- Block REST API endpoints for label creation at the bash level for all agents.
- Restrict `forgejo_create_label` and related MCP tools for all agents.
- Restrict `forgejo_add_issue_labels` to only the `forgejo-label-manager`.
- Ensure all label operations are centralized through the `forgejo-label-manager`.
- Update agent definitions to use the label manager instead of direct API calls or MCP tools for adding labels.
This prevents agents from creating new project-level labels and enforces the use of organization-level labels, resolving the issue of duplicate labels being created.
- Remove maximum cap (16) on CA_MAX_PARALLEL_WORKERS in resources.yaml
- Can now be set to any positive value (32, 64, etc.)
- Only minimum validation remains (must be > 0)
- Remove dynamic backpressure/throttling from implementation-orchestrator
- Dispatch always runs at full configured speed
- Resource monitoring remains for visibility only
- No automatic reduction of slots_available based on failures
- Convert system-watchdog from auto-degradation to monitoring + suggestions
- Renamed DEGRADATION_THRESHOLDS to HEALTH_THRESHOLDS
- Removed apply_system_degradation() and check_degradation_recovery()
- Changed findings to include suggestions instead of actions
- Watchdog now reports issues with fix recommendations
- No automatic throttling or pausing of agents
The system now operates at maximum configured speed at all times,
with the watchdog providing diagnostic insights when issues arise.
- Add system-watchdog audit for PRs with 3+ failed attempts
- Implement automatic human assistance requests with detailed analysis
- Add deep context gathering to implementation-worker before fixes
- Enhance all agents with enriched context propagation
- Add loop detection to prevent repetitive failed attempts
- Improve PR reviewer with anti-pattern detection
- Update human-liaison to provide targeted help for struggling PRs
- Add historical awareness to PR fix orchestrator
- Enhance epic-planner with context-aware issue creation
- Create documentation for improvements and future agent ideas
These changes enable the system to:
- Recognize when it's stuck and needs human help
- Learn from previous failures to avoid repetition
- Understand full context including comments and history
- Provide detailed debugging information to humans
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