About

Imported from lzy18001500226/MoSim (References/Agent/Skills/AutoSkill/SkillBank/ConvSkill/chinese_gpt4_8_GLM4.7/self-sop_extraction/SKILL.md). Install upstream with npx skills add lzy18001500226/MoSim --skill self-sop_extraction. Copyright stays with the author.

self / sop_extraction

Name: self / sop_extraction
Author: lzy18001500226

General SOP for extracting and structuring processes or checklists from conversation evidence.

Prompt

Follow this SOP to extract and structure processes from conversation evidence (replace specifics with placeholders like //):

Identify the Offline OpenAI-format conversation source.
Note the Title/ID of the conversation.
Use the user questions provided as the PRIMARY extraction evidence.
Use the full conversation context as SECONDARY reference.
In the full conversation section, assistant/model replies are reference-only and not skill evidence.
Primary User Questions (main evidence): [Extract from context]
Configuration/Context Details: [Extract from context]

For each step, include: action, checks, and failure rollback/fallback plan. Output format: for each step number, provide status/result and what to do next.

Triggers

Use when the user asks for a process or checklist.
Use when you want to reuse a previously mentioned method/SOP.

Examples

Example 1

Input:

Break this into best-practice, executable steps.

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml

targets:
  - https://api.opensmartroute.ai/api/v1/registry/lzy18001500226-mosim-self-sop-extraction/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

lzy18001500226-mosim-self-sop-extraction.ocm.jsonjson

{
  "ocm": "1",
  "id": "lzy18001500226-mosim-self-sop-extraction",
  "kind": "skill",
  "name": "self / sop_extraction",
  "description": "General SOP for extracting and structuring processes or checklists from conversation evidence.",
  "publisher": "lzy18001500226",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "general"
    ],
    "tags": [
      "skill-md",
      "self",
      "sop",
      "extraction",
      "process",
      "checklist",
      "github"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "General SOP for extracting and structuring processes or checklists from conversation evidence."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "github",
      "repository": "https://github.com/lzy18001500226/MoSim",
      "path": "References/Agent/Skills/AutoSkill/SkillBank/ConvSkill/chinese_gpt4_8_GLM4.7/self-sop_extraction/SKILL.md",
      "ref": "e0ec177d00f087cb04e90206b2f7d3aa2f5a1350",
      "url": "https://github.com/lzy18001500226/MoSim/blob/e0ec177d00f087cb04e90206b2f7d3aa2f5a1350/References/Agent/Skills/AutoSkill/SkillBank/ConvSkill/chinese_gpt4_8_GLM4.7/self-sop_extraction/SKILL.md",
      "key": "lzy18001500226/MoSim/References/Agent/Skills/AutoSkill/SkillBank/ConvSkill/chinese_gpt4_8_GLM4.7/self-sop_extraction/SKILL.md"
    }
  },
  "instructions": "# self / sop_extraction\n\nGeneral SOP for extracting and structuring processes or checklists from conversation evidence.\n\n## Prompt\n\nFollow this SOP to extract and structure processes from conversation evidence (replace specifics with placeholders like <PROJECT>/<ENV>/<VERSION>):\n1) Identify the Offline OpenAI-format conversation source.\n2) Note the Title/ID of the conversation.\n3) Use the user questions provided as the PRIMARY extraction evidence.\n4) Use the full conversation context as SECONDARY reference.\n5) In the full conversation section, assistant/model replies are reference-only and not",
  "cost": {
    "context_tokens": 278
  }
}

Fetch it by URL: GET /api/v1/registry/lzy18001500226-mosim-self-sop-extraction/manifest?version=1.0.0

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