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AB qgcar-skill

Use when the user wants help with Qiguan campus bus tickets using the local qg CLI, including listing schedules, choosing Zhuhai/South/East campus routes, generating WeChat order-entry links, copying links, or troubleshooting qg/qg-list commands. The skill should help prepare a booking link, but must not auto-submit passenger information, create orders, or pay.

ClawHub Agent Skills author: qybaihe v0.1.0 MIT-0 27 files · 1 script body ≈ 746 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process B 70/100 · Nearly there — weak spots: inputs and preconditions

IntegrationInfrastructuretype 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%
90
Quality 40%
91
Run on models
none yet
Process rating
B
70/100
Nearly there
Inputs and preconditions w 11
0
Tools and files w 18
60
Result and completion w 14
60
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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 · 6

    ✓ No critical or high findings

    Medium and low: 6
    • medium Dangerous commands cmd-pipe-to-shell-known-host README.md:35
      Pipe-to-shell installer from a well-known host (still executes remote code)
      curl -fsSL https://raw.githubusercontent.com/qybaihe/qg-skill/26ed…79c/install.sh | bash
    • low Secrets in code secret-high-entropy-token package-lock.json:231
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…l1I+R1H7…G3i/cYFJ…fIw==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:265
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…XcW+/GvMN…kxZ/opySAZMrc+9LY/WyjA…InQ==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:282
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…qEP+UeRV…fdw==",
      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…Fnw/+3lVx…cQS+Yu6w==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:418
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…UzV+AA46…P4O+ng17CA==",
      detector

    Files scanned: 27. 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 70/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 8 branches
    • 100Steps. 5 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 746 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress

    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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 363: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 5 items
    • +3Output format is stated explicitly
    • +4Has examples (11 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: clean
    This skill is a disclosed campus bus helper that queries schedules and generates WeChat order-entry links, but its installer deserves normal supply-chain caution.
    LLM: benign (high) · VirusTotal: · 29 May 2026