SKILLEMALL.ai
GitHub ↗ RU Sign in

BD fp_youtube_script

输入视频主题、关键词、产品信息，输出 5 分钟 YouTube 维修科普视频的完整 10 列分镜脚本。 严格对齐运营 Excel 蓝本：Section/镜号/景别/画面内容/参考画面(生图prompt)/ 台词初版中英/二次验证中英/建议画面。符合北美机械师口语习惯，内置 FridayParts 技术准确性规范，第一次输出就自动规避"过于绝对"的技术表述。 Use when: 生成 YouTube 视频脚本 / 维修教程脚本 / 设备故障科普视频。

ClawHub Agent Skills author: zhuxirui677 v1.0.0 MIT-0 8 files body ≈ 1 139 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

输入视频主题、关键词、产品信息，输出 5 分钟 YouTube 维修科普视频的完整 10 列分镜脚本。 严格对齐运营 Excel 蓝本：Section/镜号/景别/画面内容/参考画面(生图prompt)/ 台词初版中英/二次验证中英/建议画面。符合北美机械师口语习惯，内置 FridayParts…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureYouTubeMedia 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
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
D
46/100
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
    • 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: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "display_name"
    • note frontmatter-key unknown frontmatter key "temperature"
    • note frontmatter-key unknown frontmatter key "max_tokens"
    • note frontmatter-key unknown frontmatter key "triggers"

    Process rating: all ten parameters 46/100

    • 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
    • 40Consistency. Frontmatter name (fp_youtube_script) differs from the folder (fp-youtube-script)
    • 100Tools and files. No external tools needed
    • 100Steps. 21 steps
    • 100Execution cost. Instruction body is 1139 tokens

    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
    • -42 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +3Description length 226: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 21 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

    External checks

    ClawHub: clean
    This skill is a coherent prompt-only helper for generating FridayParts repair-video scripts, with no evidence of hidden execution, data access, persistence, or exfiltration.
    LLM: benign (high) · VirusTotal: · 29 Jun 2026