Epic: The Self-Healing Swarm (v0.04)

[dewitt]

As discussed in our new vision design doc (docs/design/23-self-healing-swarm.md), we need to evolve Swarm from a reactive CLI into a proactive, self-healing ecosystem.

By treating the ~/.config/swarm/trajectories/ local database as a training dataset, Swarm can autonomously adapt.

Key Initiatives for v0.04

• Trajectory Mining & Pattern Recognition: Run a background "Swarm Analyst" to identify systemic failure modes.
• Automated Skill Generation: Dynamically draft SKILL.md files for repeated boilerplate execution flows.
• Dynamic Prompt Optimization (DPO): Extract optimal conversational paths from fast trajectories to fine-tune intent routing.
• Proactive Environment Remediation: Sub-plan to fix broken tools (e.g. apt-get install or fetch API keys) before failing.
• Self-Monitoring Load Balancing: Detect 429s or latency spikes and shift from Gemini to Claude gracefully.
• Automated Post-Incident Artifacts: Generate incident_report.md on multiple request_replan failures.
• Memory Compaction: Asynchronously summarize conversation history at 80% context saturation.
• Semantic Test Generation: Convert successful long-running multi-agent workflows into structural regression tests.
• Tool Reliability Scoring: Deprecate frequently failing tools on specific machine architectures dynamically.
• Heuristic Deadlock Detection ("Overwatch"): Monitor the live trajectory stream to violently interrupt logic loops.

[dewitt]

Today's progress has significantly advanced the Self-Healing Swarm roadmap. I have implemented the following core architectural components:

✅ Completed Initiatives

• Automated Post-Incident Artifacts: The Swarm now automatically generates a localized in the workspace when a session hits a recursive replan limit. This artifact contains the full JSON trajectory dump and the final agent reasoning to aid in asynchronous self-healing analysis.
• Heuristic Deadlock Detection ("Overwatch"): Verified the existing Overwatch routines that monitor the execution graph for deadlocks, interrupt loops, and automatically commit the failure reasons to Tier 3 Semantic Memory to prevent future occurrences.
• Automated Skill Generation (Foundational): Implemented thread-safe, mid-session hot-reloading of the directory. This allows the to dynamically create new capabilities that are immediately ingested by the orchestrator without restarting the session.
• Self-Correction & Memory Management: Added the command, giving users a direct mechanism to purge poisoned or hallucinated facts from the agent's long-term semantic knowledge.
• Environment Remediation (Surgical): Added automatic home directory tilde () expansion to all file-system tools, solving a systemic environment barrier for agents.

I've also resolved the high-friction JSON parsing and terminal artifact issues, providing a stable foundation for the upcoming Swarm Analyst and Tool Reliability Scoring phases.