SKILLEMALL.ai

AB html-to-wechat

Take existing HTML content (file, URL, or pasted HTML) and publish it directly to WeChat Official Account draft box. No file conversion, no web scraping — just HTML to WeChat compatibility check to publish. Use when the user already has HTML and wants to push it to WeChat.

ClawHub Agent Skills author: lutongsuo v1.0.0 MIT-0 5 files body ≈ 3 753 tokens Open the sourceclawhub.ai analyzed 2 d ago

Take existing HTML content (file, URL, or pasted HTML) and publish it directly to WeChat Official Account draft box.

As a process B 69/100 · Nearly there — weak spots: result and completion, running it twice

ProcedureSoftware developmentAI and agentsWriting and documentstype 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
69/100
Nearly there
Result and completion w 14
0
Running it twice w 4
30
Tools and files w 18
60
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "prerequisites"
    • note frontmatter-key unknown frontmatter key "triggers"

    Process rating: all ten parameters 69/100

    • 0Result and completion. Does not say what the result is
    • 30Running it twice. 26 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, read, web, python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 44 steps
    • 100Failures and branches. 3 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3753 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • high The skill tells the model to perform an irreversible action with no human approval
    • low The response is described with custom markup (15 tags): a typed call is more reliable

    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 273: enough signal without eating the budget
    • +4Structure: 24 headings
    • +3Step-by-step instructions: 44 items
    • +4Has examples (13 code blocks)
    • +3All 1 scripts are documented

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

    External checks

    ClawHub: clean
    This skill coherently helps publish user-provided HTML to a WeChat draft box, but it uses WeChat credentials, external uploads, and one runtime dependency install that users should understand first.
    LLM: benign (medium) · VirusTotal: · 9 Jul 2026