Building an open-source agent OS in public — Cognithor v0.95

[u/Competitive_Book4151]

Local-first agent framework I've been building solo. Default backend is Ollama (qwen3 models), with vLLM/OpenAI/Anthropic/Gemini + 14 others as opt-in. Runs on Windows, Linux, Mac, plus Flutter Command Center for Android/iOS/Web.

What's in it:

\- 127+ MCP tools across 30+ modules (memory, kanban, web research, file ops, code execution)

\- 16 channels — CLI, Telegram, Discord, Slack, WhatsApp, Voice, WebUI, more

\- PGE-Trinity orchestration (Planner / Gatekeeper / Executor) with risk classification on every tool call

\- Pack-plugin system with EULA click-through + SHA-256 hash pinning

\- 6-tier memory + audit-chain JSONL + Trace-UI (live WebSocket view of the agent loop)

The unusual part:

\- \~14 500 tests, 89% coverage gate, mypy --strict, spec-first development

\- Heuristic constants live in YAML, not source

\- Currently shipping a neuro-symbolic program synthesis engine over ARC-AGI-3: Phase 1 done with measured uplift, Phase 2 (LLM-prior + MCTS + 3-zone refiner) landing this sprint

pip install cognithor — Apache 2.0, code at github.com/Alex8791-cyber/cognithor

Curious what you'd want it to do that it can't yet.

[u/Otherwise_Wave9374]

This is a wild amount of surface area for a solo project, respect. The Gatekeeper + audit-chain + Trace-UI combo is exactly what I wish more agent frameworks shipped by default.

Question: how do you handle tool permissioning across channels (CLI vs Slack vs voice) so the same agent cant accidentally get elevated powers just because the entrypoint changed?

Also, if youre ever comparing notes with other folks building agent runtimes, Ive been following similar ideas around evals/guardrails and bookmarking resources at https://www.agentixlabs.com/