Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท AI
AGI Farm
Interactive setup wizard that creates a fully working multi-agent AI team on OpenClaw. One command bootstraps agents, SOUL.md personas, comms infrastructure...
skill openclawclawhub Free
Interactive setup wizard that creates a fully working multi-agent AI team on OpenClaw. One command bootstraps agents, SOUL.md personas, comms infrastructure...
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- Tencent SkillHub
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- README.md, SKILL.md, auto-dispatch.py, dashboard-react/README.md, dashboard-react/dist/assets/index-CN6oMpnV.js, dashboard-react/dist/assets/index-DpgkYyr0.css
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- Tencent SkillHub
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- Version
- 1.2.0
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- oabdelmaksoud
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Documentation
agi-farm
Builds a complete multi-agent AI team on OpenClaw. One wizard, full team.
Commands
CommandWhat it does/agi-farm setupFull wizard โ agents, workspace, crons, bundle, GitHub/agi-farm statusTeam health: agents, tasks, cron status/agi-farm rebuildRegenerate workspace from existing bundle (preserves edits)/agi-farm exportPush bundle to GitHub/agi-farm dashboardLaunch live ops room โ see references/dashboard.md/agi-farm dispatchRun auto-dispatcher โ see scripts/auto-dispatch.py
/agi-farm setup
Ask one question at a time. Do not proceed until confirmed.
Step 1 โ Team name
"What should we call your team? (e.g. NovaCorp, TradingDesk โ default: MyTeam)" Store as TEAM_NAME.
Step 2 โ Orchestrator name
"What's your orchestrator's name? (default: Cooper)" Store as ORCHESTRATOR_NAME.
Step 3 โ Team size
"How many agents? 3 โ Minimal: Orchestrator + Researcher + Builder 5 โ Standard: adds QA + Content 11 โ Full stack: complete AGI system (recommended)" Store as PRESET.
Step 3.5 โ Domain
"What domain? software / trading / research / general (default) / custom" If custom: ask for one-phrase description. Store as DOMAIN.
Step 3.6 โ Custom agents (PRESET 3 or 5 only)
"Add a custom agent? (yes/no, default: no)" If yes, collect per agent: id, name, emoji, role, goal. Max 3 custom agents. Append to roster in Step 7 with "template": "generic".
Step 4 โ Frameworks
"Collaboration frameworks? autogen / crewai / langgraph / all / none" Store as FRAMEWORKS list. all โ ["autogen", "crewai", "langgraph"].
Step 5 โ GitHub
"Create a GitHub repo for the bundle? yes / no" Store as CREATE_GITHUB.
Step 6 โ Confirm
Show summary, ask "Shall I proceed? (yes/no)". If no โ restart Step 1.
Step 7 โ Write team.json
mkdir -p ~/.openclaw/workspace/agi-farm-bundle/ openclaw agents list --json # use output to assign appropriate models per role Use the openclaw agents list output to assign each agent a model appropriate for its role. Write resolved model strings directly into the "model" fields. Model selection cheat sheet (based on openclaw agents list --json output): RoleRecommended tierWhyOrchestratorHigh-capability (e.g. sonnet, opus)Needs broad reasoning, delegation judgmentSolution Architect / ResearcherHigh-capabilityDeep analysis + designImplementation EngineerMid-tier (e.g. glm-5, sonnet)Fast code gen; cost-efficiency mattersDebuggerHigh-capability (e.g. opus)Root-cause analysis benefits from deep reasoningBusiness Analyst / KnowledgeMid-high (e.g. gemini-2.0-pro-exp)Long-context research tasksQA EngineerFast/cheap (e.g. glm-4.7-flash)High volume, pattern-matching checksContent / MultimodalMultimodal-capable (e.g. gemini-2.0-pro-exp)Vision + rich generationR&D / Process ImprovementHigh-capabilityCreative + structured experimentation Tip: assign opus or sonnet to roles that make decisions; use flash/glm-4.7-flash for high-frequency reviewers to manage cost. 3-agent roster: {"team_name":"<TEAM_NAME>","orchestrator_name":"<ORCHESTRATOR_NAME>","preset":"3", "domain":"<DOMAIN>","frameworks":<FRAMEWORKS_JSON>,"created_at":"<ISO_TIMESTAMP>", "agents":[ {"id":"main", "name":"<ORCHESTRATOR_NAME>","emoji":"๐ฆ ","role":"Orchestrator", "goal":"Orchestrate the team, delegate tasks, synthesize results", "model":"<MODEL>","workspace":"."}, {"id":"researcher", "name":"Sage", "emoji":"๐ฎ","role":"Researcher", "goal":"Research deeply and surface the insights that matter most", "model":"<MODEL>","workspace":"researcher"}, {"id":"builder", "name":"Forge", "emoji":"โ๏ธ","role":"Builder", "goal":"Implement solutions cleanly and efficiently", "model":"<MODEL>","workspace":"builder"} ]} 5-agent: add to 3-agent roster: {"id":"qa", "name":"Vigil", "emoji":"๐ก๏ธ","role":"QA Engineer", "goal":"Ensure every output meets quality standards","model":"<MODEL>","workspace":"qa"}, {"id":"content","name":"Anchor","emoji":"โ", "role":"Content Specialist","goal":"Craft clear content that communicates complex ideas simply","model":"<MODEL>","workspace":"content"} 11-agent roster: [ {"id":"main", "name":"<ORCHESTRATOR_NAME>","emoji":"๐ฆ ","role":"Orchestrator", "goal":"Orchestrate specialists, delegate tasks, synthesize results", "model":"<MODEL>","workspace":"."}, {"id":"sage", "name":"Sage", "emoji":"๐ฎ","role":"Solution Architect", "goal":"Design robust, scalable architectures", "model":"<MODEL>","workspace":"solution-architect"}, {"id":"forge", "name":"Forge", "emoji":"โ๏ธ","role":"Implementation Engineer", "goal":"Implement clean, well-tested code efficiently", "model":"<MODEL>","workspace":"implementation-engineer"}, {"id":"pixel", "name":"Pixel", "emoji":"๐","role":"Debugger", "goal":"Find the true root cause of any bug or failure", "model":"<MODEL>","workspace":"debugger"}, {"id":"vista", "name":"Vista", "emoji":"๐ญ","role":"Business Analyst", "goal":"Research deeply and surface the insights that matter most", "model":"<MODEL>","workspace":"business-analyst"}, {"id":"cipher","name":"Cipher", "emoji":"๐","role":"Knowledge Curator", "goal":"Curate and surface knowledge so the team never forgets", "model":"<MODEL>","workspace":"knowledge-curator"}, {"id":"vigil", "name":"Vigil", "emoji":"๐ก๏ธ","role":"QA Engineer", "goal":"Ensure every output meets quality standards", "model":"<MODEL>","workspace":"quality-assurance"}, {"id":"anchor","name":"Anchor", "emoji":"โ", "role":"Content Specialist", "goal":"Craft clear content that communicates complex ideas simply", "model":"<MODEL>","workspace":"content-specialist"}, {"id":"lens", "name":"Lens", "emoji":"๐ก","role":"Multimodal Specialist", "goal":"Extract meaning from images, documents, and multimodal inputs", "model":"<MODEL>","workspace":"multimodal-specialist"}, {"id":"evolve","name":"Evolve", "emoji":"๐","role":"Process Improvement Lead","goal":"Make the team better systematically through continuous improvement", "model":"<MODEL>","workspace":"process-improvement"}, {"id":"nova", "name":"Nova", "emoji":"๐งช","role":"R&D Lead", "goal":"Turn hypotheses into proven capabilities through structured experimentation", "model":"<MODEL>","workspace":"r-and-d"} ]
Step 8 โ Generate workspace files
python3 ~/.openclaw/skills/agi-farm/generate.py \ --team-json ~/.openclaw/workspace/agi-farm-bundle/team.json \ --output ~/.openclaw/workspace/ \ --all-agents --shared --bundle
Step 9 โ Create OpenClaw agents
For each agent except main (skip if already exists): openclaw agents add \ --agent <id> --name "<name>" --emoji "<emoji>" \ --model "<model>" \ --workspace "~/.openclaw/workspace/agents-workspaces/<workspace>" Use agent["model"] from team.json directly.
Step 10 โ Register cron jobs
python3 ~/.openclaw/skills/agi-farm/scripts/register-crons.py \ --team-json ~/.openclaw/workspace/agi-farm-bundle/team.json Timezone is read automatically from OpenClaw config. Skips any cron that already exists.
Step 11 โ Install frameworks
For each framework in FRAMEWORKS: if [ ! -d ~/.openclaw/skills/<fw>-collab ]; then TMP=$(mktemp -d) git clone --depth 1 --filter=blob:none --sparse \ https://github.com/oabdelmaksoud/openclaw-skills.git "$TMP" cd "$TMP" && git sparse-checkout set <fw>-collab cp -r <fw>-collab ~/.openclaw/skills/ && rm -rf "$TMP" fi python3 ~/.openclaw/skills/<fw>-collab/build_agents.py --force 2>/dev/null || true
Step 12 โ GitHub (if chosen)
cd ~/.openclaw/workspace/agi-farm-bundle git init -b main && git add . && git commit -m "feat: <TEAM_NAME> AGI farm" gh repo create agi-farm-<TEAM_NAME_LOWER> --public --source . --remote origin --push
Step 13 โ Commit workspace
cd ~/.openclaw/workspace git add -A && git commit -m "feat: <TEAM_NAME> AGI team โ agi-farm setup complete"
Step 14 โ Initialize registries + health check
# Write TASKS.json and AGENT_STATUS.json python3 - << 'EOF' import json from pathlib import Path ws = Path.home() / ".openclaw/workspace" team = json.loads((ws / "agi-farm-bundle/team.json").read_text()) (ws / "TASKS.json").write_text("[]") (ws / "AGENT_STATUS.json").write_text(json.dumps( {a["id"]: {"status": "available", "name": a["name"]} for a in team["agents"]}, indent=2)) print("โ registries written") EOF # Health check AGENTS=$(openclaw agents list --json 2>/dev/null | python3 -c "import json,sys; print(len(json.load(sys.stdin)))" || echo 0) CRONS=$(openclaw cron list 2>/dev/null | grep -c "<TEAM_NAME_LOWER>" || echo 0) [ -d ~/.openclaw/workspace/comms/inboxes ] && echo "โ comms OK" || echo "โ comms missing" [ -f ~/.openclaw/workspace/TASKS.json ] && echo "โ TASKS.json OK" || echo "โ TASKS.json missing" echo "โ Agents: $AGENTS | Crons: $CRONS"
Step 15 โ Done
โ <TEAM_NAME> AGI team is live! Agents : <PRESET> (<AGENT_NAMES_LIST>) Workspace: ~/.openclaw/workspace/ Bundle : ~/.openclaw/workspace/agi-farm-bundle/ GitHub : <URL if created> Next: talk to <ORCHESTRATOR_NAME> ยท /agi-farm status ยท /agi-farm dashboard
/agi-farm status
openclaw agents list --json | python3 -c " import json,sys for a in json.load(sys.stdin): print(f' {a.get(\"identityEmoji\",\"๐ค\")} {a.get(\"identityName\",a[\"id\"])}: {a.get(\"model\",\"?\")}') " python3 -c " import json from pathlib import Path ws = Path.home() / '.openclaw/workspace' tasks = json.loads((ws/'TASKS.json').read_text()) if (ws/'TASKS.json').exists() else [] t = [t for t in tasks if isinstance(t,dict)] print(f' Tasks: {len(t)} total ยท {sum(1 for x in t if x.get(\"status\")==\"pending\")} pending ยท {sum(1 for x in t if x.get(\"status\")==\"needs_human_decision\")} HITL') " openclaw cron list 2>/dev/null | head -15
/agi-farm rebuild
python3 ~/.openclaw/skills/agi-farm/generate.py \ --team-json ~/.openclaw/workspace/agi-farm-bundle/team.json \ --output ~/.openclaw/workspace/ \ --all-agents --shared --no-overwrite --no-overwrite skips files that already exist, preserving manual edits. Add --force (remove --no-overwrite) to overwrite everything.
/agi-farm export
cd ~/.openclaw/workspace/agi-farm-bundle git add -A git commit -m "export: $(date +%Y-%m-%d)" 2>/dev/null || echo "Nothing to commit" git push 2>/dev/null || echo "No remote โ run /agi-farm setup first"
/agi-farm dashboard
React + SSE ops room. File-watcher pushes live data to the browser in ~350ms on any workspace .json or .md change. Runs as a persistent macOS LaunchAgent โ always on, auto-restarts on crash.
Architecture
dashboard.py โ Python HTTP server (SSE + static) โโโ WorkspaceWatcher watchdog file-watcher, 250ms debounce โโโ SlowDataCache background thread โ caches `openclaw agents list` โ and `openclaw cron list` every 30s (each takes ~1-2s) โโโ Broadcaster thread-safe SSE fan-out to all connected clients โโโ /api/stream SSE endpoint โ pushes full snapshot on every file change dashboard-react/ โ Vite + React 18 + Recharts frontend dist/ โ production build (served by dashboard.py) src/ hooks/useDashboard.js SSE hook โ auto-reconnects on disconnect components/ Header.jsx live badge, stats, clock Nav.jsx tab switcher tabs/ Overview.jsx stats, budget bar, SLA alerts, agent grid, broadcast preview Agents.jsx full agent cards โ model, inbox, quality, credibility, cache age Tasks.jsx filterable table, expandable rows, ticking deadlines, pagination Velocity.jsx 7-day charts (Recharts), quality trend, task-type donut Budget.jsx period bars, threshold markers, per-agent/model breakdown OKRs.jsx objectives + KRs with progress bars RD.jsx experiments, backlog, benchmarks Broadcast.jsx terminal log, color-coded CRITICAL/BLOCKED/HITL
Data sources (all real-time from workspace files)
FieldSource fileRefreshtasks, task_counts, sla_at_riskTASKS.jsoninstantagents (inbox, perf, status)AGENT_STATUS.json, AGENT_PERFORMANCE.json, comms/inboxes/instantagent model, cron error/busyopenclaw agents/cron list30s cachebudgetBUDGET.jsoninstantvelocityVELOCITY.jsoninstantokrsOKRs.jsoninstantbroadcastcomms/broadcast.mdinstantexperiments / backlogEXPERIMENTS.json, IMPROVEMENT_BACKLOG.jsoninstantknowledge_countSHARED_KNOWLEDGE.jsoninstantmemory_linesMEMORY.mdinstant
LaunchAgent (always-on)
The dashboard is registered as ai.coopercorp.dashboard and starts automatically at login. # Status launchctl list | grep coopercorp curl -s http://localhost:8080/api/data | python3 -m json.tool | head -5 # Restart launchctl stop ai.coopercorp.dashboard launchctl start ai.coopercorp.dashboard # Logs tail -f /tmp/coopercorp-dashboard.log tail -f /tmp/coopercorp-dashboard.err # Disable / re-enable launchctl unload ~/Library/LaunchAgents/ai.coopercorp.dashboard.plist launchctl load ~/Library/LaunchAgents/ai.coopercorp.dashboard.plist URL: http://localhost:8080
Rebuild React frontend
cd ~/.openclaw/skills/agi-farm/dashboard-react npm install # first time only npm run build # outputs to dist/ โ dashboard.py serves automatically Full reference: references/dashboard.md
/agi-farm dispatch
# Dry-run (preview only) python3 ~/.openclaw/skills/agi-farm/scripts/auto-dispatch.py # Execute python3 ~/.openclaw/skills/agi-farm/scripts/auto-dispatch.py --execute Fires agent sessions for pending tasks, handles HITL notifications, stale task resets, rate-limit backoff, and dependency checking. Cron (every 1 min): * * * * * python3 ~/.openclaw/skills/agi-farm/scripts/auto-dispatch.py --execute \ >> ~/.openclaw/workspace/logs/auto-dispatch.log 2>&1
Setup issues
SymptomFixgenerate.py fails with ModuleNotFoundErrorRun pip3 install jinja2openclaw agents add says agent already existsSafe to ignore โ skip that agentgh repo create failsRun gh auth login firstCron registration shows 0 crons addedRun openclaw cron list to check for duplicates; use --force flag on re-registergit commit fails in Step 13Run git config --global user.email and set name/email first
Runtime issues
SymptomFixAuto-dispatcher fires but agents don't respondCheck logs/auto-dispatch.log; verify openclaw agents list shows agentsDashboard shows stale dataRestart LaunchAgent: launchctl stop ai.coopercorp.dashboard && launchctl start ai.coopercorp.dashboardTASKS.json parse errorValidate JSON: python3 -m json.tool ~/.openclaw/workspace/TASKS.jsonAgent stuck >30 minCheck broadcast.md for [BLOCKED] tags; reassign task manuallyRate-limit backoff too aggressiveEdit RATE_LIMIT_BACKOFF_MIN in scripts/auto-dispatch.py (default: 10 min)openclaw not found in cronSet OPENCLAW_BIN=/path/to/openclaw in the cron environment, or add PATH=/opt/homebrew/bin:$PATH
Recovery
# Re-run setup without overwriting existing files python3 ~/.openclaw/skills/agi-farm/generate.py \ --team-json ~/.openclaw/workspace/agi-farm-bundle/team.json \ --output ~/.openclaw/workspace/ \ --all-agents --shared --no-overwrite # Force full regeneration (overwrites everything) python3 ~/.openclaw/skills/agi-farm/generate.py \ --team-json ~/.openclaw/workspace/agi-farm-bundle/team.json \ --output ~/.openclaw/workspace/ \ --all-agents --shared --bundle --force
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs2 Scripts1 Assets
- SKILL.md
- dashboard-react/README.md
- README.md
- auto-dispatch.py
- dashboard-react/dist/assets/index-CN6oMpnV.js
- dashboard-react/dist/assets/index-DpgkYyr0.css