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BD video-translator

Real time video translation / dubbing skill. Translate user-provided video (file or URL) and return preview_url. 适用于视频直译、视频翻译、视频配音、字幕翻译出片。

ClawHub Agent Skills author: papawaigo v1.0.0 MIT-0 5 files · 1 script body ≈ 332 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWriting and documentsMedia and videotype 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
B
83/100
safety, quality, tests
Safety 60%
98
Quality 40%
61
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: video-translator (ClawHub)

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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Exfiltration net-credential-use scripts/curl_examples.sh:77
    Credential used in a network call (verify the destination is the intended service) (test fixture / example file; quoted — discussed, not commanded)
    STATUS_RESP="$(curl -sS -H "Authorization: Bearer ${API_KEY}" "${BASE_URL}/video-trans/jobs/${JOB_ID}")"
    fixturequoted
  • low Exfiltration net-credential-use scripts/curl_examples.sh:87
    Credential used in a network call (verify the destination is the intended service) (test fixture / example file; quoted — discussed, not commanded)
    FINAL_RESP="$(curl -sS -H "Authorization: Bearer ${API_KEY}" "${BASE_URL}/video-trans/jobs/${JOB_ID}")"
    fixturequoted

Files scanned: 5. 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")

Process rating: all ten parameters 49/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (video-translator) differs from the folder (dubbing-hub)
  • 100Tools and files. No external tools needed
  • 100Steps. 35 steps
  • 100Execution cost. Instruction body is 332 tokens
  • 100Running it twice. No mutating operations

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
  • +4No input/output examples
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 138: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 35 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.

External checks

ClawHub: suspicious
The skill appears purpose-built for video translation, but it can send user videos or video URLs to an external service without clear disclosure or confirmation.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026