entirely when OPENAI_API_KEY is not set. - Update m6_acceptance.robot, wf04_multi_project.robot, wf05_db_migration.robot, wf07_cicd.robot, and wf16_devcontainer.robot to use 'Resolve LLM Actor' instead of the inline has_openai boolean check. No production source code (src/) is modified. The decision to fall back to Anthropic is made once per suite setup, before any test runs. Closes #10198	2026-04-17 18:00:47 +08:00
hurui200320	80c8636c4a	Revert "feat: add fallback to Anthropic Sonnet when OpenAI quota is exhausted" ... This reverts commit f5712787e0.	2026-04-17 18:00:47 +08:00
hurui200320	8a89a5d5a6	Revert "debug: upgrade logging levels for fallback diagnostics" ... This reverts commit 51472c0b37.	2026-04-17 18:00:46 +08:00
hurui200320	ed7276773e	Merge branch 'master' into fix/plan-diff-correction-stub	2026-04-17 09:38:13 +00:00
hurui200320	1fda56b778	fix(cli): implement plan diff --correction to show real correction attempt diff ... Implement spec-compliant correction diff output for `agents plan diff --correction <CORRECTION_ATTEMPT_ID>`. Fixes the following issues from the cycle-1 PR review: - C1/M1: Replace direct `unit_of_work.correction_attempts` access with the proper `unit_of_work.transaction()` context manager, eliminating the AttributeError crash and the resource (session) leak. - C2: Add `unit_of_work: UnitOfWork | None = None` constructor parameter to `PlanApplyService` and wire it in `_get_apply_service()` via `container.unit_of_work()`, removing the illegal `get_container()` call inside the method body (ADR-003 DI violation). - C3: Replace metadata serialization stub with a three-section structured diff (Correction Diff summary, Comparison table, Patch Preview) as specified in §agents plan diff of the specification. - C4/M2: Add `features/plan_correction_diff.feature` with 6 BDD scenarios covering all 4 output formats plus plan-not-found and correction-not-found error paths. - C5: Update the three existing BDD scenarios that tested old stub behavior to mock `_get_apply_service()` and assert the new output. - C6: Rename branch to `bugfix/m4-plan-diff-correction-stub` per CONTRIBUTING.md convention. - C7: Amend commit message with body and ISSUES CLOSED footer. - C8: Narrow `except Exception` to `except CorrectionAttemptNotFoundError` to avoid masking programming errors. - M3: Add `robot/plan_correction_diff.robot` and `robot/helper_plan_correction_diff.py` integration test covering rich, plain, and JSON formats and the not-found error path. - M4: Type `_build_correction_diff_dict` parameter as `CorrectionAttemptRecord` instead of `Any`. - M5: Change `fmt: str` to `fmt: Literal["rich", "plain", "json", "yaml"]` on both `diff()` and `correction_diff()`, with a `cast()` call in the CLI layer where Typer supplies a plain `str`. - M6: Add `ValueError` guards for empty `plan_id` and `correction_attempt_id` at the top of `correction_diff()`. - M7: Add blank line between `diff()` and `correction_diff()` method definitions. - M8: Update PR description to reflect actual implementation. - m1: Remove unused `plan` variable in `correction_diff()`. - m2: Reduce three blank lines to two between top-level definitions in `plan_apply_service.py`. - n1: Remove trailing whitespace from blank line in `plan.py`. Quality gates: lint (ruff), typecheck (pyright strict), unit_tests (Behave 632 features / 0 failures) all pass. ISSUES CLOSED: #9085	2026-04-17 08:34:33 +00:00
hurui200320	8953449dc2	fix(actor): validate v3 YAML via ActorConfigSchema in agents actor add CLI ... - schema.py: provider field changed to Optional[str] with model validator validate_provider_required_for_llm_graph() that requires it only for LLM and GRAPH actor types; TOOL actors do not require provider - schema.py: is_v3_yaml() uses version_str == "3" or version_str.startswith("3.") to avoid false positives from "30" or "300" version strings - schema.py: tool namespace validation uses strict 2-part split to reject empty namespace or empty name (e.g. "/tool", "ns/", "a/b/c") - cli/commands/actor.py: schema_version extraction uses raw_version pattern (no # type: ignore[assignment]) for clean static typing - actor/__init__.py: is_v3_yaml removed from __all__ and _LAZY_IMPORTS since it is a module-private helper, not a public API - robot/actor_add_v3_schema_validation.robot: YAML fixtures for 'Reject v3 LLM Actor Without Model Field' and 'Reject v3 TOOL Actor Without Tools Field' now include required provider field (and model for TOOL fixture) - robot/helper_actor_add_v3_schema_validation.py: except clauses unified to catch (subprocess.TimeoutExpired, FileNotFoundError) in both add_actor() and update_actor() functions - features/actor_add_v3_schema_validation.feature: 'Update a v3 actor with valid YAML succeeds' scenario now includes 'And the actor should be validated via ActorConfigSchema'; error assertions tightened to exact messages (e.g. "Input should be 'llm', 'tool' or 'graph'", "Node ID must be alphanumeric", "must be namespaced") - features/steps/actor_add_v3_schema_validation_steps.py: step_run_actor_update now spies on ActorConfigSchema.model_validate; failure paths assert isinstance(result.exception, SystemExit) ISSUES CLOSED: #5869	2026-04-17 16:28:45 +08:00
HAL9000	449c33b752	style(tests): apply ruff format to run_behave_parallel.py ... Fix formatting of conditional expression in _is_btrfs_or_overlayfs() that was flagged by ruff format --check in CI.	2026-04-17 07:16:05 +00:00
Test	4fc4d7863c	fix(tests): prevent behave-parallel multiprocessing deadlock on btrfs/overlayfs ... Detect btrfs and overlayfs filesystems and automatically fall back to sequential mode to prevent deadlocks caused by SQLite WAL file locking and btrfs COW copy-up locks when multiple forked workers try to access the same files simultaneously. The fix adds a _is_btrfs_or_overlayfs() function that: 1. Attempts to detect the filesystem type using stat command 2. Falls back to reading /proc/mounts if stat fails 3. Returns True if the filesystem is btrfs or overlayfs The sequential mode condition is updated to include this check, ensuring that on affected filesystems, all features run in a single process instead of being split across multiple forked workers. ISSUES CLOSED: #9390	2026-04-17 07:16:05 +00:00
freemo	ebf54c642c	Build: Attempt to prevent merge workers from waiting till merge completes	2026-04-17 01:23:28 -04:00
HAL9000	e18ac5f23c	fix(security): replace startswith sandbox check with Path.relative_to() in validate_path #7558 ... The validate_path() function in file_tools.py used str.startswith() to verify that a resolved path stays within the sandbox root. This allowed sibling directories whose names share a string prefix with the sandbox (e.g. /tmp/sandbox-escape/ bypassing /tmp/sandbox/) to escape the containment check. Replace the string prefix check with Path.relative_to(root), which performs a proper OS-level path prefix comparison using path separators. Add a Behave regression scenario tagged @tdd_issue @tdd_issue_7558 that exercises the prefix-collision bypass to prevent regressions. ISSUES CLOSED: #7558	2026-04-17 04:50:55 +00:00
HAL9000	51472c0b37	debug: upgrade logging levels for fallback diagnostics ... Change fallback LLM creation and invocation logs from DEBUG to WARNING level so they appear in Robot Framework test output. Also enhance error message to clearly show which provider failed and why. This change makes it possible to diagnose why the fallback is not working by seeing the actual logs in test output instead of having them filtered as DEBUG level messages. Logs now include: - 'Creating fallback LLM instance: anthropic/claude-sonnet-4-20250514' - 'Fallback LLM created, attempting invocation' - 'Using cached fallback LLM, attempting invocation' - 'FALLBACK PROVIDER FAILED: anthropic/claude-sonnet-4-20250514 returned error: [error details]' This will help diagnose why E2E tests fail with 'both providers exhausted' when Anthropic should have available credits.	2026-04-17 03:56:35 +00:00
CoreRasurae	f5712787e0	feat: add fallback to Anthropic Sonnet when OpenAI quota is exhausted ... Implements graceful degradation for E2E robot integration tests that hit OpenAI 429 quota limit errors. Changes: - Add _is_quota_error() helper to detect quota-specific API errors (429, insufficient_quota, rate_limit) - Modify _execute_with_llm() in StrategyActor to catch quota errors and attempt fallback to Anthropic Haiku - Configure fallback provider as 'anthropic/claude-sonnet-4-20250514' - Add comprehensive logging for quota error detection and provider fallback - Add E2E test scenarios for quota fallback verification When quota errors occur on both OpenAI and Anthropic fallback, tests now fail with a clear message explaining that the test outcome cannot be verified when no LLM provider is available. This ensures CI/CD pipelines properly track which tests could not be executed due to quota constraints, rather than silently skipping them and creating false confidence in test coverage. This ensures CI/CD pipelines can complete E2E tests even when the primary provider (OpenAI) hits quota limits, improving pipeline reliability and reducing false negatives caused by provider-specific issues. 1. **Cache fallback_llm instance** - Instead of recreating the fallback LLM every time a quota error occurs, cache it as an instance variable (self._fallback_llm). This avoids unnecessary re-initialization overhead. 2. **Implement quota recovery logic** - Add intelligent recovery behavior: - Track last quota error timestamp (self._last_quota_error_time) - Track fallback mode state (self._using_fallback) - Once quota error detected, switch to fallback provider - Only attempt to recover primary provider every 5 minutes (_QUOTA_RECOVERY_INTERVAL) - This avoids hammering primary provider with repeated quota errors 3. **Add detailed recovery logging** - Log quota fallback transitions and recovery attempts to improve observability and debugging. Benefits: - Reduced latency: No redundant primary provider calls after quota error - Reduced overhead: Cached fallback LLM instance, no per-call recreation - Better observability: Clear logging of fallback mode entry/exit - Intelligent recovery: Automatic recovery attempt after 5-minute interval Updated tests: - M6 E2E Event Queue Via Plan Lifecycle Transitions - M6 E2E Hierarchical Decomposition Via Plan Tree - M6 E2E Full Autonomy Acceptance Flow Fixes: #10042	2026-04-17 03:56:35 +00:00
freemo	82591c1a86	Build: Trying to fix skill script not being called	2026-04-16 23:27:39 -04:00
freemo	9684d80637	Build: Enabling skill scripts	2026-04-16 23:01:57 -04:00
freemo	6dad967130	Build: fixed systems skill to link to the scripts from the main skill page	2026-04-16 22:41:42 -04:00
freemo	85c22aa7a8	Build: Fixed bug in permissions, sped up product-verifier slightly	2026-04-16 21:58:11 -04:00
freemo	5e3b4c9b68	build: fixed typo in permissions in pr-merge related agents	2026-04-16 20:21:59 -04:00
freemo	588199886e	build: wrong name for auto-agents system skill	2026-04-16 19:53:09 -04:00
freemo	438df82caa	build: changed pr-merge process (including supervisor) to use new skills and scripts	2026-04-16 19:10:04 -04:00
freemo	ac702cc375	build: Added script to initiate the merge	2026-04-16 18:50:59 -04:00
freemo	d3e0911f86	build: added script for rebasing on server to system skill	2026-04-16 18:17:15 -04:00
freemo	703cf13c01	build: removed rules skills, its in the system skill	2026-04-16 18:01:14 -04:00
freemo	a58d17416c	build: added scripts into auto-agents-system skill for getting the PR categories for merging.	2026-04-16 17:59:56 -04:00
freemo	0257841825	Revert "refactor(agents): migrate all agent definitions to use skills for universal rules" ... This reverts commit bb97f1450e.	2026-04-16 14:15:30 -04:00
freemo	bb97f1450e	refactor(agents): migrate all agent definitions to use skills for universal rules ... Replace ~600 chars of verbatim per-agent boilerplate with skill references. All 91 agents now load cleveragents-agent-rules for exhaustive pagination, label management, bot signatures, and credential flow rules. Adds explicit skill: "*": deny + targeted allows to every agent permission block, matching the existing bash: and task: deny-first convention. Tier selectors carry no skill permissions since they are pure pass-through with no skill references in their bodies. forgejo-label-manager also grants forgejo-api for its curl pattern reference.	2026-04-16 01:00:55 -04:00
freemo	dceb0e91d3	docs(skill): add cleveragents-agent-rules universal agent rules skill ... Introduces a new skill containing the complete specification for the five universal operational rules every agent must follow: exhaustive pagination protocol, label management via forgejo-label-manager, bot signature format, credential flow hierarchy, and localhost:4096 restriction.	2026-04-16 01:00:48 -04:00
clever-agent	93c349d531	Build: Stopped using codex for most of our agents	2026-04-16 00:51:51 -04:00
HAL9000	d167155e90	Build: Removed gemini as a model option	2026-04-15 23:43:29 -04:00
freemo	c9dc70004c	docs(skill): add full redundancy and self-healing documentation to cleveragents-system skill ... Add new references/redundancy/README.md (280 lines) covering: - Three-layer redundancy architecture overview (product-builder / watchdog / supervisors) with the key insight that each layer uses a different observation mechanism to prevent blind spots between layers - Layer 1 (product-builder): fast cycle (60s liveness), deep inspection (5-min message reading with anti-pattern catalogue: error loops, circular patterns, policy violations, context exhaustion), worker health check (pool count vs expected), hourly verification - Layer 2 (system-watchdog): independent 5-min audit using Forgejo tracking issue STALENESS rather than OpenCode session status — catches frozen-but-alive sessions that appear healthy to product-builder; session introspection for anti-pattern detection; clear role separation (watchdog detects, product-builder restarts) - Layer 3 (supervisor self-monitoring): per-cycle worker health checks, stuck detection (15-min threshold), completed vs crashed distinction, pool filling - State persistence as the foundation of self-healing: everything externalized to Forgejo (tracking issues, attempt comments, claim protocol, announcements) - Supervisor crash-recovery pattern: session crash → product-builder detects ≤60s → relaunch → READ_TRACKING_STATE first → light/moderate/full recovery based on offline duration → resume from recovered state - Worker crash-recovery pattern: crash → supervisor detects in next cycle → Forgejo evidence check → re-dispatch at same or escalated tier - Two independent health signals table: OpenCode (session presence/status, latency 60s) vs Forgejo (tracking staleness, latency 2×interval) — what each catches - Complete failure mode catalogue (13 failure types with: who detects it, how, recovery action, and whether recovery is automatic or requires human) - async-agent-monitor health classifications: healthy/stuck/idle/finished/errored with threshold and configurable idle_threshold_minutes parameter - Redundancy gaps and limitations: product-builder has no watcher; watchdog detects but cannot restart; worker downtime latency varies by supervisor sleep Expand SKILL.md (539 → 775 lines, 10 → 13 decision trees): - Significantly expand 'Is something wrong?' tree: now lists every failure type with which layer detects it, how detection works, and recovery action (supervisor missing, frozen, error loop, waiting for input, worker crashed, worker frozen, supervisor stopped dispatching, orphaned claim, CI violations, multiple supervisors down, product-builder crash) - Add new 'How does the system self-heal?' tree: full three-layer redundancy decision tree with per-layer mechanics (fast/deep/hourly cadences), the Forgejo persistence foundation, complete supervisor crash-recovery pattern, complete worker crash-recovery pattern, and the single-point-of-failure note - Update Key Numbers table: add worker health check and hourly cycle entries; clarify session health threshold is configurable; add watchdog staleness threshold (2×interval); add supervisor max downtime (≤60s); add worker re-dispatch latency (varies by sleep interval) - Update frontmatter description to cover self-healing and redundancy - Update reference index to describe the new redundancy reference file ISSUES CLOSED: #0	2026-04-15 20:18:54 +00:00
freemo	e1e65c85ae	docs(skill): final cleanup pass — remove remaining duplicated project knowledge, cross-reference other skills ... agent-registry/README.md: - Remove typecheck-fixer 'Never uses type: ignore' rule (contributing rule, lives in cleveragents-contributing not the system registry) - Remove coverage-improver '>=97%' threshold (project-specific threshold, lives in cleveragents-contributing) - Change new-issue-creator description from 'following CONTRIBUTING.md format' to 'following the project issue format' with cross-reference pointer - Remove subtask-loop trivial description; expand to show the full implement → test → quality gates → review loop it manages - Remove duplicate forgejo-label-manager entry ('See above.') — was listed twice in the utility subagents table - Add cross-reference note at top of Utility Subagents section: descriptions focus on system role; project-specific rules (testing philosophy, quality gates, commit standards, issue format) are in cleveragents-contributing - AUTO-IMP-SUP dispatch ordering: add inline cross-reference note pointing to cleveragents-contributing and cleverthis-guidelines for label definitions - AUTO-OWNR description: replace specific label names ('MoSCoW labels', 'Wont Do') with generic role description + cross-reference note SKILL.md: - Reference Index: fix tracking-system entry description — remove 'label rules' (those were removed from tracking-system last pass); replace with accurate description of what the file now covers (Automation Tracking and needs feedback labels as system-specific labels) No system-specific content was removed: all agent prefixes, the full announcement relevancy matrix, worker tag patterns, sleep intervals, worker count formulas, tier system mechanics, tracking system operations, credential propagation hierarchy, and claim/heartbeat/release protocol are fully preserved. ISSUES CLOSED: #0	2026-04-15 20:13:47 +00:00