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AB bilibili-video-prompt-analyzer

Analyze Bilibili AI-generated videos to extract/reverse-engineer prompts for imitation and replication. Extracts frames, extracts subtitles, generates detailed ComfyUI/Seedance-format prompts with keyframe and scene breakdown ready for direct use. Use when you have a Bilibili AI video link and want production-ready prompts to generate similar videos.

ClawHub Agent Skills author: jilanfang v1.1.1 MIT-0 5 files · 3 scripts body ≈ 986 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 73/100 · Nearly there — weak spots: failures and branches, progress reporting

AnalyzerMedia and videoAI and agentstype 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
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
B
73/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
50
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: 5. 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 73/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 28 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 986 tokens
    • 100Running it twice. No mutating operations
    • low The response is described with custom markup (6 tags): a typed call is more reliable

    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
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 352: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 28 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)
    • +3All 3 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: clean
    This skill does what it says: it downloads a user-provided Bilibili video and extracts local frames/subtitles for prompt analysis, with ordinary media-download cautions.
    LLM: benign (high) · VirusTotal: · 29 May 2026