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BD bilibili-video-parser

B站视频解析-把B站视频链接（bilibili.com/video/BVxxx 长链或 b23.tv 短链）转成中文字幕连贯稿和交互式 HTML 报告。原理：B站公开 API 获取元数据+cid -> 优先尝试CC字幕API（有字幕直接用，跳过转写）-> 无字幕时下载音频流 -> 本地 faster-whisper（base 模型、CPU、int8）转写 -> 本地规则提取分析 -> 生成交互式 HTML 报告（含一句话总结、金句卡片、核心观点、结构拆解、内容判断、内容亮点六大模块）。免费，不依赖任何 API key 或 cookie 登录。一条命令出连贯稿（无时间戳）+ 可视化 HTML 报告。

ClawHub Agent Skills author: Black_Amico v0.1.4 MIT-0 5 files body ≈ 1 426 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

B站视频解析-把B站视频链接（bilibili.com/video/BVxxx 长链或 b23.tv 短链）转成中文字幕连贯稿和交互式 HTML 报告。原理：B站公开 API 获取元数据+cid -> 优先尝试CC字幕API（有字幕直接用，跳过转写）-> 无字幕时下载音频流 -> 本地…

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationMedia and videoSoftware developmenttype 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%
73
Run on models
none yet
Process rating
D
41/100
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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"

Process rating: all ten parameters 41/100

  • 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
  • 40Consistency. Frontmatter name (bilibili-video-parser) differs from the folder (bilibili-video-parser-2)
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 100Steps. 32 steps
  • 100Execution cost. Instruction body is 1426 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
  • +2Single-language instructions
  • +3Description length 302: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 32 items
  • +4Has examples (8 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This skill does what it claims: it turns user-provided Bilibili videos into local transcripts and HTML reports using disclosed network downloads and local transcription.
LLM: benign (high) · VirusTotal: · 14 Aug 2026