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Analyze

Organization
evidentloop
analyze

需求分析阶段入口；聚合评分、追问与范围判定规则，按需加载 references/assets/scripts。

Overview

Publisherevidentloop
Repositorysopify
Skill nameanalyze
Stars
368
Forks
30
Bundled files
4
LicenseApache-2.0
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by evidentloop on GitHub. Read the source before you install it.

Installation

Install the Analyze AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/evidentloop/sopify/tree/main/skills/zh/skills/sopify/analyze
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/evidentloop/sopify.git /tmp/sopify
mkdir -p .claude/skills
cp -r /tmp/sopify/skills/zh/skills/sopify/analyze .claude/skills/analyze
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analyze in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Analyze on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Analyze is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Analyze（入口文档）

先读证据，再把目标、交付物和候选路径分开。

何时激活

  • 进入需求分析阶段（workflow / plan_only）。
  • 需要做需求评分、追问或复杂度路由判定。

执行骨架

  1. 先加载 references/analyze-rules.md。
  2. 读取用户提供的材料和相关代码，区分目标、交付物与候选路径，再做完整性评分。
  3. 若评分不足，按 auto_decide 处理：
    • false：使用 assets/question-output.md 追问。
    • true：显式补充假设后继续。
  4. 评分达标后，交接已确认的成功标准、范围、证据和仍会影响结果的未知项。
  5. 输出阶段摘要，格式参考 assets/success-output.md。

资源导航

  • 长规则：references/analyze-rules.md
  • 共享写作规范：../references/shared-writing-dna.md（所有输出遵循）
  • 输出契约：../references/output-contract.md（必需 section、条件增强、自检）
  • 追问模板：assets/question-output.md
  • 达标输出模板：assets/success-output.md
  • 确定性评分脚本：scripts/score_requirement.py

确定性逻辑（脚本优先）

当需要可审计评分时，优先调用：

bash
python3 skills/zh/skills/sopify/analyze/scripts/score_requirement.py \
  --goal-clarity 2 \
  --expected-outcome 2 \
  --scope-boundary 1 \
  --constraints 1 \
  --require-score 7

脚本输出 JSON，包含：总分、阈值判定、缺失维度清单。

边界

  • 不在本技能直接生成方案包（交给 design）。
  • 不在本技能直接执行代码修改（交给 develop）。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Analyze AI skill do?

需求分析阶段入口；聚合评分、追问与范围判定规则，按需加载 references/assets/scripts。

Why use Analyze on TypingMind?

Because you install it once and use it with any model. Analyze is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Analyze in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/evidentloop/sopify/tree/main/skills/zh/skills/sopify/analyze. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Analyze?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Analyze?

As many as you like. As long as a model supports skills, you can use Analyze with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Analyze AI skill free?

Yes. It is published on GitHub by evidentloop under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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