SKILLEMALL.ai

AC mp-cli-sup

Debug a WeChat Mini Program's LIVE runtime via the system `vince-mp` JSON CLI — one persistent session, then instant reused commands (pageData, query/tap, scan, console, doctor, log correlation). Use for "debug WeChat DevTools", "连上小程序", "$mp-cli-sup". NOT for browser automation, source-only edits, or non-WeChat work.

ClawHub Agent Skills author: VincentJiang06 v0.2.2 MIT-0 20 files body ≈ 2 066 tokens Open the sourceclawhub.ai analyzed 32 h ago

Debug a WeChat Mini Program's LIVE runtime via the system vince-mp JSON CLI — one persistent session, then instant reused commands (pageData, query/tap, scan…

As a process C 50/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

IntegrationSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
95
Quality 40%
94
Run on models
none yet
Process rating
C
50/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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.

Obfuscation 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 files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.

For the author

Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.

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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • medium Obfuscation uni-zero-width scripts/check_battery_clean.mjs:47
      Zero-width / invisible characters (possible hidden text) (3 occurrences)
      const ctxKey = (c) => String(c).replace(/[␀-␀␀­]/g, "").trim().toLowerCase();

    Files scanned: 20. 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 50/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 100Steps. 24 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2066 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

    • +3Output format is not stated: the model decides each time
    • -31 of 5 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 319: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 24 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (5 of 5)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.

    External checks

    ClawHub: clean
    This skill is a live WeChat Mini Program debugging helper with powerful but disclosed runtime controls and documented safety boundaries.
    LLM: benign (high) · VirusTotal: · 1 Aug 2026