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BC OpenClaw Documentation Expert — Live Fetch

Fetches live from docs.openclaw.ai on every question. Whole-docs index, working scripts (not echo placeholders), CI-style selftest for decision-tree rot, worked routing examples, SOUL/multi-agent/sessions/platforms/nodes/clawhub covered.

ClawHub Agent Skills author: Igor Numeriano v1.6.2 MIT-0 9 files · 6 scripts body ≈ 4 301 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

ReferenceInfrastructureAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
99
Quality 40%
70
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • low Dangerous commands cmd-autorun-instruction EXAMPLES.md:4
    Instructs the agent to auto-run a script on every session (test fixture / example file)
    These are few-shot anchors, not answers. Always run `scripts/fetch.sh <path>` before replying.
    fixture

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 55/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 12 mutating operations with no state check
  • 40Consistency. Frontmatter name (OpenClaw Documentation Expert — Live Fetch) differs from the folder (openclaw-handbook)
  • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 4301 tokens
  • 100Steps. 34 steps
  • 100Failures and branches. 3 branches, has a failure section
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (15 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 237: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 34 items
  • +4Has examples (1 code blocks)
  • +3All 6 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.

External checks

ClawHub: clean
This skill is a focused OpenClaw documentation helper with disclosed local miss logging that users should be aware of.
LLM: benign (high) · VirusTotal: · 29 May 2026