ec1352f059
## Summary - Adds a fast-fail path when `composio_list_tools` ends up empty for requested or connected toolkits that do not have curated OpenHuman agent catalogs. - Returns a clear unsupported-toolkit error instead of a successful empty `tools` response for uncurated scopes such as OneDrive, Excel, or Todoist. - Keeps existing behavior for catalogued toolkits and direct-mode empty responses. - Adds focused unit coverage for toolkit normalization and unsupported-toolkit messaging. ## Problem - Some toolkits can be connected in the UI but do not have curated OpenHuman agent tool catalogs yet. - When the agent asks `composio_list_tools` for those toolkits, it can receive an empty usable tool list and continue trying until max iterations. - Users then see a generic agent failure instead of a direct explanation that the connected toolkit is not agent-ready. ## Solution - Track the explicit `toolkits` filter, or the active connected toolkits when filtering to connected accounts. - If the final `tools` list is empty and the scoped toolkit set includes uncatalogued toolkits, return a `ToolResult::error` with a concrete agent-ready support message. - Leave catalog creation and UI preview/coming-soon badges as follow-up slices so this PR stays small. ## Submission Checklist - [x] Tests added or updated (happy path + at least one failure / edge case) per [Testing Strategy](../gitbooks/developing/testing-strategy.md#failure-path-requirement) - [x] **Diff coverage ≥ 80%** — local coverage run is blocked by missing libclang; CI coverage gate will verify changed lines. - [x] Coverage matrix updated — N/A: behavior-only Composio tool failure path, no feature row added/removed/renamed. - [x] All affected feature IDs from the matrix are listed in the PR description under `## Related` — N/A: no matrix feature ID changed. - [x] No new external network dependencies introduced (mock backend used per [Testing Strategy](../gitbooks/developing/testing-strategy.md#mock-policy)) - [x] Manual smoke checklist updated if this touches release-cut surfaces ([`docs/RELEASE-MANUAL-SMOKE.md`](../docs/RELEASE-MANUAL-SMOKE.md)) — N/A: no release smoke checklist surface changed. - [x] Linked issue closed via `Closes #NNN` in the `## Related` section — N/A: partial fix for #2283; catalog/UI work remains. ## Impact - Runtime: Composio agent tool discovery. - User-visible: the agent gets a direct unsupported-toolkit message instead of looping on an empty action list. - Compatibility: catalogued toolkits still return tools as before; direct mode still returns success+empty by design. ## Related - Refs #2283 - Follow-up PR(s)/TODOs: add curated catalogs for OneDrive/Excel/Todoist; add UI preview/agent-coming-soon labeling for uncatalogued connected toolkits. --- ## AI Authored PR Metadata (required for Codex/Linear PRs) ### Linear Issue - Key: N/A - URL: N/A ### Commit & Branch - Branch: `codex/2283-uncurated-toolkit-fast-fail` - Commit SHA: `d299c8ae92c690b911647f22746372572f17ff60` ### Validation Run - [x] `pnpm --filter openhuman-app format:check` — N/A: no frontend changes. - [x] `pnpm typecheck` — N/A: no TypeScript changes. - [x] Focused tests: blocked locally; see Validation Blocked. - [x] Rust fmt/check (if changed): `cargo fmt --check` passed. - [x] Tauri fmt/check (if changed): N/A: no Tauri shell changes. ### Validation Blocked - `command:` `cargo test --lib empty_uncurated_toolkits_message --manifest-path Cargo.toml` - `error:` `whisper-rs-sys` build script could not find `clang.dll` / `libclang.dll`; `LIBCLANG_PATH` is unset in this Windows environment. - `impact:` focused Rust tests could not run locally, but the helper tests are included for CI. ### Behavior Changes - Intended behavior change: empty `composio_list_tools` results for uncatalogued requested/connected toolkits now fail fast with a useful message. - User-visible effect: the agent should stop burning through max iterations when a connected toolkit is not yet agent-ready. ### Parity Contract - Legacy behavior preserved: catalogued toolkits, scope filtering, connection filtering, and direct-mode short-circuit behavior are unchanged. - Guard/fallback/dispatch parity checks: unit tests cover requested toolkit normalization, uncatalogued toolkit messaging, and catalogued toolkit no-op behavior. ### Duplicate / Superseded PR Handling - Duplicate PR(s): none found for #2283 at PR creation time. - Canonical PR: this PR for the fast-fail slice only. - Resolution (closed/superseded/updated): N/A <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Bug Fixes** * Improved toolkit filtering so empty results now return clear, user-facing guidance when selected toolkits lack curated agent tools, including which toolkits are affected. * **Tests** * Added unit tests to validate normalized toolkit filtering and the new uncatalogued-toolkit messaging behavior, including provider-backed cases. <!-- review_stack_entry_start --> [](https://app.coderabbit.ai/change-stack/tinyhumansai/openhuman/pull/2293?utm_source=github_walkthrough&utm_medium=github&utm_campaign=change_stack) <!-- review_stack_entry_end --> <!-- end of auto-generated comment: release notes by coderabbit.ai --> Co-authored-by: aqilaziz <gonzes7@gmail.com> Co-authored-by: Steven Enamakel <enamakel@tinyhumans.ai>
OpenHuman
OpenHuman is your Personal AI super intelligence. Private, Simple and extremely powerful.
Discord • Reddit • X/Twitter • Docs • Follow @senamakel (Creator)
🇺🇸 English | 🇨🇳 简体中文 | 🇯🇵 日本語 | 🇰🇷 한국어 | 🇩🇪 Deutsch
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
# Download DMG, EXEs over at https://tinyhumans.ai/openhuman or run in from your terminal
# For macOS or Linux x64
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 designed to integrate with you in your daily life. Each bullet links to the deeper writeup in the docs.
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Simple, UI-first & Human A clean desktop experience and short onboarding paths take you from install to a working agent in a few clicks — no config-first setup, no terminal required. The agent has a face: a desktop mascot that speaks, reacts to its surroundings, joins your Google Meets as a real participant, remembers you across weeks, and keeps thinking in the background even when you've stopped typing.
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118+ third-party integrations with auto-fetch: plug into Gmail, Notion, GitHub, Slack, Stripe, Calendar, Drive, Linear, Jira and the rest of your stack with one-click OAuth. Every connection is exposed to the agent as a typed tool, and every twenty minutes the core walks each active connection and pulls fresh data into the memory tree. No prompts, no polling loops you have to write, so the agent already has tomorrow's context this morning.
Managed integrations are backend-proxied through OpenHuman's Composio connector layer. If you want to run Composio directly instead of using the managed backend path, configure direct mode with your own Composio API key; real-time trigger webhooks then need to be hosted and wired by you.
-
Memory Tree + Obsidian Wiki: a local-first knowledge base built from your data and your activity. Everything you connect is canonicalized into ≤3k-token Markdown chunks, scored, and folded into hierarchical summary trees stored in SQLite on your machine. The same chunks land as
.mdfiles in an Obsidian-compatible vault you can open, browse and edit, inspired by Karpathy's obsidian-wiki workflow. -
Batteries included: web search, a web-fetch scraper, a full coder toolset (filesystem, git, lint, test, grep), and native voice (STT in, ElevenLabs TTS out, mascot lip-sync, live Google Meet agent) are wired in by default. Model routing sends each task to the right LLM (reasoning, fast, or vision) under one subscription. No "install a plugin to read files" friction. Optional local AI via Ollama for on-device workloads.
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Smart token compression (TokenJuice): every tool call, scrape result, email body, and search payload is run through a token compression layer before it touches any LLM Model. HTML is converted to Markdown, long URLs are shortened, and verbose tool output is deduped and summarized via a configurable rule overlay etc... CJK, emoji, and other multi-byte text are preserved grapheme-by-grapheme — never stripped. You get the same information but at a fraction of the tokens. Reducing cost & latency by up to 80%.
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Messaging channels and privacy & security: inbound/outbound across the channels you already use, with workflow data that stays on device, encrypted locally, treated as yours.
Contributing from source
New contributor? Start with CONTRIBUTING.md for the fork/PR workflow and local validation commands, or use the copy-paste AI-agent prompt in CONTRIBUTING-BEGINNERS.md. The short path is:
- Install Git, Node.js 24+, pnpm 10.10.0, Rust 1.93.0 (
rustfmt+clippy), CMake, Ninja, ripgrep, and the platform desktop build prerequisites. - Fork and clone the repo, then run
git submodule update --init --recursivebeforepnpm installso the vendored Tauri/CEF sources are present. - Use
pnpm devfor web-only UI work,pnpm --filter openhuman-app dev:appfor the desktop shell, and focused checks such aspnpm typecheck,pnpm format:check, andcargo check -p openhuman --libbefore opening a PR.
Deeper docs: Architecture · Getting Set Up · Cloud Deploy.
Context in minutes, not weeks
OpenHuman is the first agent harness that gets to know you in minutes. Inspired by Karpathy's LLM Knowledgebase. Most agents start cold. Hermes learns by watching you work; OpenClaw waits for plugins to ferry context in. Either way, you spend days or weeks before the agent knows enough about your stack to be genuinely useful.
OpenHuman summarizes and compresses all your documents, emails & chats; and creates a memory graph that lets your agent remember everything about you.
OpenHuman skips the wait. Connect your accounts, let auto-fetch pull data locally on a 20-minute loop, and then have Memory Trees compress everything into Markdown files stored intelligently in a Karpathy-style Obsidian wiki.
In just one sync pass, the agent has full (compressed) context of your inbox, your calendar, your repos, your docs, your messages. No training period. No "give it a few weeks.". It becomes you, controlled by you.
Already self-host agentmemory across other coding agents? OpenHuman ships an optional Memory backend that proxies to it — set memory.backend = "agentmemory" in config.toml and the same durable store powers OpenHuman alongside Claude Code, Cursor, Codex, and OpenCode. See the agentmemory backend page for setup.
OpenHuman vs Other Agent Harnesses
High-level comparison (products evolve, so verify against each vendor). OpenHuman is built to minimize vendor sprawl, keep workflow knowledge on-device, and give the agent a persistent memory of your data, not only chat.
| Claude Cowork | OpenClaw | Hermes Agent | OpenHuman | |
|---|---|---|---|---|
| Open-source | 🚫 Proprietary | ✅ MIT | ✅ MIT | ✅ GNU |
| Simple to start | ✅ Desktop + CLI | ⚠️ Terminal-first | ⚠️ Terminal-first | ✅ Clean UI, minutes |
| Cost | ⚠️ Sub + add-ons | ⚠️ BYO models | ⚠️ BYO models | ✅ One sub + TokenJuice |
| Memory | ✅ Chat-scoped | ⚠️ Plugin-reliant | ✅ Self-learning | 🚀 Memory Tree + Obsidian vault, optional agentmemory backend |
| Integrations | ⚠️ Few connectors | ⚠️ BYO | ⚠️ BYO | 🚀 118+ via OAuth |
| Auto-fetch | 🚫 None | 🚫 None | 🚫 None | ✅ 20-min sync into memory |
| API sprawl | 🚫 Extra keys | 🚫 BYOK | 🚫 Multi-vendor | ✅ One account |
| Model routing | 🚫 Single model | ⚠️ Manual | ⚠️ Manual | ✅ Built-in |
| Native tools | ✅ Code-only | ✅ Code-only | ✅ Code-only | ✅ Code + search + scraper + voice |
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