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Eleven-MEleven-M/flowmind/skills/offline-design-analysis/SKILL.md

offline-design-analysis

Skill1 starsChanged 3 months agoMITView on GitHub

Analyze local learning history, Markdown/HTML/Lake/Lakebook documents, and repository code without an AI model. Use for natural-language requests to summarize code or documents, recover historical design rules, explain a module, or generate an evidence-backed design/business flow when AI is unavailable or offline execution is requested.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Treat generated flow as a discovery aid, not proof of unstated business semantics.

    line 22
  2. Distinctive:

    Never execute analyzed code or include credential values.

    line 23

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Offline Design Analysis

Analyze only local material with FlowMind's deterministic parser and ranker. Do not call a model or network service.

Workflow

  1. Resolve the synchronized FlowMind source directory and requested repository directory.
  2. Parse bounded supported files and sanitized learning records.
  3. Rank evidence using natural-language terms and RESOURCE_INDEX.md metadata.
  4. Extract headings, explicit rules, ordered steps, code symbols, endpoints, data/cache keys, and message names.
  5. Return the design flow, summaries, citations, confidence, limitations, and test focus.

Evidence rules

  • Preserve the local relative path for every conclusion.
  • Report low confidence when evidence is sparse or the requested relationship is not explicit.
  • Treat generated flow as a discovery aid, not proof of unstated business semantics.
  • Never execute analyzed code or include credential values.

Trigger Patterns

"离线分析", "无模型分析", "不用AI分析", "没有AI模型"
"分析历史资料", "分析学习资料", "历史设计总结"
"总结代码", "代码总结", "分析文档", "文档总结"
"生成设计流程", "梳理设计流程", "本地资料分析"
"分析流程", "业务流程分析", "分析业务逻辑", "梳理调用链路"
"offline analysis", "without AI", "summarize local code"

Examples

离线分析历史资料和代码，总结门店搜索的设计流程
没有 AI 模型，帮我分析 sourceDir=/data/source repo=/work/service 的合同续约逻辑
总结本地文档中的业务规则并给出证据来源
分析下当前合同校验额度的流程

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Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

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