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Openclaw Workspace

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win4r
openclaw-workspace

Use when maintaining or optimizing OpenClaw workspace files — AGENTS.md, TOOLS.md, SOUL.md, USER.md, IDENTITY.md, HEARTBEAT.md, BOOT.md, MEMORY.md, and related checklists and memory files. Covers workspace auditing, token budget analysis, new agent workspace setup from scratch, memory distillation, and cross-file consistency reviews.

Overview

Publisherwin4r
Repositoryopenclaw-workspace
Skill nameopenclaw-workspace
Stars
288
Forks
32
Bundled files
3
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by win4r on GitHub. Read the source before you install it.

Installation

Install the Openclaw Workspace AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/win4r/openclaw-workspace/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/win4r/openclaw-workspace.git \
  .claude/skills/openclaw-workspace
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Openclaw Workspace in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Openclaw Workspace on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Openclaw Workspace is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

OpenClaw Workspace Skill

Overview

OpenClaw workspace files form the agent's "soul and memory" — they are injected into the system prompt on every turn (or on relevant turns), giving the agent its identity, behavioral rules, environmental knowledge, and long-term memory. Managing these files well is critical: bloat wastes tokens, redundancy creates confusion, and stale content leads to bad decisions.

Token budget: 20,000 chars per file, ~150,000 chars total across all bootstrap files.

File Inventory

FilePurposeLoaded WhenSub-agents?
AGENTS.mdBoot sequence, checklists, behavioral rulesEvery turn (all agents)Yes
SOUL.mdPersona, tone, values, continuity philosophyEvery turn (all agents)Yes
TOOLS.mdEnv-specific notes (SSH, TTS, cameras, devices)On-demand reference (part of bootstrap set)Yes
USER.mdHuman profile, preferences, relationship contextEvery turn (all agents)Yes
IDENTITY.mdName, emoji, avatar, self-descriptionEvery turnYes
HEARTBEAT.mdPeriodic check tasks and health routinesEvery heartbeat turnDepends
BOOT.mdStartup actions (requires hooks.internal.enabled)On gateway startupNo
BOOTSTRAP.mdFirst-time onboarding script — delete after useNew workspaces onlyNo
MEMORY.mdLong-term curated facts and iron-law rulesMain sessions onlyNo
memory/YYYY-MM-DD.mdDaily session logsLoaded per AGENTS.md boot sequenceNo
checklists/*.mdStep-by-step ops guidesReferenced in AGENTS.md, loaded on demandNo

Security rule: MEMORY.md must NEVER be loaded in group chats or sub-agent sessions — it contains private context that should not leak.

For full details on each file's design, anti-patterns, and section structure, see references/workspace-files.md.

Workspace Paths

PathPurpose
~/.openclaw/workspace/Default workspace for main agent
~/.openclaw/workspace-<profile>/Per-profile workspace (multiple agents)
~/.openclaw/workspace/vendor/OpenClaw-Memory/Vendor-managed base files (synced from upstream)
~/.openclaw/workspace/checklists/Checklist files referenced from AGENTS.md
~/.openclaw/workspace/memory/Daily session logs
~/.openclaw/workspace/docs/On-demand documentation (NOT auto-loaded)

Config key: agents.defaults.workspace or per-agent agents.list[].workspace.

Workflow: Audit Existing Workspace

Use when workspace files may be bloated, stale, or redundant.

  1. Read all active files — AGENTS.md, SOUL.md, TOOLS.md, USER.md, IDENTITY.md, HEARTBEAT.md, BOOT.md, MEMORY.md
  2. Check character counts:
    bash
    wc -c ~/.openclaw/workspace/AGENTS.md
    wc -c ~/.openclaw/workspace/SOUL.md
    wc -c ~/.openclaw/workspace/TOOLS.md
    wc -c ~/.openclaw/workspace/USER.md
    wc -c ~/.openclaw/workspace/IDENTITY.md
    wc -c ~/.openclaw/workspace/MEMORY.md
    # Or all at once:
    wc -c ~/.openclaw/workspace/*.md
  3. Flag files over 10,000 chars — prime candidates for trimming or offloading to docs/
  4. Check for redundancy — same fact in SOUL.md and AGENTS.md? Same tool note in TOOLS.md and MEMORY.md?
  5. Check for staleness — outdated SSH hosts, old tool names, deprecated rules, historical context that's no longer needed
  6. Check MEMORY.md discipline — should contain curated facts, lessons learned, decisions, and critical rules — not raw session summaries or task-specific notes
  7. Propose targeted edits — trim, move to docs/, or restructure

See references/optimization-guide.md for specific optimization strategies.

Workflow: Set Up New Workspace

Use when creating a workspace for a new agent from scratch.

File creation order (matters for boot sequence to work):

  1. SOUL.md — persona and values first; everything else follows from identity
  2. AGENTS.md — boot sequence, safety rules, checklist table
  3. IDENTITY.md — name, emoji, avatar
  4. USER.md — human profile and preferences (main agent only)
  5. TOOLS.md — environment-specific notes (add as you discover env details)
  6. MEMORY.md — start minimal; only truly universal iron laws
  7. HEARTBEAT.md — periodic health checks (optional, add when needed)
  8. BOOT.md — startup hooks (optional, only if hooks.internal.enabled = true)
  9. BOOTSTRAP.md — first-run onboarding (optional; delete after first successful startup)

Minimal viable workspace: AGENTS.md + SOUL.md + TOOLS.md. Everything else is optional.

BOOTSTRAP.md note: If creating a BOOTSTRAP.md, include a self-deletion instruction at the end:

## Final Step
Delete this file: exec `rm ~/.openclaw/workspace/BOOTSTRAP.md`

Workflow: Memory Distillation

Use periodically (weekly or monthly) to keep MEMORY.md lean.

  1. Read all recent daily logs: memory/YYYY-MM-DD.md files from the past period
  2. Identify candidates for promotion to MEMORY.md:
    • Rules violated more than once (recurring mistakes)
    • Hard-won discoveries that aren't in skills docs
    • Env-specific facts that should always be in context (not left to memory_search recall)
  3. Check what's already in MEMORY.md — avoid duplicates
  4. Draft additions — use iron-law format: concise, action-oriented, unambiguous
  5. Archive old daily logs — move files older than 30 days to memory/archive/ or delete
  6. Check MEMORY.md total size — keep under 10,000 chars; if larger, review for rules that are now stable enough to move to a skill's SKILL.md instead

Do NOT put in MEMORY.md:

  • Long narratives or session summaries
  • Things already covered in skill docs
  • Anything specific to a single past task
  • Episodic or task-specific memories (store those via memory_search/SQLite instead)

Workflow: Add or Update a Checklist

Use when adding a new high-risk operation type or updating an existing checklist.

  1. Create or edit checklists/<operation-name>.md
  2. Structure:
    markdown
    # Checklist: <Operation Name>
    
    ## Pre-flight
    - [ ] Step 1
    - [ ] Step 2
    
    ## Execution
    - [ ] Step 3
    
    ## Verification
    - [ ] Confirm outcome
    - [ ] Log result in memory
  3. Register in AGENTS.md — add a row to the checklists table:
    markdown
    | <Operation description> | `checklists/<filename>.md` |
  4. Keep checklists short — if a checklist exceeds ~50 lines, it's probably trying to be documentation; move narrative content to docs/ and keep only the actionable steps

Workflow: Update TOOLS.md

Use when adding a new tool, device, or environment capability.

TOOLS.md = environment-specific cheat sheet. It should contain:

  • SSH hosts and common commands for this specific machine
  • TTS provider, voice IDs, and any quirks
  • Camera IDs or device names for this setup
  • Node device IDs or names
  • Any local aliases or shortcuts that aren't obvious

Do NOT put in TOOLS.md:

  • General skill documentation (use skill SKILL.md files)
  • Things that are the same across all environments
  • Installation instructions (use docs/)

Format conventions:

markdown
# TOOLS.md - Local Notes

## SSH
- Main server: `ssh user@hostname`

## TTS
- Provider: Edge
- Voice: zh-CN-XiaoxiaoNeural

## Cameras
- Living room: node-id `abc123`, device `camera-0`

Common Issues

File exceeds token limit

Symptom: File is over 20,000 chars; OpenClaw may truncate it. Fix: Audit for content that belongs in docs/ (loaded on demand) instead of the bootstrap file. Move detailed references, historical context, and long examples out. Keep only what needs to be on every turn.

MEMORY.md leaking to groups

Symptom: Agent shares private context in group chats or Discord. Fix: Ensure MEMORY.md boot step in AGENTS.md is gated: "Main session only: Read MEMORY.md". Verify the agent's boot sequence explicitly checks session type before loading.

Boot sequence not loading files

Symptom: Agent doesn't know about content in SOUL.md, USER.md, or MEMORY.md at session start. Fix: Check that AGENTS.md boot sequence explicitly names each file to read. The agent won't auto-load files — it follows the boot sequence instructions in AGENTS.md. Verify hooks.internal.enabled = true in config if using BOOT.md.

MEMORY.md growing too large

Symptom: File approaches or exceeds 10,000 chars; reading it on every turn wastes significant context. Fix: Run memory distillation workflow. Move stable rules that have been incident-free for months into relevant skill SKILL.md files. Delete rules that are no longer relevant.

Workspace changes not taking effect

Symptom: Agent still uses old content after editing a workspace file. Fix: Workspace files are read at session start per the boot sequence. Restart the gateway or start a new session for changes to take effect.

Reference Files

ReferenceCoverage
workspace-files.mdDeep-dive on each file: purpose, design principles, anti-patterns, section structure
optimization-guide.mdToken efficiency strategies, audit commands, distillation process

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Openclaw Workspace AI skill do?

Use when maintaining or optimizing OpenClaw workspace files — AGENTS.md, TOOLS.md, SOUL.md, USER.md, IDENTITY.md, HEARTBEAT.md, BOOT.md, MEMORY.md, and related checklists and memory files. Covers workspace auditing, token budget analysis, new agent workspace setup from scratch, memory distillation, and cross-file consistency reviews.

Why use Openclaw Workspace on TypingMind?

Because you install it once and use it with any model. Openclaw Workspace is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Openclaw Workspace in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/win4r/openclaw-workspace/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Openclaw Workspace?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Openclaw Workspace?

As many as you like. As long as a model supports skills, you can use Openclaw Workspace with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Openclaw Workspace AI skill free?

It is published on GitHub by win4r. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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