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understand-onboard

Helps your agent create a welcome guide for new team members. It organizes essential information to get started.

What it does

Generates an onboarding guide for new team members joining a project. It uses project information like code structure and documentation to create a learning roadmap.

When to use it

  • ✓When starting a new project with colleagues.
  • ✓When a new member joins the team.
  • ✓To organize existing project knowledge.

Example of what to ask your AI

“Create an onboarding guide for project 'X' based on the current knowledge.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/Egonex-AI/Understand-Anything/blob/main/understand-anything-plugin/skills/understand-onboard/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/Egonex-AI/Understand-Anything/blob/main/understand-anything-plugin/skills/understand-onboard/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The agent analyzes the project's files to understand its structure, code, and documentation. It then organizes this information into an easy-to-follow guide.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add Egonex-AI/Understand-Anything --skill understand-onboard

Or download just the file:

curl -L https://raw.githubusercontent.com/Egonex-AI/Understand-Anything/main/understand-anything-plugin/skills/understand-onboard/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

/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)

…

FAQ

What is a 'knowledge graph'?

It's a representation of the project's information, like files, functions, and their connections, which the agent uses to understand the project.

What are 'layers' and 'tour'?

'Layers' organize the project's architecture. 'Tour' is a suggested roadmap for learning about the project.

What happens if the project code changes?

The agent checks if the code has changed since the last analysis. If there are significant changes, it warns that the guide might not be fully up-to-date and suggests refreshing the analysis.

Details

Original description by the author

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

repo: Egonex-AI/Understand-Anything

Popularity

GitHub stars
87k
Ranking position
#847
License
MIT
Updated
10/12/2026

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