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understand-explain skill

by Egonex-AI·Egonex-AI/Understand-Anything·84k stars·MIT

Use when you need a deep-dive explanation of a specific file, function, or module in the codebase

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Install the understand-explain skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.

git clone --depth 1 https://github.com/Egonex-AI/Understand-Anything.git /tmp/Understand-Anything
mkdir -p ~/.claude/skills
cp -r /tmp/Understand-Anything/understand-anything-plugin/skills/understand-explain ~/.claude/skills/understand-explain
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

/understand-explain

Provide a thorough, in-depth explanation of a specific code component.

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, dependson, configures, documents, deploys, triggers, containsflow, 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 $UADIR. Run UADIR=$([ -d .understand-anything ] && echo .understand-anything || echo .ua) — this is the legacy .understand-anything/ when it already exists, otherwise the new .ua/. Check that $UA_DIR/knowledge-graph.json exists. If not, tell the user to run /understand first.
  1. Check graph freshness before using graph-derived context:
  • Read project.gitCommitHash from the graph metadata as GRAPHCOMMITRAW. Resolve it as a commit before using it in any Git diff, then compare it with git rev-parse HEAD and inspect project-scoped committed and working-tree changes from the project root:
GRAPH_COMMIT=$(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 explaining that graph-derived context may omit those changes. Suggest: Run /understand to refresh the graph.
  • Run the commit diff only when GRAPHCOMMITRAW 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.
  1. Find the target node — use Grep to search the knowledge graph for the component: "$ARGUMENTS"
  • For file paths (e.g., src/auth/login.ts): search for "filePath" matches
  • For function notation (e.g., src/auth/login.ts:verifyToken): search for the function name in "name" fields filtered by the file path
  • Note the exact node id, type, summary, tags, and complexity
  1. Find all connected edges — Grep for the target node's ID in the edges section:
  • "source" matches → things this node calls/imports/depends on (outgoing)
  • "target" matches → things that call/import/depend on this node (incoming)
  • Note the connected node IDs and edge types
  1. Read connected nodes — for each connected node ID from step 4, Grep for those IDs in the nodes section to get their name, summary, and type. This builds the component's neighborhood.
  1. Identify the layer — Grep for the target node's ID in the "layers" section to find which architectural layer it belongs to and that layer's description.
  1. Read the actual source file — Read the source file at the node's filePath for the deep-dive analysis.
  1. Explain the component in context:
  • Its role in the architecture (which layer, why it exists)
  • Internal structure (functions, classes it contains — from contains edges)
  • External connections (what it imports, what calls it, what it depends on — from edges)
  • Data flow (inputs → processing → outputs — from source code)
  • Explain clearly, assuming the reader may not know the programming language
  • Highlight any patterns, idioms, or complexity worth understanding

More skills from Egonex-AI/Understand-Anything

  • AunderstandAnalyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships
  • Aunderstand-chatUse when you need to ask questions about a codebase or understand code using a knowledge graph
  • Aunderstand-dashboardLaunch the interactive web dashboard to visualize a codebase's knowledge graph
  • Aunderstand-diffUse when you need to analyze git diffs or pull requests to understand what changed, affected components, and risks
  • Aunderstand-domainExtract business domain knowledge from a codebase and generate an interactive domain flow graph. Works standalone (lightweight scan) or derives from an existing /understand knowledge graph.
  • Aunderstand-figmaAnalyze a Figma file via the Figma REST API and generate an interactive design knowledge graph (pages, screens, components, component sets, instances, design tokens) with a kind:"design" dashboard.
  • Aunderstand-knowledgeAnalyze a Karpathy-pattern LLM wiki knowledge base and generate an interactive knowledge graph with entity extraction, implicit relationships, and topic clustering.
  • Aunderstand-onboardUse when you need to generate an onboarding guide for new team members joining a project

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