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Use when an OpenClaw or Codex agent needs to work inside URUC, handle URUC-originated or [URUC_EVENT] messages first, bootstrap the bundled local daemon from OpenClaw skill env, inspect authoritative session state, discover live city/plugin commands, and keep the active OpenClaw workspace AGENTS.md, TOOLS.md, and memory docs synchronized with stable URUC rules.

ClawHub Agent Skills author: waibiwaibi v1.0.0 MIT-0 10 files body ≈ 3 783 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceAI and agentsSoftware developmentInfrastructuretype 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
A
90/100
safety, quality, tests
Safety 60%
98
Quality 40%
79
Run on models
none yet
Process rating
D
44/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

    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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-high-entropy-token scripts/lib/openclaw-gateway.mjs:246
      High-entropy token-like string (may be an id, hash or a credential)
      publicKey: publ…Pem(deviceIdentity.publicKeyPem),
    • low Secrets in code secret-high-entropy-token scripts/lib/openclaw-gateway.mjs:403
      High-entropy token-like string (may be an id, hash or a credential)
      function publ…Pem(publicKeyPem) {

    Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 44/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 18 mutating operations with no state check
    • 40Consistency. Frontmatter name (uruc-skill) differs from the folder (uruc)
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 60Failures and branches. 2 branches
    • 85Steps. 221 steps, 2 vague phrases
    • 100Execution cost. Instruction body is 3783 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 11 top-level sections: this looks like several domains in one skill

    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
    • -2localhost URLs: will not work for another user
    • -31 of 2 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 363: enough signal without eating the budget
    • +4Structure: 28 headings
    • +3Step-by-step instructions: 221 items
    • +4Has examples (9 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

    External checks

    ClawHub: suspicious
    This appears to be a real URUC bridge skill, but it gives agents persistent background control, broad remote action authority, and permission to change future workspace instructions without a clear approval gate.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026