Understand Explain

egonex-ai/understand-anything/understand-anything-plugin/skills/understand-explain

作者 egonex-ai790b15702863无许可证85K 个星标收录于 2026年10月8日更新于 2026年10月8日仓库2天前更新

Use when you need a deep-dive explanation of a specific file, function, or module in the codebase

AI 生成的概览

借助预构建的知识图谱及其源代码,解释代码库中某个文件、函数或模块。

功能
该技能针对某一个代码组件(如文件、函数、类或模块)生成深入说明。它会在知识图谱 JSON 中定位该组件,收集其关联边、所属分层和相邻节点,然后读取实际源文件,说明其架构角色、内部结构、依赖关系和数据流。它还会检查图谱相对于当前 Git 提交是否过期,并在可能遗漏项目改动时给出提醒。
适用场景
当需要深入解释代码库中某个特定文件、函数或模块时使用。适用于新人上手、代码理解和了解某组件与项目其余部分的关联。它依赖已有的知识图谱,因此不适用于尚未分析过的项目。
运行要求
需要已有的知识图谱,位于 .ua/knowledge-graph.json 或旧版 .understand-anything/knowledge-graph.json,由单独的 /understand 步骤生成。它使用 Grep 和文件读取,并可选地使用 Git 命令检查图谱新鲜度;Git 元数据为尽力而为,缺失时不会阻止解释。它不附带任何脚本。

/understand-explain

Provide a thorough, in-depth explanation of a specific code component.

Graph Structure Reference

The knowledge graph JSON has this structure:

  • project — {name, description, languages, frameworks, analyzedAt, gitCommitHash}
  • nodes[] — each has {id, type, name, filePath?, summary, tags[], complexity, languageNotes?}
    • Code node types: file, function, class, module, concept
    • Non-code node types: config, document, service, table, endpoint, pipeline, schema, resource
    • Domain/knowledge node types: domain, flow, step, article, entity, topic, claim, source
    • IDs use the node type as prefix, e.g. file:path, function:path:name, config:path, article:path
  • edges[] — each has {source, target, type, direction, weight}
    • Key types: imports, contains, calls, depends_on, configures, documents, deploys, triggers, contains_flow, flow_step, related, cites
  • layers[] — each has {id, name, description, nodeIds[]}
  • tour[] — each has {order, title, description, nodeIds[]}

How to Read Efficiently

  1. Use Grep to search within the JSON for relevant entries BEFORE reading the full file
  2. Only read sections you need — don't dump the entire graph into context
  3. Node names and summaries are the most useful fields for understanding
  4. Edges tell you how components connect — follow imports and calls for dependency chains

Instructions

  1. Resolve the data directory $UA_DIR. Run UA_DIR=$([ -d .understand-anything ] && echo .understand-anything || echo .ua) — this is the legacy .understand-anything/ when it already exists, otherwise the new .ua/. Check that $UA_DIR/knowledge-graph.json exists. If not, tell the user to run /understand first.

  2. Check graph freshness before using graph-derived context:

    • Read project.gitCommitHash from the graph metadata as GRAPH_COMMIT_RAW. Resolve it as a commit before using it in any Git diff, then compare it with git rev-parse HEAD and inspect project-scoped committed and working-tree changes from the project root:
      bash
      GRAPH_COMMIT=$(git rev-parse --verify --end-of-options "${GRAPH_COMMIT_RAW}^{commit}" 2>/dev/null)git rev-parse HEADgit diff --name-only "$GRAPH_COMMIT" HEAD -- .git diff --cached --name-only -- .git diff --name-only -- .git ls-files --others --exclude-standard -- .
    • The -- . pathspec is required: commits that only touch a sibling monorepo project must not make this graph stale. A hash mismatch alone is not stale when the project diff is empty.
    • Ignore the selected data directory (.ua/ or legacy .understand-anything/) in every command's output because it contains generated graph artifacts, not project source drift.
    • If the committed diff or any working-tree command reports project files, warn before explaining that graph-derived context may omit those changes. Suggest: Run /understand to refresh the graph.
    • Run the commit diff only when GRAPH_COMMIT_RAW resolves successfully. If the graph commit or Git metadata is missing, invalid, or unavailable, give a brief best-effort warning and continue instead of blocking.
  3. Find the target node — use Grep to search the knowledge graph for the component: "$ARGUMENTS"

    • For file paths (e.g., src/auth/login.ts): search for "filePath" matches
    • For function notation (e.g., src/auth/login.ts:verifyToken): search for the function name in "name" fields filtered by the file path
    • Note the exact node id, type, summary, tags, and complexity
  4. Find all connected edges — Grep for the target node's ID in the edges section:

    • "source" matches → things this node calls/imports/depends on (outgoing)
    • "target" matches → things that call/import/depend on this node (incoming)
    • Note the connected node IDs and edge types
  5. Read connected nodes — for each connected node ID from step 4, Grep for those IDs in the nodes section to get their name, summary, and type. This builds the component's neighborhood.

  6. Identify the layer — Grep for the target node's ID in the "layers" section to find which architectural layer it belongs to and that layer's description.

  7. Read the actual source file — Read the source file at the node's filePath for the deep-dive analysis.

  8. Explain the component in context:

    • Its role in the architecture (which layer, why it exists)
    • Internal structure (functions, classes it contains — from contains edges)
    • External connections (what it imports, what calls it, what it depends on — from edges)
    • Data flow (inputs → processing → outputs — from source code)
    • Explain clearly, assuming the reader may not know the programming language
    • Highlight any patterns, idioms, or complexity worth understanding

来源与署名

来源:egonex-ai/understand-anything位于understand-anything-plugin/skills/understand-explain提交790b157

许可证: 无许可证

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