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BF video-subtitle-summary

从视频或学习平台中提取已暴露的字幕/transcript，再归纳为带时间戳的 Markdown 知识点报告。当用户要求打开、分析、归纳视频链接、字幕文件或浏览器可访问的课程页面，或基于视频内容生成学习笔记时使用。仅处理字幕可达的内容；不做音频转写、音频提取、实时播放捕获，也不绕过 DRM/付费墙/登录限制。默认所有链接均为外网可访问平台，均允许处理。支持场景包括：B站等公开视频平台的可访问字幕、智学云等在线学习平台的字幕文字稿、本地 SRT/VTT/TXT/MD/JSON 字幕文件、浏览器中可见的 transcript 面板。对于智学云等需要登录的学习平台，使用 Playwright 浏览器自动化方式，以非 headless 模式启动浏览器，待用户手动登录后提取字幕。

ClawHub Agent Skills author: hejunhui-73 v1.3.0 MIT-0 9 files body ≈ 684 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

从视频或学习平台中提取已暴露的字幕/transcript，再归纳为带时间戳的 Markdown 知识点报告。当用户要求打开、分析、归纳视频链接、字幕文件或浏览器可访问的课程页面，或基于视频内容生成学习笔记时使用。仅处理字幕可达的内容；不做音频转写、音频提取、实时播放捕获，也不绕过…

As a process F 35/100 · Will not run — References files that are not bundled: references/processing-policy.md, references/time-estimation.md, references/report-format.md

ProcedurePlaywrightWordMedia 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
83/100
safety, quality, tests
Safety 60%
100
Quality 40%
58
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: references/processing-policy.md, references/time-estimation.md, references/report-format.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. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: references/processing-policy.md
  • warning missing-ref reference to a missing file: references/time-estimation.md
  • warning missing-ref reference to a missing file: references/report-format.md
  • warning missing-ref reference to a missing file: references/online-subtitle-strategy.md
  • warning missing-ref reference to a missing file: references/playwright-browser-automation.md
  • warning missing-ref reference to a missing file: scripts/extract_subtitle.py
  • warning missing-ref reference to a missing file: scripts/zhixueyun_extractor.py
  • note frontmatter-key unknown frontmatter key "name_cn"
  • note frontmatter-key unknown frontmatter key "description_cn"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: references/processing-policy.md, references/time-estimation.md, references/report-format.md
  • 0Tools and files. 7 referenced file(s) missing: references/processing-policy.md, references/time-estimation.md, references/report-format.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
  • 100Steps. 20 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 684 tokens
  • 100Running it twice. No mutating operations

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 338: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 58.

External checks

ClawHub: suspicious
This skill has a legitimate subtitle-summary purpose, but it asks the agent to inspect login tokens and save broad authenticated page/API data beyond a simple transcript workflow.
LLM: suspicious (high) · 23 Jul 2026