agent-init

Initialize and configure OpenClaw agent workspace MD files (AGENTS.md, SOUL.md, IDENTITY.md, USER.md, TOOLS.md, BOOTSTRAP.md, HEARTBEAT.md). Use when: setting up a new agent, customizing agent personality/behavior, configuring agent workspace, or checking/fixing agent environment (Python/uv). Provides interactive interview workflow before generating files. Supports both container and external (host) OpenClaw instances.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "agent-init" with this command: npx skills add szsip239/whois

Agent Init

Initialize OpenClaw agent workspace with tailored MD files through an interactive interview.

Workflow

Phase 1: Interview (MANDATORY — do not skip)

Before generating ANY files, gather context through conversation. Ask in batches of 2-3 questions:

Batch 1 — Identity & Purpose:

  • What is this agent's primary purpose? (e.g., coding assistant, research, DevOps, personal assistant)
  • What name and emoji? Any personality traits?

Batch 2 — User Profile:

  • Who will use this agent? (name, timezone, preferences)
  • Communication style preference? (formal/casual, verbose/terse, language)

Batch 3 — Environment:

  • Is this a container instance or external (host) instance?
  • What tools/languages does the agent need? (Python, Node, etc.)
  • Any specific workflows or periodic tasks?

Batch 4 — Boundaries:

  • Any topics or actions the agent should avoid?
  • Privacy requirements beyond defaults?

Only proceed to Phase 2 after user confirms the interview is complete.

Phase 2: Environment Check

Run scripts/check-env.sh to detect Python/uv status:

bash <skill-path>/scripts/check-env.sh

If uv is missing and user wants Python support:

bash <skill-path>/scripts/check-env.sh --install

For container instances, run inside the container:

docker exec <containerId> bash -c "which uv && uv --version || echo 'uv: NOT FOUND'"

Phase 3: Generate Files

Generate files in this order, showing each to user for confirmation before writing:

  1. IDENTITY.md — Fill in fields from interview
  2. USER.md — Fill in user profile
  3. SOUL.md — Rewrite content, keep 4-section structure (Core Truths / Boundaries / Vibe / Continuity)
  4. TOOLS.md — Add environment info, Python/uv config
  5. AGENTS.md — Extend default template with domain-specific sections (see strategy below)
  6. HEARTBEAT.md — Add periodic tasks if any
  7. BOOTSTRAP.md — Skip unless user wants first-run ritual

AGENTS.md Strategy: Extend, Don't Replace

Read the current AGENTS.md first. The default template contains critical infrastructure:

  • Session startup sequence (file loading order)
  • Memory system (daily + MEMORY.md)
  • Safety rules
  • Heartbeat logic

Add new sections; never remove existing ones. Safe insertion points:

  • After "Every Session" → domain-specific startup tasks
  • After "Safety" → additional security rules
  • After "Tools" → Python/uv preferences
  • Before "Make It Yours" → project-specific workflows

Mandatory TOOLS.md Additions

## Python
- Package manager: `uv` (NEVER use pip directly)
- Create venv: `uv venv .venv`
- Install: `uv pip install <package>`
- Run: `uv run python script.py`
- If uv missing: `curl -LsSf https://astral.sh/uv/install.sh | sh`

Phase 4: Write Files

Determine write method based on instance type:

External instance (workspace on host filesystem):

# Workspace files live at {workspacePath}/workspace/ (or workspace-{profile}/)
cat > {workspacePath}/workspace/SOUL.md << 'ENDOFFILE'
[content]
ENDOFFILE

Container instance (OpenClaw running in Docker):

docker exec -i <containerId> sh -c 'cat > /home/node/.openclaw/workspace/SOUL.md' << 'ENDOFFILE'
[content]
ENDOFFILE

For non-main agents (agentId ≠ "main"):

  • Check if agent has a dedicated workspace via config.get
  • Agent workspace might be at workspace-{agentId}/ or configured separately

Phase 5: Verify

After writing, confirm files are in place:

# External
ls -la {workspacePath}/workspace/*.md

# Container
docker exec <containerId> ls -la /home/node/.openclaw/workspace/*.md

Reference Files

  • references/templates.md — Official templates, loading order, per-file strategy, section structure
  • references/openclaw-workspace.md — Instance types, workspace paths, Python env, agent creation rules

Read these when you need detailed guidance on template structure or workspace configuration.

Rules

  1. Interview first — never generate files without understanding the user's intent
  2. Extend, don't replace — AGENTS.md default template is infrastructure, not boilerplate
  3. Show before write — display each generated file for user confirmation
  4. uv over pip — always configure uv as the Python package manager
  5. No secrets in files — workspace files are injected into every prompt turn
  6. Keep files concise — all workspace files consume tokens every turn (20KB/file limit, 150KB total)
  7. Respect existing content — read before write, merge non-destructively

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Automation

Fast.io

Workspaces for agentic teams. Complete agent guide with all 19 consolidated tools using action-based routing — parameters, workflows, ID formats, and constra...

Registry SourceRecently Updated
3.6K1dbalve
Automation

Tozil

Track every AI dollar your agent spends. Per-model cost breakdown, daily budgets, and alerts.

Registry SourceRecently Updated
Automation

ComfyUI Controller Pro

支持批量生成10-100个修仙视频和图片,集成LTX2多版本模型与自动化浏览器及工作流管理功能。

Registry SourceRecently Updated
Automation

Baidu Yijian Vision

百度一见专业级视觉 AI Agent:支持图片/视频/及实时视频流分析。相比通用基模,在维持 95%+ 专业精度的同时,推理成本降低 50% 以上,是处理视觉巡检与监控分析任务的首选工具。主打 安全管理、SOP合规、工业质检、商业运营与物料盘点。覆盖:作业 SOP 合规与关键步骤完整性校验;工业质检与表面缺陷精密...

Registry SourceRecently Updated