41 lines
1.7 KiB
Markdown
41 lines
1.7 KiB
Markdown
# TODO
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## Done
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- [x] Firecracker CLI runner with snapshots (~1.1s)
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- [x] Multi-agent system — overseer + agent VMs + IRC + Ollama
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- [x] 5 templates, 5+ models, hot-reload, non-root agents
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- [x] Tools: run_command, web_search, fetch_url, save_memory
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- [x] Discoverable skill system — SKILL.md + run.py, auto-loaded
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- [x] Persistent workspace + memory (MEMORY.md pattern)
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- [x] Overseer: !invoke, !destroy, !list, !model, !models, !templates, !persona, !status, !help
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- [x] Health checks, crash recovery, graceful shutdown, systemd
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- [x] Network policies, thread safety, trigger fix, race condition fix
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- [x] Install/uninstall scripts, deployed on 2 machines
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- [x] Refactor: firecracker-vm.ts shared helpers, skill extraction
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## Next up (Phase 5 — by priority)
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### Quick wins
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- [ ] Large output handling — save >2K results to file, preview + read_file
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- [ ] Iteration budget — configurable max rounds per template, prevent runaway loops
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### Medium effort
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- [ ] Skill registry git repo — shared skills on Gitea, `fireclaw skills pull`
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- [ ] Session persistence — SQLite + FTS5 in workspace
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- [ ] Context compression — summarize old turns when context gets long
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- [ ] !logs — tail agent history from workspace
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### Bigger items
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- [ ] Skill learning — agents create new skills from experience
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- [ ] Cron agents — scheduled agent spawns
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- [ ] Dangerous command approval — pattern detection + allowlist
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- [ ] Parallel tool execution — concurrent independent tool calls
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## Polish
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- [ ] Agent-to-agent response quality — 7B models parrot, needs better prompting or larger models
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- [ ] Cost tracking per interaction
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- [ ] Execution recording / audit trail
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- [ ] Update regression tests for skill system + channel layout
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