skill-metadata.json
{
"documents": {
"SKILL.md": {
"kind": "entrypoint",
"title": "Deepline Monitors",
"tags": [
"recipe"
],
"providers": []
}
}
}
code.deepline.com · 공식 웹
ACCESS-GATED 베타. Deepline 모니터는 데이터 웨어하우스로 스트리밍되어 플레이를 트리거하는 공급자 이벤트 피드(채용 공고, 이메일 회신, 자금 조달, 의향)입니다. 모니터 액세스 권한이 있는 경우에만 사용하십시오: 먼저 `deepline monitors status`를 실행하십시오. 액세스 권한이 없다고 표시되면 이 레시피를 사용하지 마시고, 사용자에게 Deepline 팀에 문의하도록 안내하십시오.
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skill-metadata.json{
"documents": {
"SKILL.md": {
"kind": "entrypoint",
"title": "Deepline Monitors",
"tags": [
"recipe"
],
"providers": []
}
}
}
SKILL.md--- name: deepline-monitors description: "ACCESS-GATED beta. Deepline Monitors are provider event feeds (job posts, email replies, funding, intent) that stream into your warehouse and trigger plays. Only use if you have monitor access: run `deepline monitors status` first; if it reports no access, do NOT use this recipe — tell the user to contact the Deepline team." --- # Deepline Monitors ## Quick Start ```bash npm install -g deepline # Fallback for secure sandboxes: mkdir -p "$HOME/.local" && npm config set prefix "$HOME/.local" && export PATH="$HOME/.local/bin:$PATH" && npm install -g deepline --registry https://code.deepline.com/api/v2/npm/ deepline auth register --wait auto deepline auth wait --timeout 120 # completes Cowork/browser approval; no-op if already connected deepline auth status deepline -h ``` This is a recipe shortcut. It pre-selects the deepline-monitors recipe but the **deepline-gtm governs the entire session**. ## Execution order 1. **Invoke `deepline-gtm`** using the Skill tool. 2. **Follow the meta-skill's full routing instructions** - analyze the user's complete prompt and load every sub-doc the meta-skill tells you to. Do not skip docs just because a recipe is pre-selected. 3. **Follow the meta-skill's routing gate for this recipe.** Read the deepline-monitors recipe at `../deepline-gtm/recipes/deepline-monitors.md` (relative to this file) only when that gate routes you to it. Conditional access and safety checks still apply. The recipe only covers one part of the task. The meta-skill handles everything else the user asked for.