Understand Onboard

作者 egonex-ai790b15702863無授權條款85K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫2 天前更新

Use when you need to generate an onboarding guide for new team members joining a project

AI 產生的概覽

依據專案知識圖譜,為新成員產生 Markdown 格式的上手引導文件。

功能
讀取專案知識圖譜 JSON(專案中繼資料、分層、導覽與檔案層級節點),產出結構化的上手引導。指南涵蓋專案概觀、架構分層、關鍵概念、引導式導覽、檔案地圖與複雜度熱點。它也會用 Git 歷史檢查圖譜是否過期,並提議將結果儲存到 docs/UA_ONBOARDING.md。
適用情境
適用於新成員加入專案、需要一份入門說明文件的情境。適合已產生知識圖譜、希望取得分層的高階導覽而非程式碼層級細節的專案。
執行需求
需要已存在的知識圖譜檔案 .ua/knowledge-graph.json 或舊版 .understand-anything/knowledge-graph.json,由獨立的 /understand 步驟產生。使用 Git 指令檢查圖譜新舊,並以 Grep/Read 擷取圖譜內容。不隨附指令碼,僅為指示。

/understand-onboard

Generate a comprehensive onboarding guide from the project's knowledge graph.

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 generating the guide that onboarding content 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. Read project metadata — use Grep or Read with a line limit to extract the "project" section (name, description, languages, frameworks).

  4. Read layers — Grep for "layers" to get the full layers array. These define the architecture and will structure the guide.

  5. Read the tour — Grep for "tour" to get the guided walkthrough steps. These provide the recommended learning path.

  6. Read file-level structural nodes only — use Grep to find nodes with file-level types (file, config, document, service, pipeline, table, schema, resource, endpoint) in the knowledge graph. Skip function-level and class-level nodes to keep the guide high-level. Extract each node's name, filePath, summary, and complexity.

  7. Identify complexity hotspots — from the file-level nodes, find those with the highest complexity values. These are areas new developers should approach carefully.

  8. Generate the onboarding guide with these sections:

    • Project Overview: name, languages, frameworks, description (from project metadata)
    • Architecture Layers: each layer's name, description, and key files (from layers + file nodes)
    • Key Concepts: important patterns and design decisions (from node summaries and tags)
    • Guided Tour: step-by-step walkthrough (from the tour section)
    • File Map: what each key file does (from file-level nodes, organized by layer)
    • Complexity Hotspots: areas to approach carefully (from complexity values)
  9. Format as clean markdown

  10. Offer to save the guide to docs/UA_ONBOARDING.md in the project

  11. Suggest the user commit it to the repo for the team

來源與署名

來源:egonex-ai/understand-anything位於understand-anything-plugin/skills/understand-onboard提交790b157

授權條款: 無授權條款

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