SKILLEMALL.ai

BF wechat-search

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ClawHub Agent Skills author: to the moon v1.0.4 MIT-0 6 files body ≈ 2 610 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 31/100 · Will not run — References files that are not bundled: url

ProcedureGitHubInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
94
Quality 40%
67
Run on models
none yet
Process rating
F
31/100
Will not run
References files that are not bundled: url
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: wechat-search (ClawHub)

What is at stake

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

Secrets in code 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 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 If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail.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. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Secrets in code secret-labelled-token references/gzh_trend_data_format.md:20
    Labelled token / key literal (vendor format unknown — verify it is not a live credential)
    X-API-Key: ak_c…6c3
  • low Secrets in code secret-password-literal references/gzh_trend_data_format.md:20
    Hard-coded password / key literal (may be an example)
    X-API-Key: ak_c…6c3

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: url
  • note frontmatter-key unknown frontmatter key "dependency"

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: url
  • 0Tools and files. 1 referenced file(s) missing: url
  • 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
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (wechat-search) differs from the folder (gzh-explosive-content-detector)
  • 100Steps. 104 steps
  • 100Execution cost. Instruction body is 2610 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 76: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -251 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 35 headings
  • +3Step-by-step instructions: 104 items
  • +4Has examples (11 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: suspicious
The skill mostly matches its WeChat article-search purpose, but it ships a hardcoded Redfox API key and includes optional calendar subscription behavior that users should review carefully.
LLM: suspicious (high) · VirusTotal: · 2 Jun 2026