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Onboarding Guide Generator

Free

Create onboarding guides from project knowledge graphs.

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Free · Opens the source repo

What Onboarding Guide Generator does

The Onboarding Guide Generator is a tool designed to streamline the onboarding process for new team members by automatically generating comprehensive guides based on a project's knowledge graph. This skill processes a structured JSON file that encapsulates vital project information, including its name, description, languages, frameworks, and various nodes representing code and non-code components. By leveraging this structured data, the skill produces a well-organized onboarding document that highlights key aspects of the project, making it easier for newcomers to understand their roles and responsibilities.

To use the Onboarding Guide Generator, users must first ensure that the knowledge graph is up to date by checking the associated Git commit hash. This ensures that the generated guide reflects the most current state of the project. The skill then extracts essential metadata, layers, and guided tour steps from the graph, providing a clear overview of the project's architecture and important concepts. The guide includes sections such as Project Overview, Architecture Layers, Key Concepts, Guided Tour, File Map, and Complexity Hotspots, all formatted in clean markdown for easy readability.

This skill is particularly beneficial for development teams working on complex projects where new hires may struggle to grasp the architecture and workflows. By automating the creation of onboarding materials, teams can save time and ensure that all relevant information is consistently presented to new members. The Onboarding Guide Generator is an excellent addition for teams looking to enhance their onboarding process and improve knowledge transfer within the organization.

When to use it

Use this skill when onboarding new team members to ensure they have a structured guide that reflects the current state of the project.

When not to use it

This skill may not be suitable for projects without a well-defined knowledge graph or for teams that prefer personalized onboarding experiences.

What you can build with it

New Team Member Onboarding

Use the skill to generate an onboarding guide for new hires, providing them with essential project information and resources.

Project Documentation Updates

When significant changes occur in the project, run the skill to create an updated onboarding guide that reflects the latest architecture and components.

Knowledge Transfer for Remote Teams

Facilitate knowledge transfer in remote teams by providing a clear, structured onboarding guide that can be accessed anytime.

How to install Onboarding Guide Generator

View source

1. Install with the skills CLI

npx skills add egonex-ai/understand-anything/understand-onboard --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by egonex-ai

/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/ONBOARDING.md in the project

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

Frequently asked questions about Onboarding Guide Generator

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