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BC byted-mediakit-tools

火山引擎 AI MediaKit 音视频处理工具集，提供视频理解、音频提取、视频剪辑、音视频拼接、画质增强、文生视频、音视频合成等能力。当用户提及音频剪辑、视频剪辑、音视频拼接、文生视频、音频提取、画质增强、视频理解、音视频合成、媒体裁剪等需求时必须调用本Skill。当用户需要视频理解时，宿主agent必须自动解析用户的具体要求作为prompt参数传入，同时传入视频URL和fps参数；max_frames 为可选参数。

ClawHub Agent Skills author: Volc-AI-MediaKit v1.0.0 MIT-0 24 files · 1 script body ≈ 1 584 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype 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
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
C
53/100
Has gaps
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

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: 24. 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 "display_name"
  • note frontmatter-key unknown frontmatter key "permissions"
  • note frontmatter-key unknown frontmatter key "env"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 13 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1584 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
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 211: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 13 items
  • +4Has examples (14 code blocks)
  • +4Reference files are cited in the instructions (9 of 9)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
This media-processing skill appears legitimate, but it deserves review because it can send media URLs and prompts to external services and tells agents to persist API secrets locally.
LLM: suspicious (high) · VirusTotal: · 29 May 2026