## Summary - Adds shared `waitForTestId` and `clickTestId` E2E helpers for stable DOM hooks. - Adds missing `cron-jobs-panel` and `cron-refresh` hooks to the Cron Jobs settings panel. - Migrates the reference cron E2E flow away from Tailwind class/DOM walking to cron row/action test IDs. - Documents the E2E `data-testid` naming taxonomy in the E2E guide. ## Problem - #1861 calls out `cron-jobs-flow.spec.ts` as the concrete example of brittle selectors: it found `morning_briefing` via Tailwind class strings and `closest('div.p-4')`. - That breaks on harmless class/layout refactors and makes the reference spec a weak template for future E2E work. ## Solution - Use existing `CoreJobList` cron row/action hooks directly from the spec. - Add the missing panel/refresh hooks so the whole cron flow can avoid text/button discovery for row actions. - Centralize test ID waiting/clicking in `element-helpers.ts` instead of keeping local DOM snippets in specs. ## 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) - updated the reference cron E2E spec and helper path. - [x] **Diff coverage >= 80%** - N/A locally: E2E helper/spec/doc change; CI diff coverage is authoritative. - [x] Coverage matrix updated - N/A: E2E selector-hardening change, 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 applies. - [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-cut surface. - [x] Linked issue closed via `Closes #NNN` in the `## Related` section - N/A: this is a scoped slice that references #1861 without closing the broader audit issue. ## Impact - Runtime impact: none outside stable `data-testid` attributes on the Cron Jobs panel. - Test impact: cron E2E is less coupled to Tailwind classes and container structure. - Compatibility: `waitForTestId` is documented as tauri-driver/DOM-backed; Mac2 specs should keep accessibility/text helpers unless IDs are mirrored into accessible labels. ## Related - Refs #1861 - Follow-up PR(s)/TODOs: add stable hooks/migrations for the remaining settings, skills, conversation, onboarding, and notification E2E surfaces tracked by #1861. --- ## AI Authored PR Metadata (required for Codex/Linear PRs) ### Linear Issue - Key: N/A - URL: N/A ### Commit & Branch - Branch: `codex/1861-cron-e2e-testids` - Commit SHA: `28eca40a3d2e3a75b61105887e4faf58d4c0866e` ### Validation Run - [x] `pnpm --filter openhuman-app exec prettier --check src/components/settings/panels/CronJobsPanel.tsx test/e2e/helpers/element-helpers.ts test/e2e/specs/cron-jobs-flow.spec.ts` - passed - [x] `pnpm typecheck` - passed - [x] Focused tests: N/A, E2E spec migration not run locally - [x] Rust fmt/check (if changed): `cargo fmt --all --check` - passed; `git diff --check` - passed - [x] Tauri fmt/check (if changed): N/A ### Validation Blocked - `command:` `pnpm --filter openhuman-app exec tsc -p test/tsconfig.e2e.json --noEmit` - `error:` local command could not find `tsc` / `@wdio/globals/types` via that invocation - `impact:` app-wide `pnpm typecheck` passes; remote E2E/TS jobs remain authoritative for the E2E tsconfig ### Behavior Changes - Intended behavior change: none for users; E2E selectors now target stable hooks. - User-visible effect: none. ### Parity Contract - Legacy behavior preserved: cron load, refresh, pause/resume, run-history, and remove behavior unchanged. - Guard/fallback/dispatch parity checks: spec still asserts the same UI and sidecar persistence behavior. ### Duplicate / Superseded PR Handling - Duplicate PR(s): N/A - Canonical PR: this PR - Resolution (closed/superseded/updated): N/A <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Tests** * Added E2E helpers and updated cron-jobs flow to use stable test identifiers for more reliable UI interactions and polling. * **Documentation** * Added guidance on stable test ID naming and how to use the new E2E helpers in the testing guide. * **Maintenance** * Cron Jobs panel and controls now expose stable identifiers for testing (no user-facing behavior changes). <!-- review_stack_entry_start --> [](https://app.coderabbit.ai/change-stack/tinyhumansai/openhuman/pull/2301?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.
-
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.
-
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%.
-
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 |
Star us on GitHub
Building toward AGI and artificial consciousness? Star the repo and help others find the path.
Contributors Hall of Fame
Show some love and end up in the hall of fame. Contributors get free merch and special access to our Discord.

