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BD Video Analyzer Skill

name: video-analyzer version: 1.0.10 description: 鏅鸿兘鍒嗘瀽 Bilibili/YouTube/鏈湴瑙嗛锛岀敓鎴愯浆鍐欍€佽瘎浼板拰鎬荤粨銆傛敮鎸佸叧閿抚鎴浘鑷姩宓屽叆銆? author: user tags: [video, transcription, analysis, bilibili, youtube, ai]

modbender/skill-library-mcp Agent Skills author: modbender MIT 31 files body ≈ 972 tokens Open the sourcegithub.com↗ analyzed 2 d ago

name: video-analyzer version: 1.0.10 description: 鏅鸿兘鍒嗘瀽 Bilibili/YouTube/鏈湴瑙嗛锛岀敓鎴愯浆鍐欍€佽瘎浼板拰鎬荤粨銆傛敮鎸佸叧閿抚鎴浘鑷姩宓屽叆銆? author: user tags: [video…

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerYouTubeMedia 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%
95
Quality 40%
79
Run on models
none yet
Process rating
D
44/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Obfuscation medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.

For the author

Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.

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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • medium Obfuscation uni-mixed-script-word SKILL.md:135
      Word mixing Latin and Cyrillic letters (homoglyph obfuscation) (1 occurrence)
      - 澶фā鍨嬶紙large-v2锛夌簿搴﹂珮浣嗛€熷害鎱紝灏忔ā鍨嬶紙small锛夐€熷害蹇絾绮惧害杈冧綆

    Files scanned: 30. 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)

    Process rating: all ten parameters 44/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 6 mutating operations with no state check
    • 40Consistency. Frontmatter name (Video Analyzer Skill) differs from the folder (video-analyzer)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (python, node) that frontmatter does not declare
    • 100Steps. 51 steps
    • 100Execution cost. Instruction body is 972 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 192: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 51 items
    • +4Has examples (3 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.