SKILLEMALL.ai

AB wjs-publishing-wechat

Use when the user wants to write or publish a 微信公众号 (WeChat Official Account) article — they share rough thoughts, a draft, or notes and ask for help polishing, generating a cover image (题图) and explanation illustration (解释图), or preparing the article for upload to mp.weixin.qq.com. Triggers include "写一篇微信文章", "公众号", "润色", "题图", "发公众号", "/wjs-publishing-wechat".

ClawHub Agent Skills author: Jian Shuo Wang v0.1.0 MIT-0 10 files · 4 scripts body ≈ 2 015 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 67/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorWriting and documentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
B
67/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
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 · 0

    ✓ No critical or high findings

    Files scanned: 10. 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 67/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 14 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 50Failures and branches. 0 branches, has a failure section
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 82 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2015 tokens

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 364: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 82 items
    • +4Has examples (11 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    This skill is mostly a real WeChat publishing helper, but it needs review because it can use account credentials, send draft content to AI/image services, and create WeChat drafts with broad activation rules.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026