SKILLEMALL.ai

AC wechat-article-extract

Extract public WeChat Official Account articles from mp.weixin.qq.com links or saved HTML into clean Markdown or structured JSON, including title, account name, publish time, article text, tables, image markers, and image URLs. Use when the user asks to read, scrape, parse, extract, archive, convert, summarize, or save WeChat/Weixin/微信公众号 public article content.

ClawHub Agent Skills author: JoannaXing v1.0.0 MIT-0 5 files body ≈ 555 tokens Open the sourceclawhub.ai analyzed 2 d ago

Extract public WeChat Official Account articles from mp.weixin.qq.com links or saved HTML into clean Markdown or structured JSON, including title, account…

As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
58/100
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 · 0

    ✓ No critical or high findings

    Files scanned: 4. 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 58/100

    • 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. 2 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
    • 100Steps. 25 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 555 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

    • +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
    • +1No license
    • +2Single-language instructions
    • +3Description length 364: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 25 items
    • +4Has examples (2 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This skill is a straightforward WeChat article extractor whose file and network behavior is disclosed and fits its purpose.
    LLM: benign (high) · VirusTotal: · 14 Jun 2026