atft-autonomy
Coordinate Claude Code skills with OpenAI Codex autonomous workflows for end-to-end ATFT-GAT-FAN maintenance.
Best use case
atft-autonomy is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Coordinate Claude Code skills with OpenAI Codex autonomous workflows for end-to-end ATFT-GAT-FAN maintenance.
Teams using atft-autonomy should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/atft-autonomy/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How atft-autonomy Compares
| Feature / Agent | atft-autonomy | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Coordinate Claude Code skills with OpenAI Codex autonomous workflows for end-to-end ATFT-GAT-FAN maintenance.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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.
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