CD model-checker
查询公司内部可用AI模型列表。
As a process D 36/100 · Unfinished process — weak spots: steps, result and completion, when it triggers
How to improve
- 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 · 5
✓ No critical or high findings
Medium and low: 5
-
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:18High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…9dM/mwVgvbZJaSNaRk+bshk…Kbz+IoId…W0Q==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:48High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…SDq+2kAA…MOe/+5cdoEdg==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:83High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…FrF+LTRo…W3g==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:92High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…A6j+hAmM…GbS+kf5c…csw==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:101High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…5bm+c2gQ…aG5+esrLODihIorn+Pe6F…dXA==",
detector
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-shortdescription under 40 chars: too little signal for triggering - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 36/100
- 0Steps. Prose only: no discrete steps
- 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
- 100Tools and files. No external tools needed
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 46 tokens
- 100Running it twice. No mutating operations
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 15: 120–800 characters recommended
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- -15SKILL.md body under 300 characters: nearly empty
- +1No license
- +2Single-language instructions
- +4Structure: 3 headings
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 43.
External checks
ClawHub: clean
This skill simply fetches a disclosed list of internal AI models from one stated company API endpoint, with no evidence of hidden local access or persistence.
LLM: benign (high) · VirusTotal: · 28 May 2026