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pipeline-guard
// Validates and optimizes run_pipeline DOT graphs with model selection from QoS catalog
// Validates and optimizes run_pipeline DOT graphs with model selection from QoS catalog
Recursively crawl websites using headless Chrome. Triggers: crawl, scrape website, 爬取, crawl site, deep crawl, website content.
OminiX ASR (speech-to-text), preset-voice TTS with emotion/speed control, and model management via Qwen3 models on Apple Silicon. For voice cloning and custom voice profiles, use mofa-fm. Triggers: voice, transcribe audio, text to speech, speak this, read aloud, model management, download model, 语音识别, 语音合成, 模型管理.
Deep multi-round web research with parallel fetching. Triggers: deep search, research, 深度搜索, 调研, investigate, deep research.
Manage sub-accounts under the current profile. Triggers: create account, 创建账号, sub account, manage account, list accounts, 子账号.
Send emails via SMTP or Feishu/Lark Mail. Triggers: send email, 发邮件, email to, 发送邮件, mail, send mail.
Get current weather for any city worldwide. Triggers: weather, forecast, temperature, 天气, 气温, how cold, how hot, is it raining, wind.
| name | pipeline-guard |
| description | Validates and optimizes run_pipeline DOT graphs with model selection from QoS catalog |
| version | 0.1.0 |
| author | octos |
| always | true |
Automatically validates DOT graphs and assigns optimal models before run_pipeline executes.
This is a lifecycle hook — it runs transparently before every pipeline execution.
model_catalog.json scores and assigns:
The LLM writes DOT graphs without model= attributes. This hook injects them automatically based on live QoS scores.