SKILLEMALL.ai

AC video-bgm

Analyze a video's mood and add AI-generated BGM. Optionally speed up/slow down. Uses Gemini for video analysis and fal.ai Lyria2 for music generation. Triggers on "add bgm", "add music to video", "video bgm", or any request to add background music to a video file.

ClawHub Agent Skills author: Lucius Pang v1.0.2 MIT-0 2 files body ≈ 1 379 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 60/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, consistency

AnalyzerMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
60/100
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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 60/100

  • 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. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (video-bgm) differs from the folder (phy-video-bgm)
  • 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. 11 steps
  • 100Execution cost. Instruction body is 1379 tokens
  • low 10 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 264: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 11 items
  • +3Output format is stated explicitly
  • +4Has examples (10 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: suspicious
The skill does what it claims, but it should be reviewed because it can upload user videos to external AI services, remove original audio in outputs, and build shell commands from user-controlled values without clear validation guidance.
LLM: suspicious (high) · VirusTotal: suspicious · 28 May 2026