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微信公众号全流程运营：选题→采集→写作→排版→发布→数据分析→评论管理。 Use when: (1) 用户要写公众号文章或提供了选题方向, (2) 用户说"写一篇关于XXX的文章"/"帮我写篇推文"/"出一篇稿子", (3) 用户要求采集热点/素材/竞品分析, (4) 用户提到公众号日报/周报/数据分析/阅读量/粉丝, (5) 用户要求检查评论/回复评论/评论管理, (6) 用户说"发布"/"推送"/"推到公众号"/"发到草稿箱", (7) 用户讨论文章排版/封面图/标题优化。 即使用户没有明确说"公众号"，只要涉及微信文章写作、内容发布、 公众号后台操作、文章数据查看、或读者互动管理，都应使用此技能。 当用户给出选题方向时，自动完成素材采集→内容写作→封面生图→排版美化→推送草稿箱全流程。

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 29 files body ≈ 2 352 tokens Open the sourcegithub.com↗ analyzed 3 d ago

微信公众号全流程运营：选题→采集→写作→排版→发布→数据分析→评论管理。 Use when: (1) 用户要写公众号文章或提供了选题方向, (2) 用户说"写一篇关于XXX的文章"/"帮我写篇推文"/"出一篇稿子", (3) 用户要求采集热点/素材/竞品分析, (4)…

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentAI and agentsWriting 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
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
D
43/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 26. 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 43/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 60Tools and files. Uses tools (python, node) that frontmatter does not declare
    • 100Steps. 118 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2352 tokens
    • low The response is described with custom markup (10 tags): a typed call is more reliable
    • medium 3 test cases, all positive: not one "should refuse" or "should ask first"

    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
    • -31 of 9 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +3Description length 350: enough signal without eating the budget
    • +4Structure: 28 headings
    • +3Step-by-step instructions: 118 items
    • +4Has examples (8 code blocks)
    • +4Reference files are cited in the instructions (7 of 8)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.