7b457aa27d
* feat(agent): pure orchestrator pattern with per-skill delegation tools (#478) Refactors the main agent from a direct tool-calling model to a pure orchestrator that delegates all work through dynamically generated tools. Architecture changes: - Orchestrator only sees generated tools (notion, gmail, research, run_code, review_code, plan, spawn_subagent) — skill tools are architecturally unreachable from the main agent - Each installed skill auto-generates a delegation tool at build time (SkillDelegationTool) that routes to skills_agent with the correct skill_filter - Static archetype tools (research, run_code, etc.) delegate to their respective sub-agents - visible_tool_specs filters the function-calling schema sent to the provider, enforcing the orchestrator boundary at the API level Prompt changes: - Rewrote AGENTS.md as a lean orchestrator prompt — no more routing tables or agent_id instructions - Orchestrator skips TOOLS.md, MEMORY.md, HEARTBEAT.md (~6k tokens saved per turn) — subagents get tool specs from the registry - Workspace .md files auto-sync via builtin-hash mechanism so prompt updates ship automatically to existing installs Bug fixes: - ModelSpec::Hint now resolves to {hint}-v1 (e.g. agentic-v1) instead of hint:agentic which the backend rejected - validate_skill_filter now uses skill_id from the engine tuple instead of splitting on __ in the raw tool name (which always failed) - Memory context forwarded to subagents via ParentExecutionContext Observability: - Added [agent] tagged logs for tool responses, agent state transitions, and delegation decisions throughout turn.rs See docs/agent-prompt-architecture.excalidraw for the visual diagram. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: rustfmt orchestrator_tools.rs Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: cargo fmt Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: address CodeRabbit review — dispatch guard, fork specs, decouple sync - Enforce visible-tool allowlist at dispatch time (not just schema) - Fork mode uses visible_tool_specs (not full registry) - De-duplicate spawn_subagent when extending orchestrator tools - Raw tool output moved to debug level, info level logs metadata only - Decouple workspace file sync from prompt rendering so skipped files still get synced to disk Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
OpenHuman
The age of super intelligence is here. OpenHuman is your Personal AI super intelligence. Private, Simple and extremely powerful.
Discord • Reddit • X/Twitter • Docs
"The Tet. What a brilliant machine" — Morgan Freeman as he reminisces about alien superintelligence in the movie Oblivion
Early Beta — Under active development. Expect rough edges.
To install or get started, either download from the website over at tinyhumans.ai/openhuman or run
# For MacOS/Linux
curl -fsSL https://raw.githubusercontent.com/tinyhumansai/openhuman/main/scripts/install.sh | bash
# For Windows
irm https://raw.githubusercontent.com/tinyhumansai/openhuman/main/scripts/install.ps1 | iex
What is OpenHuman?
OpenHuman is an open-source agentic assistant that is designed to integrate with you in your daily life. Here's what makes OpenHuman special:
-
Simple, UI-first — A clean desktop experience and short onboarding paths so you can go from install to a working agent in a few clicks, without a config-first setup. You don't need a terminal to run OpenHuman.
-
One subscription, many providers — You only need one account to get access to many agentic APIs (AI Models, Search, Webhooks/Tunnels and other 3rd party APIs etc..), simplifying the experience to get a powerful agent going.
-
Rich Skills — Plug into Gmail, Slack, Notion, and the rest of your stack via rich, feature-backed skills. Connections are typically one click through setup wizards instead of wiring APIs by hand. Workflow data is kept on device, encrypted locally, and treated as yours: encryption and sensitive context stay on your machine. Webhooks give instant feedback into the agent when external systems or skills emit events, so the loop stays tight without constant polling.
-
Local knowledge base — Built from your data and your activity. How you work across tools, sessions, and connected services—so the agent gets rich, workflow-aware context, not a one-off chat transcript. Everything is stored on your machine and compounding over time without becoming a cloud dossier. Channels, skills and ongoing conversations feed the same loop so day-to-day context does not reset every session.
-
Local AI model — The Rust core exposes local AI paths (and the desktop bundle can ship local/bundled runners where applicable) for the workloads above—vision snippets, speech helpers, summarization, tooling—so sensitive steps can stay off the cloud when you choose.
-
Deep desktop integrations — OpenHuman is a native desktop assistant, not a web-only chat: memory-aware keyboard autocomplete, voice (STT listening and TTS replies), screen intelligence that understands what is on screen and feeds your local context, plus windowing and OS-level permissions—so the agent meets you on the machine, not trapped in a browser tab.
Architecture: docs/ARCHITECTURE.md. Contributor orientation: CONTRIBUTING.md.
OpenHuman vs other agents
High-level comparison (products evolve—verify against each vendor). OpenHuman is built to minimize vendor sprawl, keep workflow knowledge on-device, and ship deep desktop features—not only chat.
| Claude Code/Cowork | OpenClaw | Hermes Agent | OpenHuman | |
|---|---|---|---|---|
| Open-source: Is the codebase open to review? | 🚫 Proprietary client | ✅ MIT License | ✅ MIT License | ✅ GNU License |
| Simple: Is it simple to get started? | ✅ Simple Desktop App + CLI | ⚠️ Terminal first and often complex | ⚠️ Terminal first and often complex | ✅ Simple, Clean UI/UX. Get started within minutes |
| Cost: How expensive is to run? | ⚠️ Subscription + add-on tool/API costs | ⚠️ Tied to models & hosting you choose | ⚠️ Tied to models & hosting you choose | ✅ Cost optimized with the option to run many things locally for free |
| Memory & Knowledge Base (KB): Does the agent know you and your world? | ✅ Built-in memory; mostly chat/session scoped | ⚠️ Has a local memory but often needs plugins for richer behavior | ✅ Self-learning / task loops (typical) | 🚀 Local KB + Self-learning from your activity & data (GMail, Notion etc... via skills) & prompts |
| API spagetti: How complex is it to hook mulitple features together? | 🚫 Claude bill + often extra keys for MCP/tools | 🚫 BYOK / multi-vendor common | 🚫 Multiple providers common | ✅ One account get access to many bundled platform APIs |
| Extensibility: Can you add rich features into it? | ✅ MCP (different model than sandboxed skills) | ✅ Plugin Architecture (SKILL.md) | ✅ Plugin Architecture (SKILL.md) | 🚀 Rich Skills with ability to have realtime updates, local DB & more |
| Desktop integrations: Can it integrate into your desktop completely? | ⚠️ Desktop app & access to folders | ⚠️ Often lighter native surface | ⚠️ Often lighter native surface | ✅ STT, TTS, screen intelligence, memory-aware autocomplete and a whole lot more |
Contributors Hall of Fame
Show some love and end up in the hall of fame