smart-explore

thedotmack/claude-mem · updated Apr 8, 2026

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$npx skills add https://github.com/thedotmack/claude-mem --skill smart-explore
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summary

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.

skill.md

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.

3-Layer Workflow

Step 1: Search -- Discover Files and Symbols

smart_search(query="shutdown", path="./src", max_results=15)

Returns: Ranked symbols with signatures, line numbers, match reasons, plus folded file views (~2-6k tokens)

-- Matching Symbols --
  function performGracefulShutdown (services/infrastructure/GracefulShutdown.ts:56)
  function httpShutdown (services/infrastructure/HealthMonitor.ts:92)
  method WorkerService.shutdown (services/worker-service.ts:846)

-- Folded File Views --
  services/infrastructure/GracefulShutdown.ts (7 symbols)
  services/worker-service.ts (12 symbols)

This is your discovery tool. It finds relevant files AND shows their structure. No Glob/find pre-scan needed.

Parameters:

  • query (string, required) -- What to search for (function name, concept, class name)
  • path (string) -- Root directory to search (defaults to cwd)
  • max_results (number) -- Max matching symbols, default 20, max 50
  • file_pattern (string, optional) -- Filter to specific files/paths

Step 2: Outline -- Get File Structure

smart_outline(file_path="services/worker-service.ts")

Returns: Complete structural skeleton -- all functions, classes, methods, properties, imports (~1-2k tokens per file)

Skip this step when Step 1's folded file views already provide enough structure. Most useful for files not covered by the search results.

Parameters:

  • file_path (string, required) -- Path to the file

Step 3: Unfold -- See Implementation

Review symbols from Steps 1-2. Pick the ones you need. Unfold only those:

smart_unfold(file_path="services/worker-service.ts", symbol_name="shutdown")

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.

how to use smart-explore

How to use smart-explore on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add smart-explore
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/thedotmack/claude-mem --skill smart-explore

The skills CLI fetches smart-explore from GitHub repository thedotmack/claude-mem and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/smart-explore

Reload or restart Cursor to activate smart-explore. Access the skill through slash commands (e.g., /smart-explore) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.737 reviews
  • James Shah· Dec 24, 2024

    smart-explore fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Dhruvi Jain· Dec 20, 2024

    Registry listing for smart-explore matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Neel Agarwal· Dec 20, 2024

    smart-explore reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ishan Agarwal· Dec 12, 2024

    Keeps context tight: smart-explore is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Benjamin Lopez· Dec 8, 2024

    smart-explore has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Oshnikdeep· Nov 11, 2024

    Solid pick for teams standardizing on skills: smart-explore is focused, and the summary matches what you get after install.

  • Ishan Srinivasan· Nov 11, 2024

    We added smart-explore from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Nikhil White· Nov 3, 2024

    smart-explore is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Tariq Ramirez· Oct 22, 2024

    smart-explore reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ganesh Mohane· Oct 2, 2024

    I recommend smart-explore for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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