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AB youtube-transcript

Use when the user wants a YouTube video's transcript fetched, wants to summarize/analyze/quote a YouTube video by its spoken content, wants to search YouTube (globally or a channel handle's videos), wants a channel handle resolved to its channel ID, or wants the videos in a YouTube playlist. Calls the getyoutubetranscript.com public API - requires an API key (free tier available, no card required).

ClawHub Agent Skills author: TubeAgentKit v1.0.3 MIT-0 9 files · 7 scripts body ≈ 2 294 tokens Open the sourceclawhub.ai↗ analyzed 8 h ago

Use when the user wants a YouTube video's transcript fetched, wants to summarize/analyze/quote a YouTube video by its spoken content, wants to search YouTube…

As a process B 72/100 · Nearly there — weak spots: result and completion

IntegrationYouTubeMedia 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
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
B
72/100
Nearly there
Result and completion w 14
0
Tools and files w 18
60
When it triggers w 12
70
the three weakest of ten parameters · all ten

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 · 0

    ✓ No critical or high findings

    Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "source"

    Process rating: all ten parameters 72/100

    • 0Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 8 steps
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2294 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    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 401: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 8 items
    • +4Has examples (6 code blocks)
    • +3All 7 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    The skill mostly matches its YouTube transcript purpose, but its account-signup shell examples handle user input unsafely enough to require review before installation.
    LLM: suspicious (high) · 12 Sept 2026