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AC youtube-publishing-and-metadata

The YouTube publish-metadata skill. Use when someone wants to "write a YouTube title/description," "set tags/category/privacy," "optimize YouTube SEO/metadata," set made-for-kids, or publish a YouTube video via WoopSocial. Writes the metadata (title, description+chapters, tags) and sets category/privacy/madeForKids — YouTube is a search engine, so metadata is the launchpad, and madeForKids is a COPPA/FTC legal flag set truthfully. Uses the INDEX framework. Reads brand-profile + goals-and-kpis + the script/video first. The video file + script are inputs (not WoopSocial); the thumbnail and A/B title testing are native YouTube Studio; WoopSocial publishes via the YouTube fields; metrics never fabricated. Distinct from youtube-long-form/youtube-shorts (the script) and thumbnail-design (the thumbnail).

ClawHub Agent Skills author: Social Media Skills v1.0.0 MIT-0 7 files body ≈ 1 360 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

The YouTube publish-metadata skill.

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorYouTubeMedia 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
C
54/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 54/100

    • 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
    • 30Running it twice. 15 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 85Steps. 11 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1360 tokens
    • low No test case covers injection arriving through data

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 808: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 11 items
    • +4Reference files are cited in the instructions (4 of 4)

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

    External checks

    ClawHub: clean
    This skill is a clearly scoped YouTube metadata and publishing helper, with its publishing-related actions disclosed and bounded to the expected workflow.
    LLM: benign (high) · VirusTotal: · 24 Jul 2026