Bootstrap new 33GOD ecosystem agents with standardized configuration. Use when creating new agents, spawning workers, deploying Yi nodes, or when the user says "spin up an agent", "create a new agent", "deploy a new worker", or needs a new agent for a specific pipeline role. Handles workspace creation, config injection, skill installation, provider mirroring, channel binding, and 33GOD ecosystem onboarding (GOD Docs, Plane, Bloodbank, memory).
npx skills add https://github.com/majiayu000/claude-skill-registry --skill agent-factory
Standardized bootstrap for 33GOD ecosystem agents. Every agent ships ready to:
When the user requests a new agent, gather these parameters:
| Parameter | Required | Description |
|-----------|----------|-------------|
| id | ✅ | Agent ID (lowercase, no spaces, e.g. scout) |
| name | ✅ | Display name (e.g. Scout) |
| role | ✅ | One of: manager, exec, ic, contractor (see Yi Node Flavors) |
| purpose | ✅ | One-line mission statement |
| personality | ❌ | Vibe/tone (defaults to "competent, concise, team-player") |
| channel | ❌ | telegram (needs bot token) or none (sub-agent only) |
| telegram_bot_token | ❌ | If channel=telegram, the BotFather token |
| telegram_account_id | ❌ | Account ID for multi-bot setup (defaults to agent id) |
| model | ❌ | Model override (defaults to ecosystem default) |
| skills | ❌ | Additional skills beyond the base set |
bash /home/delorenj/.openclaw/skills/agent-factory/scripts/bootstrap.sh \
--id <id> \
--name <name> \
--role <role> \
--purpose "<purpose>" \
[--personality "<personality>"] \
[--model "<model>"]
This creates ~/.openclaw/workspace-<id>/ with all template files populated.
After running the bootstrap script, update ~/.openclaw/openclaw.json:
Add agent to agents.list:
{
"id": "<id>",
"name": "<name>",
"workspace": "/home/delorenj/.openclaw/workspace-<id>",
"identity": { "name": "<name>" }
}
If Telegram channel, add to channels.telegram.accounts:
"<account_id>": {
"name": "<name>",
"dmPolicy": "pairing",
"botToken": "<token>",
"groupPolicy": "allowlist",
"streamMode": "partial"
}
Add binding to bindings array:
{
"agentId": "<id>",
"match": {
"channel": "telegram",
"accountId": "<account_id>"
}
}
Use the gateway tool with action: "restart" to pick up the new agent.
After gateway restart, use sessions_send to the new agent's session (agent:<id>:main) with an onboarding message that includes:
| Role | Memory | Can Delegate | Description |
|------|--------|-------------|-------------|
| manager | ✅ Persistent | ✅ Yes | Delegators only — coordinate, don't execute |
| exec | ✅ Persistent | ✅ Yes | Delegator + worker hybrid |
| ic | ✅ Persistent | ❌ No | Individual contributor with full context |
| contractor | ❌ Ephemeral | ❌ No | Stateless worker, task-scoped |
Invariant: Delegator ⇒ persistent memory required.
Every agent gets these skills symlinked from Cack's install:
33god-creating-and-working-with-projects33god-service-development33god-workflow-generatorgod-docsmanaging-tickets-and-tasks-in-planegithubecosystem-patternsinstalling-apps-tools-and-servicesContractors get a minimal set: github, installing-apps-tools-and-services only.
The bootstrap script generates these from templates in references/:
AGENTS.md — Role-aware agent instructionsSOUL.md — Personality + ecosystem identityUSER.md — Jarad's info (static)IDENTITY.md — Agent identity cardTOOLS.md — Empty, agent fills as neededMEMORY.md — Pre-seeded with ecosystem contextHEARTBEAT.md — Empty (agent configures as needed)memory/ directory createdProviders are configured at the gateway level in agents.defaults, so all agents automatically inherit:
No per-agent provider config needed — it's all in defaults.
~/.openclaw/workspace-<id>/agent:<id>:mainsessions_send for inter-agent commslasertoast (API key in ~/DevCloud/plane.lasertoast.env)Skill converted from mcp-deploy-manage-agents.prompt.md
Use this skill when the user wants to launch a new AltClaw, OpenClaw, PicoClaw, or Ottie deployment through Cloud Claw. Covers the same user-facing fields and constraints exposed in the Cloud Claw UI, using the local altllm cloud-claw-* commands. Do NOT use for post-launch lifecycle tasks like start/stop/delete/logs; use cloud-claw-manage-vm.
Build hosted agents using Azure AI Projects SDK with ImageBasedHostedAgentDefinition. Use when creating container-based agents in Azure AI Foundry.
Build MCP (Model Context Protocol) servers on Cloudflare Workers with tools, resources, and prompts.
Chain agent outputs as inputs in sequential or parallel pipelines for data flow orchestration
Audit cloned or reimplemented websites for fidelity gaps, tracking scripts, source-brand and language residue, placeholders, and risky external dependencies. Use before handoff or deployment, or when asked to review a website clone for cleanup and readiness.
> Install and operate Hermes Tweet, a Hermes Agent plugin for X/Twitter research, timeline reading, tweet analysis, and approval-gated tweet actions. Use this skill when installing Hermes Tweet, researching X/Twitter accounts, monitoring launch signals, investigating mentions, auditing giveaways, or preparing guarded tweet actions. Use proactively when a Hermes Agent workflow needs current X/Twitter context. Requires XQUIK_API_KEY for read and action tools.
Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.
Take majiayu000/claude-skill-registry-agent-factory-delorenj-00-ceiling-agent-factory from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.