Token-optimized structural code search using tree-sitter AST parsing. Use instead of reading full files when you need to understand code structure, find functions, or explore a codebase efficiently.
Install
The skill file stays in the publisher's repository.
Paste the copied command in a terminal. It installs this SKILL.md into that agent.
npx skills add thedotmack/claude-mem --skill smart-explore -a cursor -y
Download plugin/skills/smart-explore/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does smart-explore live?
The publisher keeps it at https://github.com/thedotmack/claude-mem.
Which agents can use smart-explore?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.
Token-optimized structural code search using tree-sitter AST parsing. Use instead of reading full files when you need to understand code structure, find functions, or explore a codebase efficiently.
name: smart-explore
description: Token-optimized structural code search using tree-sitter AST parsing. Use instead of reading full files when you need to understand code structure, find functions, or explore a codebase efficiently.
Smart Explore
Structural code exploration using AST parsing. This skill overrides your default exploration behavior. While this skill is active, use smart_search/smart_outline/smart_unfold as your primary tools instead of Read, Grep, and Glob.
Core principle: Index first, fetch on demand. Give yourself a map of the code before loading implementation details. The question before every file read should be: "do I need to see all of this, or can I get a structural overview first?" The answer is almost always: get the map.
Your Next Tool Call
This skill only loads instructions. You must call the MCP tools yourself. Your next action should be one of:
smart_search(query="<topic>", path="./src") -- discover files + symbols across a directory
smart_outline(file_path="<file>") -- structural skeleton of one file
smart_unfold(file_path="<file>", symbol_name="<name>") -- full source of one symbol
Do NOT run Grep, Glob, Read, or find to discover files first. smart_search walks directories, parses all code files, and returns ranked symbols in one call. It replaces the Glob → Grep → Read discovery cycle.
Returns: Full source code of the specified symbol including JSDoc, decorators, and complete implementation (~400-2,100 tokens depending on symbol size). AST node boundaries guarantee completeness regardless of symbol size — unlike Read + agent summarization, which may truncate long methods.
Parameters:
file_path (string, required) -- Path to the file (as returned by search/outline)
symbol_name (string, required) -- Name of the function/class/method to expand
When to Use Standard Tools Instead
Use these only when smart_* tools are the wrong fit:
Grep: Exact string/regex search ("find all TODO comments", "where is ensureWorkerStarted defined?")
Read: Small files under ~100 lines, non-code files (JSON, markdown, config)
Glob: File path patterns ("find all test files")
Explore agent: When you need synthesized understanding across 6+ files, architecture narratives, or answers to open-ended questions like "how does this entire system work end-to-end?" Smart-explore is a scalpel — it answers "where is this?" and "show me that." It doesn't synthesize cross-file data flows, design decisions, or edge cases across an entire feature.
For code files over ~100 lines, prefer smart_outline + smart_unfold over Read.
Workflow Examples
Discover how a feature works (cross-cutting):
1. smart_search(query="shutdown", path="./src")
-> 14 symbols across 7 files, full picture in one call
2. smart_unfold(file_path="services/infrastructure/GracefulShutdown.ts", symbol_name="performGracefulShutdown")
-> See the core implementation
Navigate a large file:
1. smart_outline(file_path="services/worker-service.ts")
-> 1,466 tokens: 12 functions, WorkerService class with 24 members
2. smart_unfold(file_path="services/worker-service.ts", symbol_name="startSessionProcessor")
-> 1,610 tokens: the specific method you need
Total: ~3,076 tokens vs ~12,000 to Read the full file
Write documentation about code (hybrid workflow):
1. smart_search(query="feature name", path="./src") -- discover all relevant files and symbols
2. smart_outline on key files -- understand structure
3. smart_unfold on important functions -- get implementation details
4. Read on small config/markdown/plan files -- get non-code context
Use smart_* tools for code exploration, Read for non-code files. Mix freely.
Exploration then precision:
1. smart_search(query="session", path="./src", max_results=10)
-> 10 ranked symbols: SessionMetadata, SessionQueueProcessor, SessionSummary...
2. Pick the relevant one, unfold it
Token Economics
Approach
Tokens
Use Case
smart_outline
~1,000-2,000
"What's in this file?"
smart_unfold
~400-2,100
"Show me this function"
smart_search
~2,000-6,000
"Find all X across the codebase"
search + unfold
~3,000-8,000
End-to-end: find and read (the primary workflow)
Read (full file)
~12,000+
When you truly need everything
Explore agent
~39,000-59,000
Cross-file synthesis with narrative
4-8x savings on file understanding (outline + unfold vs Read). 11-18x savings on codebase exploration vs Explore agent. The narrower the query, the wider the gap — a 27-line function costs 55x less to read via unfold than via an Explore agent, because the agent still reads the entire file.
Language Support
Smart-explore uses tree-sitter AST parsing for structural analysis. Unsupported file types fall back to text-based search.
Bundled Languages
Language
Extensions
JavaScript
.js, .mjs, .cjs
TypeScript
.ts
TSX / JSX
.tsx, .jsx
Python
.py, .pyw
Go
.go
Rust
.rs
Ruby
.rb
Java
.java
C
.c, .h
C++
.cpp, .cc, .cxx, .hpp, .hh
Files with unrecognized extensions are parsed as plain text — smart_search still works (grep-style), but smart_outline and smart_unfold will not extract structured symbols.
Custom Grammars (.claude-mem.json)
You can register additional tree-sitter grammars for file types not in the bundled list. Create or update .claude-mem.json in your project root:
Each key is a language name. package is the npm package of the tree-sitter grammar and extensions lists the file extensions it covers; the package must be installed in the project's node_modules (npm install tree-sitter-solidity). query (optional) is a path, relative to the config file, to a tree-sitter query whose captures (@func, @cls, @method, @iface, @enm, @struct_def, @imp) extract symbols. Without query, a minimal generic pattern is used — it only matches grammars that define function_declaration/class_declaration node types, and query compilation fails silently (0 symbols) for grammars that lack them, so a custom query is effectively required for most languages. Once registered, smart_outline and smart_unfold parse those extensions structurally instead of falling back to plain text.
Markdown Special Support
Markdown files (.md, .mdx) receive special handling beyond the generic plain-text fallback:
smart_outline — extracts headings (#, ##, ###) as the symbol tree. Use it to navigate long documents without reading the full file.
smart_search — searches within code fences as well as prose, so queries for function names inside ```ts ``` blocks work as expected.
smart_unfold — expands heading sections rather than function bodies; each section up to the next same-level heading is returned as a chunk.
Frontmatter — YAML frontmatter (lines between leading --- delimiters) is included in smart_outline output under a synthetic frontmatter symbol so metadata like title: and description: is visible without reading the whole file.
How do I install smart-explore?
Download plugin/skills/smart-explore/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does smart-explore live?
The publisher keeps it at https://github.com/thedotmack/claude-mem.
Which agents can use smart-explore?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.