export default atft-autonomy

name	atft-autonomy
description	Coordinate Claude Code skills with OpenAI Codex autonomous workflows for end-to-end ATFT-GAT-FAN maintenance.
proactive	true

ATFT Autonomy Skill

Mission

• Seamlessly orchestrate Claude and Codex agents to keep the ATFT-GAT-FAN stack production-ready.
• Decide when to run deep Codex analyses versus fast Claude remediations.
• Maintain shared context (AGENTS.md, health snapshots, run logs) across agents.

Engagement Signals

• Requests to “run full autonomous maintenance”, “coordinate Claude and Codex”, or “schedule daily self-healing”.
• Situations where an issue spans multiple domains (dataset + training + quality).
• Need to generate or refresh .mcp.json, AGENTS.md, or other shared configs.

Preflight Checklist

1. Confirm tool availability:
   • command -v codex (expect npm package @openai/codex).
   • command -v ./tools/claude-code.sh.
2. Verify configuration files:
   • .mcp.json exists with filesystem/git servers (tools/codex.sh recreates if missing).
   • AGENTS.md up to date with latest guidelines.
3. Run snapshot diagnostics:
   • tools/project-health-check.sh --summary (logs to _logs/health-checks/).
   • nvidia-smi and df -h to ensure resource headroom before long autonomous jobs.

Core Playbooks

1. Full Daily Autonomy Loop

1. ./tools/claude-code.sh --no-check "Run proactive maintenance checklist" — quick fixes + TODO updates.
2. ./tools/codex.sh --max --exec "Perform deep optimization sweep across dataset, training, and research modules" — longer Codex session with MCP.
3. Append combined findings to docs/ops/autonomy_log.md (capture commands run, deltas, next steps).
4. git status --short → review diffs, ensure no unintended drift.

2. Incident Response (multi-domain failure)

1. Launch Claude for rapid triage: ./tools/claude-code.sh "Investigate failed training and prepare briefing for Codex".
2. Pass Claude findings to Codex:
   ./tools/codex.sh --exec "Read docs/ops/incident_brief.md and propose remedial plan".
3. Execute agreed actions (dataset rebuild, training rerun, quality checks).
4. Update docs/ops/incident_log.md with both agents’ actions and resolutions.

3. Scheduled Autonomous Optimization

1. Add cron entry (example):
   0 2 * * * cd /workspace/gogooku3 && ./tools/codex.sh --max >> _logs/daily-optimization.log 2>&1.
2. Pair with weekly Claude sweep:
   0 7 * * MON cd /workspace/gogooku3 && ./tools/claude-code.sh --no-check >> _logs/weekly-claude.log 2>&1.
3. Summarize improvements weekly by aggregating _logs/codex-sessions/*.log and _logs/claude-code/*.log; record highlights in docs/ops/weekly_autonomy_report.md.

Shared Context Management

• Ensure both agents read CLAUDE.md and AGENTS.md before editing high-risk files.
• Rotate docs/SKILLS_GUIDE.md and claude/skills/ when procedures change.
• Store cross-agent decisions in EXPERIMENT_STATUS.md or docs/ops/autonomy_log.md.

Failure Handling

• Codex CLI missing → npm install -g @openai/codex.
• MCP server errors → regenerate .mcp.json via ./tools/codex.sh and restart run.
• Conflicting edits → consolidate drafts under docs/ops/autonomy_pending/ and resolve manually.
• Resource saturation → stagger Claude/Codex runs, cap concurrency in cron.

Handoff

• After combined sessions, notify stakeholders by updating docs/ops/weekly_autonomy_report.md.
• Attach session logs _logs/codex-sessions/*.log and _logs/claude-code/*.log for audit.
• Re-sync ~/.claude/skills/ so Claude picks up any procedural updates discovered during Codex runs.