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Not recommendedcritical or high security findings · low grade D
ClawHub Agent Skills author: wljmmx v0.1.5 MIT-0 69 files body ≈ 1 539 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process F 30/100 · Will not run — References files that are not bundled: PERFORMANCE_REPORT.md, QUALITY_REPORT.md

ProcedureGitHubInfrastructuretype 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
D
44/100
safety, quality, tests
Safety 60%
74
Quality 40%
0
Run on models
none yet
Process rating
F
30/100
Will not run
References files that are not bundled: PERFORMANCE_REPORT.md, QUALITY_REPORT.md
Tools and files w 18
0
Result and completion w 14
0
When it triggers w 12
0
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Secrets in code
If you install

The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. Add a description to the frontmatter: without it the skill never triggers.
  3. The text references files that are not there: add them or drop the references.
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 · 9

  • high Secrets in code meta-credential-files .env
    Credential / dotenv files bundled with the skill (1)
    .env
Medium and low: 8
  • low Exfiltration read-dotenv CONFIG.md:273
    Reads a .env file
    cp .env.example .env
  • low Secrets in code secret-high-entropy-token package-lock.json:85
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…VHO+q2xB…AGd+Kl0mmq/MprG…MzA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:126
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…VHO+q2xB…AGd+Kl0mmq/MprG…MzA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:289
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "integrity": "sha5…ywo+qwL+oL8H…C1U+vRfLQDvw==",
    quoted
  • low Secrets in code secret-high-entropy-token package-lock.json:304
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha512-Yqfm+XDx0+Prh3…1yC+JWZ2…IL7+vK+Clp7…D7g==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:316
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…xZl+RoGR…fbT/ZgrF…0EA==",
    detector
  • low Exfiltration read-dotenv README.md:146
    Reads a .env file
    cp .env.example .env
  • low Exfiltration read-dotenv SKILL.md:155
    Reads a .env file
    cp .env.example .env

Files scanned: 68. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error frontmatter SKILL.md: no YAML frontmatter block found
  • error name-missing SKILL.md: frontmatter has no `name`
  • error description-missing SKILL.md: no `description` — the skill can never trigger
  • warning missing-ref reference to a missing file: PERFORMANCE_REPORT.md
  • warning missing-ref reference to a missing file: QUALITY_REPORT.md

Process rating: all ten parameters 30/100

Will not run. References files that are not bundled: PERFORMANCE_REPORT.md, QUALITY_REPORT.md
  • 0Tools and files. 2 referenced file(s) missing: PERFORMANCE_REPORT.md, QUALITY_REPORT.md
  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 4 mutating operations with no state check
  • 100Steps. 127 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1539 tokens
  • 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)
  • +3Description length 0: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -217 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 40 headings
  • +3Step-by-step instructions: 127 items
  • +4Has examples (15 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.

External checks

ClawHub: suspicious
This skill matches its stated GitHub and agent-collaboration purpose, but it needs review because it can act through your GitHub login, control agent sessions, send data externally, and contains unsafe command and logging patterns.
LLM: suspicious (high) · VirusTotal: · 29 May 2026