ClawHub is a public registry where OpenClaw users publish, version, search, and install text-based agent skills and OpenClaw packages. It provides web browsing, a CLI-oriented API, moderation, vector search, and artifact hosting for code plugins, bundle plugins, and experimental whole-agent packages. The catalogue skills and agents are entries that can be discovered or used through this registry.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add openclaw/clawhub --skill technical-documentationgit clone --depth 1 https://github.com/openclaw/clawhubWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/openclaw/clawhub/technical-documentation)<a href="https://agentmods.dev/skills/openclaw/clawhub/technical-documentation"><img src="https://agentmods.dev/badge/skills/openclaw/clawhub/technical-documentation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/openclaw/clawhub/technical-documentation"><img src="https://agentmods.dev/badge/skills/openclaw/clawhub/technical-documentation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00021 | $0.01239 |
| Opus 5 | $0.00010 | $0.00620 |
| Sonnet 5 | $0.00004 | $0.00248 |
| Haiku 4.5 | $0.00002 | $0.00124 |
Grade A, and why
technical-documentation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- technical-documentation — 94% identical, 24 lines differ
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Technical Documentation
Purpose
Produce and review technical documentation that is clear, actionable, and maintainable for both humans and agents, including contributor-governance files and agent instruction files.
When to use
- Creating or overhauling docs in an existing product/codebase (brownfield).
- Building evergreen docs meant to stay accurate and reusable over time.
- Reviewing doc diffs for structure, clarity, and operational correctness.
- Running full-repo documentation audits that must include both governance files and product docs surfaces (
docs/,README*,.md/.mdx/.mdc, Fern/Sphinx/Mintlify-style sources). - Updating or reviewing AGENTS.md and/or CONTRIBUTING.md to keep agent and contributor workflows aligned with current repo practices.
- Improving repository onboarding/docs that include contribution instructions, issue templates, PR flow, and review gates.
- Designing governance documentation strategy for repos with alias instruction files (for example
CLAUDE.md,AGENT.md,.cursorrules,.cursor/rules/*,.agent/,.agents/,.pi/) whereAGENTS.mdis treated as canonical when present and aliases should be kept as compatibility surfaces. - Diagnosing agent-file drift where teams had to prompt iteratively to surface missing files, broken commands, or policy conflicts.
- Applying repository-specific documentation overlays, including OpenClaw page-type, docs IA, preservation, and validation rules when present.
Workflow
- Classify task:
buildorreview; context:brownfieldorevergreen. - Inventory full documentation scope early (governance + product docs): AGENTS/CONTRIBUTING/aliases plus docs directories, framework sources, and root/module READMEs.
- Detect multilingual scope (README/docs in multiple languages) and define required parity level.
- Read
references/agent-and-contributing.mdfor agent instruction andCONTRIBUTING.mdworkflow rules (inventory, canonical/alias mapping, dual-mode balance, deliverable standards, and precedence/conflict handling). - Read
references/principles.mdfor the governing ruleset (Matt Palmer & OpenAI). - For OpenClaw docs work, read
references/openclaw.mdbefore the build/review playbook. - For build tasks, follow
references/build.md. - For review tasks, follow
references/review.mdand proactively detect issues without waiting for repeated prompts. - For complex or high-risk tasks (build or review), it is acceptable to run longer, deeper, and more exhaustive investigations when needed for confidence.
- When available, use sub-agents for bounded parallel discovery/review work, then merge outputs into one coherent final deliverable.
- Use
references/tooling.mdwhen platform/tooling choices affect recommendations. - Run a proactive issue sweep for both governance and docs-content surfaces, and fix high-confidence defects in the same pass unless explicitly asked for report-only mode.
- In brownfield mode, prioritize compatibility with current docs IA, tooling, and release state.
- In evergreen mode, prioritize timeless wording, update strategy, and durable structure.
- Return deliverables plus validation notes, parity status, and remaining gaps.
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/docs-framework-agent.md 794 B
- agents/governance-agent.md 764 B
- agents/inventory-agent.md 808 B
- agents/openai.yaml 410 B
- agents/synthesis-agent.md 719 B
- assets/icon.jpg 37 KB
- references/agent-and-contributing.md 8.5 KB
- references/build.md 6.8 KB
- references/openclaw.md 5.6 KB
- references/principles.md 2.3 KB
- references/review.md 6.3 KB
- references/tooling.md 1.4 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 80 lines · 21 tokens per session scan A 67a93dc4b226
technical-documentation is a skill published in the GitHub repository openclaw/clawhub (9,402 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 1,239 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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