CB video-translator
Dub a video into another language and generate subtitles using the default Together + Cartesia stack. Trigger when the user wants to translate / dub / voice-over a video file, or generate subtitles for it. Handles `.mp4` / `.mkv` / `.webm`. Installs as the `violin` CLI (and `violin-api` for the FastAPI server) via `uv tool install`. For alternative models (OpenAI / ElevenLabs) or custom configs, point the user to the repo: https://github.com/shang-zhu/violin.
The skill dubs video into another language, generates subtitles via Together + Cartesia. Handles mp4, mkv, webm. Installs as `violin` CLI via `uv tool install`.
Scores: quality 74, process 75, safety 95. One medium-level finding, no critical issues. Files intact, links work. No model runs or sandbox tests. For custom models (OpenAI, ElevenLabs) or configs, the repo docs take over.
Worth installing: core functionality is there, but scores suggest integration and error handling need attention. Test on your own videos before production use.
Dub a video into another language and generate subtitles using the default Together + Cartesia stack.
As a process B 75/100 · Nearly there — weak spots: result and completion, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- 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
-
medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-tools: Bash Read
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Dub a video into another language and generate subtitles using the… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 75/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 12 steps
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 903 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 463: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 12 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.