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AB file-to-wechat

将任意文件（PDF、Word、Excel、PPT、图片、音频、网页等）转换为 Markdown，再生成为精美的微信公众号文章并发布到草稿箱。组合 markitdown + md_to_wechat_html + publish_to_wechat 三阶段流水线。Use when the user wants to convert any file to a WeChat article.

ClawHub Agent Skills author: lutongsuo v1.1.0 MIT-0 5 files body ≈ 2 461 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

将任意文件（PDF、Word、Excel、PPT、图片、音频、网页等）转换为 Markdown，再生成为精美的微信公众号文章并发布到草稿箱。组合 markitdown + mdtowechathtml + publishtowechat 三阶段流水线。Use when the user wants to…

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

ProcedureExcelPowerPointWordYouTubeSoftware developmentData and analyticsWriting and documentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
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. 8 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, 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. 27 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2461 tokens
    • 100Progress reporting. Reports progress
    • low 10 top-level sections: this looks like several domains in one skill

    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 195: enough signal without eating the budget
    • +4Structure: 21 headings
    • +3Step-by-step instructions: 27 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: suspicious
    This skill does what it claims, but it can read broad user files and upload generated content to WeChat drafts without a clear review or consent checkpoint.
    LLM: suspicious (medium) · 1 Jul 2026