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AceDataCloud/Skills Agent Skills author: AceDataCloud 1 file body ≈ 1 086 tokens Open the sourcegithub.com↗ analyzed 2 h ago

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As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationMedia and videotype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
95
Quality 40%
83
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Exfiltration exfil-secret-in-url SKILL.md:24
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      ME=$(curl -sS "https://graph.threads.net/v1.0/me?fields=…&access_token=…")
      placeholder
    • low Exfiltration net-credential-use SKILL.md:24
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
      ME=$(curl -sS "https://graph.threads.net/v1.0/me?fields=…&access_token=…")
      vendor-host
    • low Exfiltration net-credential-use SKILL.md:79
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
      curl -sS "https://graph.threads.net/v1.0/<THREADS_MEDIA_ID>?fields=id,permalink&access_token=$THREADS_ACCESS_TOKEN" | jq -r .permalink
      vendor-host
    • low Exfiltration exfil-secret-in-url SKILL.md:91
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      curl -sS "https://graph.threads.net/v1.0/$TID/threads?fields=…&limit=20&access_token=…" | jq '.data'
      placeholder
    • low Exfiltration net-credential-use SKILL.md:91
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
      curl -sS "https://graph.threads.net/v1.0/$TID/threads?fields=…&limit=20&access_token=…" | jq '.data'
      vendor-host

    Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "connections"
    • note frontmatter-key unknown frontmatter key "allowed_tools"

    Process rating: all ten parameters 54/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 20 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 5 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1086 tokens
    • high The skill tells the model to perform an irreversible action with no human approval
    • low The response is described with custom markup (4 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
    • +2Single-language instructions
    • +3Description length 361: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 5 items
    • +4Has examples (7 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.