SKILLEMALL.ai

AB wechat-article-visual-story

Write the WeChat article and make its pictures in one pass. Give a topic, what you are promoting, and who it is for — this WeChat Official Account article generator returns title candidates written for the feed, the digest line, a full article body structured for how people actually read on a phone, then renders the 2.35:1 cover and a set of in-body images that hold one look from top to bottom. Use it for WeChat Official Account posts, brand and product articles, promotional long-form, founder and expert columns, case studies, content marketing programmes, and any long-form post where the writing and the pictures have to be produced together rather than handed between two people.

ClawHub Agent Skills author: beatra-ai v0.1.5 MIT-0 16 files body ≈ 2 306 tokens Open the sourceclawhub.ai analyzed 2 d ago

Write the WeChat article and make its pictures in one pass.

As a process B 66/100 · Nearly there — weak spots: result and completion, progress reporting

GeneratorWriting 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
66/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
50
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: 16. 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 66/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 16 steps
    • 100Inputs and preconditions. Inputs and preconditions are listed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2306 tokens
    • 100Running it twice. Mutating operations check current state

    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
    • -32 of 3 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 688: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 16 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (10 of 10)

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

    External checks

    ClawHub: suspicious
    The skill is mostly coherent for writing WeChat articles with images, but it needs Review because it uses broad Beatra account authority, stored bearer credentials, telemetry, and silent self-updates beyond the narrow article-image task.
    LLM: suspicious (high) · 28 Aug 2026