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AB flowcutpro

AI-powered cinematic video production using Google Veo 3 as the renderer and OpenClaw's configured LLM as the creative brain. Use when asked to create videos, animate concepts, generate Reels/TikToks, produce commercials, or turn any text concept into a stitched cinematic video. The LLM plans shots, writes optimized Veo 3 prompts, maintains style consistency, and runs a quality loop. Veo 3 renders. ffmpeg stitches. Triggers on: "make a video", "create a clip", "generate a reel", "produce a commercial", "animate this", "video generation", "FlowCutPro", "flowcutpro".

ClawHub Agent Skills author: windseeker1111 v1.0.0 MIT-0 5 files body ≈ 1 110 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: inputs and preconditions, failures and branches, running it twice

GeneratorMedia 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
93/100
safety, quality, tests
Safety 60%
92
Quality 40%
94
Run on models
none yet
Process rating
B
65/100
Nearly there
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

What is at stake

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

Secrets in code 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 someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.

For the author

The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.

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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • medium Secrets in code secret-google-key scripts/flowcutpro.py:18
      Google API key (quoted — discussed, not commanded)
      API_KEY  = os.environ.get("VEO_API_KEY", "AIza…VjI")
      quoted
    • low Secrets in code secret-high-entropy-token examples/hotel-commercial.py:20
      High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file; quoted — discussed, not commanded)
      API_KEY  = os.environ.get("VEO_API_KEY", "AIza…VjI")
      fixturequoted
    • low Secrets in code secret-google-key examples/hotel-commercial.py:20
      Google API key (test fixture / example file; quoted — discussed, not commanded)
      API_KEY  = os.environ.get("VEO_API_KEY", "AIza…VjI")
      fixturequoted
    • low Secrets in code secret-high-entropy-token scripts/flowcutpro.py:18
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      API_KEY  = os.environ.get("VEO_API_KEY", "AIza…VjI")
      quoted

    Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "install"

    Process rating: all ten parameters 65/100

    • 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
    • 30Running it twice. 2 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 26 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1110 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +3Description length 571: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 26 items
    • +3Output format is stated explicitly
    • +4Has examples (5 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.

    External checks

    ClawHub: suspicious
    FlowCutPro is a coherent video-generation skill, but it includes an embedded API key and under-discloses external provider and credential-handling risks.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026