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...
โฌ 0 downloads โ
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- 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
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.2.0
Provenance
- Publisher
- oabdelmaksoud
- Source page
- View original listing
- Canonical URL
- Open canonical page
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