/understand-explain
SkillFiles & storageOnce added, your AI can give you a clear, in-depth explanation of any file, function, or module in your codebase. Ask about a specific piece of code and get an answer that accounts for how it fits with the rest of your project. Useful for making sense of code you did not write.
Available today. Use it from your connected AI after setup.
No other account needed.
After adding it, ask your AI to explain the file, function, or module you want to understand. Point it at any part of your codebase whenever you need a deeper explanation.
Then ask your AI: use the /understand-explain skill
What your AI can do with it
- Explain what any file in your codebase does
- Break down what a specific function does
- Walk through how a whole module works
- Show how a piece of code fits with the surrounding 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-explain/SKILL.md and read by ahel’s review.
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, 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
- Use Grep to search within the JSON for relevant entries BEFORE reading the full file
- Only read sections you need — don't dump the entire graph into context
- Node names and summaries are the most useful fields for understanding
- Edges tell you how components connect — follow imports and calls for dependency chains
Instructions
-
Resolve the data directory
$UA_DIR. RunUA_DIR=$([ -d .understand-anything ] && echo .understand-anything || echo .ua)— this is the legacy.understand-anything/when it already exists, otherwise the new.ua/. Check that$UA_DIR/knowledge-graph.jsonexists. If not, tell the user to run/understandfirst. -
Check graph freshness before using graph-derived context:
- Read
project.gitCommitHashfrom the graph metadata asGRAPH_COMMIT_RAW. Resolve it as a commit before using it in any Git diff, then compare it withgit rev-parse HEADand inspect project-scoped committed and working-tree changes from the project root:GRAPH_COMMIT=$(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 explaining that graph-derived context 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.
- Read
-
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, andcomplexity
- For file paths (e.g.,
-
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
-
Read connected nodes — for each connected node ID from step 4, Grep for those IDs in the nodes section to get their
name,summary, andtype. This builds the component's neighborhood. -
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. -
Read the actual source file — Read the source file at the node's
filePathfor the deep-dive analysis. -
Explain the component in context:
- Its role in the architecture (which layer, why it exists)
- Internal structure (functions, classes it contains — from
containsedges) - 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
Signals
- GitHub stars
- 82k
- Forks
- 7k
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
understand-explain- Source
- github.com/egonex-ai/understand-anything