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📐 詹明明·口播稿写作 ——口播稿协作写作技能（知识付费口播为主形态）。三类脚本选型 + 从内容单元装配 + 逐段共创，不一键成稿。 触发方式：/zmm-script、/写口播、/写稿、/zmm-写稿、「写个口播稿」「帮我把这个题写出来」「知识付费口播」「写条视频文案」 Collaborative koubo (talking-head) script writing: script-type selection, unit assembly, section-by-section co-writing. Trigger: /zmm-script, "write a talking-head script", "turn this topic into a video script" —— 📐 詹明明 · 不给公式，给判据。每条规则都标了实测代价。

ClawHub Agent Skills author: 詹明明 v0.2.10 MIT-0 3 files body ≈ 2 076 tokens Open the sourceclawhub.ai↗ analyzed 2 h ago

📐 詹明明·口播稿写作 ——口播稿协作写作技能（知识付费口播为主形态）。三类脚本选型 + 从内容单元装配 + 逐段共创，不一键成稿。 触发方式：/zmm-script、/写口播、/写稿、/zmm-写稿、「写个口播稿」「帮我把这个题写出来」「知识付费口播」「写条视频文案」 Collaborative koubo…

As a process F 33/100 · Will not run — References files that are not bundled: references/规则卡.md

GeneratorMedia and videotype 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
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: references/规则卡.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/规则卡.md
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: references/规则卡.md
  • 0Tools and files. 1 referenced file(s) missing: references/规则卡.md
  • 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
  • 100Steps. 32 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2076 tokens
  • 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -222 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 381: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 32 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

External checks

ClawHub: suspicious
This is a coherent Chinese script-writing skill, but it gives mutable external vault files and automatic memory writebacks too much durable influence without clear user approval.
LLM: suspicious (high) · 12 Sept 2026