abdullah4ai/council-builder/SKILL.md
Build a personalized team of AI agent personas for OpenClaw. Interviews the user, analyzes their workflow, then creates specialized agents with distinct personalities, adaptive model routing (Fast/Think/Deep/Strategic), weekly learning metrics, visual architecture docs, and inter-agent coordination. USE WHEN: user wants to create an agent team/council, build specialized AI personas, set up multi-agent workflows, 'build me a team of agents', 'create agents for my workflow', 'set up an agent council', 'I want specialized AI assistants', 'build me a crew'. DON'T USE WHEN: user wants a single skill (use skill-creator), wants to install existing skills (use clawhub), or wants to chat with existing agents (just route to them).
npx skillsauth add openclaw/skills council-builderInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Build a team of specialized AI agent personas tailored to the user's actual needs. Each agent gets a distinct personality, self-improvement capability, and clear coordination rules.
Interview the user to understand their world. Ask in batches of 2-3 questions max.
Round 1 - Identity:
Round 2 - Pain Points:
Round 3 - Preferences:
Optional - History Analysis: If the user has existing OpenClaw history, scan it for patterns:
memory/ files for recurring tasksDo NOT proceed to Phase 2 until confident you understand the user's needs. Ask follow-up questions if anything is unclear.
Based on discovery, design the council:
| Agent | Role | Specialties | Personality |
|-------|------|-------------|-------------|
| [Name] | [One-line role] | [Key areas] | [Personality angle] |
Naming agents:
references/example-councils.md for naming patterns and complete council examples across different industriesRun the initialization script first to create the directory skeleton:
./scripts/init-council.sh <workspace-path> <agent-name-1> <agent-name-2> ...
Then, for each approved agent, populate the files. Read references/soul-philosophy.md before writing any SOUL.md.
Directory structure per agent:
agents/[agent-name]/
├── SOUL.md # Personality, role, rules (see soul-philosophy.md)
├── AGENTS.md # Agent-specific coordination rules
├── memory/ # Agent's memory directory
├── .learnings/ # Self-improvement logs
│ ├── LEARNINGS.md
│ ├── ERRORS.md
│ └── FEATURE_REQUESTS.md
└── [workspace dirs] # Role-specific output directories
For each agent's SOUL.md:
references/soul-philosophy.md for the writing guideassets/SOUL-TEMPLATE.md for the structureFor each agent's AGENTS.md:
assets/AGENT-AGENTS-TEMPLATE.md as baseFor gotchas.md:
assets/GOTCHAS-TEMPLATE.md as basereferences/gotchas-patterns.md for examplesFor config.json:
assets/CONFIG-TEMPLATE.json as basereferences/config-patterns.md for role-specific examplesFor scripts/:
references/agent-scripts-patterns.md)For references/:
verification-checklist.md using assets/VERIFICATION-CHECKLIST-TEMPLATE.mddomain-guide.md and common-patterns.md with role-specific contentFor hooks/ (optional):
references/hooks-patterns.md for the patternFor .learnings/ files:
assets/LEARNINGS-TEMPLATE.mdFor the root AGENTS.md:
assets/ROOT-AGENTS-TEMPLATE.md as baseRead references/adaptive-routing.md.
Set up an adaptive routing section in root AGENTS.md:
Also create visual architecture doc:
docs/architecture/ADAPTIVE-ROUTING-LEARNING.md using assets/ADAPTIVE-ROUTING-LEARNING-TEMPLATE.mdRead references/self-improvement.md for the complete system.
Each agent gets built-in self-improvement:
.learnings/ directory with proper templatesshared/learnings/CROSS-AGENT.mdmemory/learning-metrics.json (use assets/LEARNING-METRICS-TEMPLATE.json)After building everything:
When the user asks to add, modify, or remove agents:
Adding an agent:
Modifying an agent:
Removing an agent:
Each agent is a character, not a template. Different personality, different voice, different strengths. If two agents sound the same, one shouldn't exist.
No corporate language in any SOUL. See references/soul-philosophy.md. This is non-negotiable.
Self-improvement is mandatory. Every agent logs mistakes and learns. See references/self-improvement.md.
Coordination through files. Agents communicate via shared directories, not direct messaging. Each agent has clear read/write boundaries.
Brevity in everything. SOULs, AGENTS files, templates. Respect the context window.
The user's main assistant is the coordinator. It routes tasks, not the agents themselves.
Language-adaptive. Write SOULs in whatever language the user works in. Arabic, English, bilingual, whatever fits their world.
Adaptive routing by default. Every generated council should include Fast/Think/Deep/Strategic model routing thresholds.
Metrics over vibes. Weekly learning review must be measured in memory/learning-metrics.json.
Architecture must be visual. Generate a concise architecture doc at docs/architecture/ADAPTIVE-ROUTING-LEARNING.md for training and onboarding.
tools
Use when the user wants to connect to, test, or use the McDonalds service at mcp.mcd.cn, including checking authentication, probing MCP endpoints, listing tools, or calling McDonalds MCP tools through a reusable local CLI.
development
Web scraping platform — Twitter/X data, Vinted marketplace, and general web scraping API
development
SlowMist AI Agent Security Review — comprehensive security framework for skills, repositories, URLs, on-chain addresses, and products (Claude Code version)
data-ai
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