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Understand-Anything

by Lum1104 · Lum1104/Understand-Anything

Visual onboarding for any codebase — structural and domain knowledge graphs that teach the system instead of just diagramming it.

Understand-Anything turns codebases and knowledge bases into interactive graphs. Two-layer view: structural (files / functions / classes) and domain (business processes / data flows). Includes semantic search ('what handles auth?'), change-impact analysis, and adaptive detail levels. Built for new-team onboarding and architecture comprehension, not pretty pictures.

▶ Watch demo 📦 Install 💡 Use Cases

Why use it

Key features

Live Demo

What it looks like in practice

ready

Install

Author repository · Claude Skills documentation

Use Cases

Real-world ways to use Understand-Anything

Onboard a new engineer to a 200k-LOC codebase

👤 Tech leads onboarding hires, or solo devs adopting a project ⏱ ~60 min intermediate

When to use: New repo, you have a week to feel productive.

Flow
  1. Index the repo
    Use understand-anything. Build the structural graph for ./repo and the domain graph from /docs.✓ Copied
    → Graph stats (nodes, edges, density)
  2. Find core seams
    Highlight the 5 most-connected modules — likely architectural seams.✓ Copied
    → Ranked list with rationale
  3. Trace one feature
    Walk me through 'create checkout' end-to-end across structural + domain graphs.✓ Copied
    → Annotated path through nodes; explains business + technical hops

Outcome: Productive in days, not weeks; targeted reading instead of brute-force.

Pitfalls
  • Graph is so dense it's unreadable — Filter by directory or by feature; the skill supports adaptive detail levels
Combine with: filesystem

Predict change impact before opening a PR

👤 Devs about to touch shared code ⏱ ~25 min intermediate

When to use: You're about to refactor a module that 'feels load-bearing'.

Flow
  1. Define the change
    Use understand-anything. I'll change the signature of calculateTax(price, region) to add a customer_class. What breaks?✓ Copied
    → List of callers + tests that need updates
  2. Visualize the blast radius
    Show me the subgraph touched by this change.✓ Copied
    → Highlighted subgraph with severity per edge
  3. Plan the PR
    Propose a PR sequence that minimizes review surface — which files first?✓ Copied
    → Ordered file list with rationale

Outcome: PR sized for human review, not a 1500-line monster.

Pitfalls
  • Graph misses runtime-only callers (reflection, dynamic dispatch) — Cross-check with grep for the function name; mention runtime callers separately

Convert a wiki into a knowledge graph

👤 Researchers / teams with sprawling wikis ⏱ ~45 min intermediate

When to use: Your team has a 200-page wiki; nobody can find anything.

Flow
  1. Ingest pages
    Use understand-anything. Build a knowledge graph from /wiki/. Extract entities and implicit relationships.✓ Copied
    → Graph with entity types + relation types
  2. Find dead ends
    Which entities are referenced but never defined?✓ Copied
    → List of stub topics needing pages
  3. Suggest reorg
    Based on cluster structure, propose a 5-section TOC.✓ Copied
    → Section list with assigned pages

Outcome: Wiki you can actually navigate.

Pitfalls
  • Implicit relationships get noisy (every page mentions 'API') — Tune the extractor's stoplist; the skill exposes a config for common-noise terms
Combine with: filesystem

Combinations

Pair with other MCPs for X10 leverage

understand-anything-skill + filesystem

Persist generated graphs for team reuse

Save the graph to .claude/graphs/ and check in. Refresh on each main merge.✓ Copied
understand-anything-skill + git-mcp-idosal

Build a graph for a remote public repo without cloning locally

Use gitmcp for the repo source; pipe into understand-anything to build the graph in memory.✓ Copied

Tools

What this MCP exposes

ToolInputsWhen to callCost
build_structural_graph repo_path, languages? First step on a new repo 0
build_domain_graph docs_path Pair with structural for full picture 0
semantic_search intent_query 'What handles X?' — find by meaning 0
impact_analysis node_id, change_kind Pre-PR change assessment 0
feature_walkthrough feature_name Onboarding / educational mode 0

Cost & Limits

What this costs to run

API quota
None — local skill
Tokens per call
Graph build is cheap; queries return 200–1500 tokens depending on subgraph size
Monetary
Free
Tip
Build once per main, cache; rebuild on big refactors

Security

Permissions, secrets, blast radius

Minimum scopes: filesystem-read
Credential storage: None
Data egress: None

Troubleshooting

Common errors and fixes

Build is slow on a huge repo

Pass --include and --exclude to scope; skip generated/vendor dirs

Cross-language calls missing

Skill is best at one-language repos per pass; for polyglot, build separate graphs and link manually

Domain graph empty

/docs path didn't have content the extractor recognized; try with /README + /design-docs

Output too dense to read

Lower detail level; or filter to a feature subgraph instead of whole-graph view

Alternatives

Understand-Anything vs others

AlternativeWhen to use it insteadTradeoff
graphify-skillYou want a lighter-weight code-graph skillLess domain-graph capability
SourcegraphYou want enterprise-grade code search and a GUIPaid; setup overhead

More

Resources

📖 Read the official README on GitHub

🐙 Browse open issues

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