understand-onboard
Installation
Copy the prompt below and send it to your AI assistant (e.g. Claude Code) — it will follow the instructions and install automatically.
Install the "understand-onboard" skill by following the instructions at https://skill123.me/install/understand-onboard.
Run in your terminal — downloads and installs to ~/.claude/skills/.
curl -fsSL https://skill123.me/install/understand-onboard.sh | bash
Download the zip and extract it into your skills directory (e.g. ~/.claude/skills/), then restart your session.
⬇ Download v1.0.0 · 2 KBNot live-tested yet — this skill is rated on static analysis only.
About this skill
Use when you need to generate an onboarding guide for new team members joining a project
/understand-onboard
Generate a comprehensive onboarding guide from the project's knowledge graph.
Documentation
Use when you need to generate an onboarding guide for new team members joining a project
/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 $UA_DIR/knowledge-graph.json exists. If not, tell the user to run /understand first.
View full documentation
2. **Check graph freshness before using graph-derived context**:
- Read
project.gitCommitHashfrom the graph metadata asGRAPH_COMMIT_RAW. Resolve it as a commit before using it in any Git diff, then compare it withgit rev-parse HEADand inspect project-scoped committed and working-tree changes from the project root:
GRAPH_COMMIT=$(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
/understandto refresh the graph. - Run the commit diff only when
GRAPH_COMMIT_RAWresolves 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
Score breakdown
Assessment methodology
Version history
Imported from Egonex-AI/Understand-Anything@main