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understand-onboard

Create an onboarding guide for new project members from a knowledge graph, a map of project components. The Markdown guide covers architecture, key concepts, a suggested learning path, important files, and areas that need extra care.

OriginalShow the original description

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

Run score Not tested

See how to install

Good for

  • Preparing a guide for new team members
  • Organizing project architecture and key files
  • Planning a codebase walkthrough
  • Sharing areas that need extra care

Overview

What it does

Creates a Markdown onboarding guide from a project's knowledge graph to help new members understand the project. The guide brings together a project overview, architectural layers, key concepts, a step-by-step tour, the roles of important files, and complex areas that require care. It focuses on larger structures such as files and services rather than function-level details.

When it helps

Use it to prepare the first document developers read when joining a team. It can suggest an order for reading the code and bring explanations that vary between team members into one shared reference. Complexity information also helps communicate which areas should be handled carefully.

Example requests

  • “Summarize the architecture and key files for new team members.”
  • “Create an onboarding guide with a learning sequence and areas that need extra care.”

Notes

You need knowledge-graph.json, created beforehand with /understand. The skill checks changes made since the graph was created and warns if some content is not reflected. After generating the guide, it offers to save it to docs/UA_ONBOARDING.md and suggests committing it so the team can share it.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Document check

AI checked the SKILL.md for operations that need care and for setup requirements. The score comes only from actually running the skill (hands-on test).

SafetyAre sending data, deleting files, and running commands disclosed?
AGoodIt inspects Git and the graph, and only offers to save the guide to docs/UA_ONBOARDING.md.
Easy setupDoes it need few tools or API keys, and are they documented?
AGoodIt specifies the required knowledge-graph.json location and directs users to /understand when it is missing.

Not counted in the score. Rated by AI (OpenAI Codex) as of Oct 21, 2026. Treat it as a guide and read the original before installing.

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Files included (1)

  • SKILL.md4.9 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

/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:
      GRAPH_COMMIT=$(git rev-parse --verify --end-of-options "${GRAPH_COMMIT_RAW}^{commit}" 2>/dev/null)
      git rev-parse HEAD
      git 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

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