/understand-onboard

SkillDev tools

Lets your agent generate an onboarding guide for new team members joining a project.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the /understand-onboard skill

About this capability

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

What this skill tells your AI

The instructions your AI receives, as published by egonex-ai/understand-anything in understand-anything-plugin/skills/understand-onboard/SKILL.md and read by ahel’s review.

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

Signals

GitHub stars
82k
Forks
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Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
understand-onboard
Source
github.com/egonex-ai/understand-anything