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免费AI模型配置领域负载物。标准化Agnes AI、智谱、商汤、小米、美团等平台的免费模型配置流程，支持文本/图像/视频/音频生成、语音识别（ASR）与信息图生成，及灵活多模态路径（单条、组合、批量生成与拼接）。核心：API Key管理、接口配置、模型选择、多模态生成（Agnes AI特有，采用基本命令组合复杂命令架构）、音频生成（简单合成+TTS语音合成）、语音识别与合成（ASR/TTS，含音色克隆/音色设计）。6域24种任务。触发词：模型配置、免费模型、API配置、模型设置、AI模型、图像生成、视频生成、音频生成、语音识别、语音合成、音色克隆、信息图生成、TTS配音、音视频合并、meta-skill-system。

ClawHub Agent Skills author: 波动几何 v1.0.7 MIT-0 15 files body ≈ 946 tokens Open the sourceclawhub.ai↗ analyzed 22 h ago

免费AI模型配置领域负载物。标准化Agnes AI、智谱、商汤、小米、美团等平台的免费模型配置流程，支持文本/图像/视频/音频生成、语音识别（ASR）与信息图生成，及灵活多模态路径（单条、组合、批量生成与拼接）。核心：API Key管理、接口配置、模型选择、多模态生成（Agnes…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationMedia 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
A
90/100
safety, quality, tests
Safety 60%
98
Quality 40%
79
Run on models
none yet
Process rating
D
46/100
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

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 Secrets in code secret-high-entropy-token scripts/agnes_gen.py:83
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    boundary = "----…0gW"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/agnes_gen.py:107
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    boundary2 = "----…0gW"
    quoted

Files scanned: 15. 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 46/100

  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 66 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 946 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 313: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 66 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 4 scripts are documented

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

External checks

ClawHub: suspicious
The skill is mostly aligned with AI model setup and media generation, but it includes review-worthy behavior: a safety-override instruction and automatic public upload of local images.
LLM: suspicious (high) · 10 Sept 2026