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BF video-transcript

从本地视频文件中提取语音文案/字幕。跨平台支持macOS/Windows/Linux，完全离线运行。使用whisper模型进行高精度语音识别，支持多语言字幕提取和OCR文字识别。触发词：视频文案提取、提取字幕、语音转文字、视频转文字、提取文案。

ClawHub Agent Skills author: 桂皮 v1.0.3 MIT-0 3 files body ≈ 1 094 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

从本地视频文件中提取语音文案/字幕。跨平台支持macOS/Windows/Linux，完全离线运行。使用whisper模型进行高精度语音识别，支持多语言字幕提取和OCR文字识别。触发词：视频文案提取、提取字幕、语音转文字、视频转文字、提取文案。

As a process F 31/100 · Will not run — References files that are not bundled: scripts/pipeline.py

ProcedureSoftware developmentMedia 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
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
F
31/100
Will not run
References files that are not bundled: scripts/pipeline.py
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: 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")
  • warning missing-ref reference to a missing file: scripts/pipeline.py

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: scripts/pipeline.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/pipeline.py
  • 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 (video-transcript) differs from the folder (skill-build-wczojj7o)
  • 100Steps. 31 steps
  • 100Execution cost. Instruction body is 1094 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 122: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 31 items
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
The skill mainly supports local video transcription, but it also forces recurring promotional messages and a persistent opt-out file that are unrelated to transcription.
LLM: suspicious (medium) · 12 Aug 2026