Bump version to 0.1.2. Update description and polish TODO. Since v0.1.0: - Multi-agent IRC orchestration (overseer + agent VMs) - 5 agent templates, 5 Ollama models - Tool access (shell + podman containers) - Persistent workspace + memory system - Agent hot-reload, non-root agents - Thread safety, health checks, network policies - Trigger matching fix, race condition fix - Graceful shutdown, crash recovery, systemd service - DM support, /invite, agent-to-agent communication Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
39 lines
1.8 KiB
Markdown
39 lines
1.8 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] Alpine rootfs with ca-certificates, podman, python3
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- [x] Global `fireclaw` command
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- [x] Multi-agent system — overseer + agent VMs + IRC + Ollama
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- [x] 5 agent templates (worker, coder, researcher, quick, creative)
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- [x] 5 Ollama models (qwen2.5-coder, qwen2.5, llama3.1, gemma3, phi4-mini)
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- [x] Agent tool access — shell commands + podman containers
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- [x] Persistent workspace + memory system (MEMORY.md pattern)
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- [x] Agent hot-reload — model/persona swap via SSH + SIGHUP
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- [x] Non-root agents — unprivileged `agent` user
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- [x] Agent-to-agent via IRC mentions (10s cooldown)
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- [x] DM support — private messages, no mention needed
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- [x] /invite support — agents auto-join invited channels
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- [x] Channel layout — #control (commands), #agents (common), DMs
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- [x] Overseer resilience — crash recovery, agent adoption
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- [x] Graceful shutdown — IRC QUIT before VM kill
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- [x] Systemd service (KillMode=process)
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- [x] Regression test suite (20 tests)
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## Next up
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- [ ] Network policies per agent — restrict internet access
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- [ ] Warm pool — pre-booted VMs for instant agent spawns
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- [ ] Persistent agent memory improvements — richer memory structure, auto-save from conversations
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- [ ] Thin provisioning — device-mapper snapshots instead of full rootfs copies
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## Polish
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- [ ] Agent-to-agent response quality — small models (7B) parrot messages instead of answering. Needs better prompting ("don't repeat the question, answer it") or larger models (14B+). Claude API would help here.
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- [ ] Cost tracking per agent interaction
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- [ ] Execution recording / audit trail
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- [ ] Agent health checks — overseer pings agents, restarts dead ones
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- [ ] Thread safety in agent.py — lock around IRC socket writes
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- [ ] Update regression tests for new channel layout
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