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BD video-analyzer

Parse local video files into transcript and AI analysis. Extract audio, transcribe with faster-whisper, analyze with AI.

ClawHub Agent Skills author: JeremyCooper2077 v1.0.0 MIT-0 4 files body ≈ 383 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Parse local video files into transcript and AI analysis.

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

AnalyzerMedia 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%
99
Quality 40%
75
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-password-literal scripts/analyze.js:14
    Hard-coded password / key literal (may be an example)
    const apiKey = cfg.env?.SU2…KEY;

Files scanned: 4. 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")

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 (video-analyzer) differs from the folder (jc-video-analyzer)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 14 steps
  • 100Execution cost. Instruction body is 383 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 120: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 14 items
  • +4Has examples (6 code blocks)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This skill performs the advertised video transcription and AI analysis workflow, but users should know the analysis step sends transcript text to a configured remote API.
LLM: benign (high) · VirusTotal: · 28 May 2026