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CC auto-video-generator

Professional REAL demo video generation with PM-driven scenario decomposition and region-aware recording. Uses Playwright native recording + bmad-agent-pm integration for intelligent video production.

ClawHub Hermes author: rosscui-chy v1.0.1 MIT-0 40 files · 18 scripts body ≈ 6 921 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Professional REAL demo video generation with PM-driven scenario decomposition and region-aware recording.

As a process C 58/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

GeneratorPlaywrightSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
C
81/100
safety, quality, tests
Safety 60%
99
Quality 40%
55
Run on models
none yet
Process rating
C
58/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
  3. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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
  • low Secrets in code secret-high-entropy-token templates/basic/landing-page-saas/index.html:127
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    background: url("data:image/svg+xml,%3Csvg width='60' height='60' viewBox='0 0 60 60' xmlns='http://www.w3.org/2000/svg'%3E%3Cg fill='none' fill-rule='evenodd'%3E%3Cg fill='%23ffffff' fill-opacity='0.
    quoted

Files scanned: 40. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 200 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • warning body-long SKILL.md body ≈ 6921 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"
  • note edit-residue the text marks something as outdated (lines 833): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 58/100

  • 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. 15 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 6921 tokens
  • 85Steps. 110 steps, 2 vague phrases
  • 100Result and completion. Output format and completion criterion are stated
  • 100Consistency. Name and required fields are in place
  • low 15 top-level sections: this looks like several domains in one skill

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)
  • -2localhost URLs: will not work for another user
  • -255 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 200: enough signal without eating the budget
  • +4Structure: 37 headings
  • +3Step-by-step instructions: 110 items
  • +3Output format is stated explicitly
  • +4Has examples (22 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.

External checks

ClawHub: suspicious
This skill is presented as a production video generator, but the inspected artifacts show simulated outputs plus several high-impact local and network exposure risks that need review before installation.
LLM: suspicious (high) · VirusTotal: · 16 Sept 2026