tldr

TLDR Code Analysis

Token-efficient codebase analysis using llm-tldr v1.5+. 95% fewer tokens than reading raw files.

Language is auto-detected (17 supported). No need to specify --lang unless overriding.

Quick Reference

Task	Command
"How does X work?"	semantic → context
"Who calls X?"	impact
"What would break?"	impact + change_impact
"Why is X null here?"	slice (backward)
"What does X affect?"	slice (forward)
"Project structure?"	arch + structure
"Find auth code"	semantic "authentication"
"Data flow in function"	dfg
"Control flow"	cfg
"Find dead code"	dead
"Type errors?"	diagnostics
"File tree"	tree
"Regex search"	search

Commands

Semantic Search (Natural Language)

Find code by meaning, not exact text. Uses 5-layer embeddings (AST + call graph + CFG + DFG + PDG):

mcp__tldr__semantic { "project": ".", "query": "user authentication flow" }
mcp__tldr__semantic { "project": ".", "query": "error handling" }

Function Context (95% Token Savings)

Get LLM-ready summary instead of reading entire file:

mcp__tldr__context { "project": ".", "entry": "handleLogin", "depth": 2 }

Impact Analysis (Before Refactoring)

Find all callers - critical before changing any function:

mcp__tldr__impact { "project": ".", "function": "useAuth" }

Architecture Overview

Understand project layers and dependencies:

mcp__tldr__arch { "project": "." }

Program Slice (Debugging)

What affects a specific line (backward) or what it affects (forward):

mcp__tldr__slice {
  "file": "src/auth.ts",
  "function": "login",
  "line": 42,
  "direction": "backward",
  "variable": "user"
}

Call Graph

Cross-file function call relationships (language auto-detected):

mcp__tldr__calls { "project": "." }

Data Flow Graph

Variable references and def-use chains:

mcp__tldr__dfg { "file": "src/auth.ts", "function": "validateToken" }

Control Flow Graph

Basic blocks and branching:

mcp__tldr__cfg { "file": "src/auth.ts", "function": "handleRequest" }

Change Impact (Affected Tests)

Find tests affected by changed files (auto-detects from git diff):

mcp__tldr__change_impact { "project": "." }

Dead Code Detection

Find unreachable code (language auto-detected):

mcp__tldr__dead { "project": "." }

Import Analysis

Parse imports or find importers:

mcp__tldr__imports { "file": "src/utils.ts" }
mcp__tldr__importers { "project": ".", "module": "auth" }

Diagnostics (Type/Lint)

Type checking and linting:

mcp__tldr__diagnostics { "path": "src/" }

File Tree

Quick project structure overview:

mcp__tldr__tree { "project": "." }
mcp__tldr__tree { "project": "src/", "extensions": [".ts", ".tsx"] }

Regex Search

Search files by regex pattern:

mcp__tldr__search { "project": ".", "pattern": "TODO|FIXME|HACK" }

Structure Overview

Functions, classes, methods per file (language auto-detected):

mcp__tldr__structure { "project": ".", "max_results": 50 }

Full File Extract

Complete code structure from a single file (imports, functions, classes, call graph):

mcp__tldr__extract { "file": "src/auth.ts" }

Daemon Status

Check uptime and cache statistics:

mcp__tldr__status { "project": "." }

Workflow Patterns

Understanding Code

1. tldr arch .                    # Get project overview
2. tldr semantic "feature name"   # Find relevant code
3. tldr context functionName      # Get LLM-ready summary
4. Read (only if more detail needed)

Before Refactoring

1. tldr impact functionName       # Who calls this?
2. tldr change_impact             # What tests affected?
3. tldr context functionName      # Understand the function
4. Make changes
5. tldr diagnostics src/          # Check for errors

Debugging

1. tldr slice file func line      # What affects this line?
2. tldr dfg file func             # Data flow analysis
3. tldr context func              # Understand function

Prerequisites

pipx install llm-tldr
tldr daemon start     # Background service (300x faster)
tldr warm .           # Build indexes including embeddings

CRITICAL RULES

1. ALWAYS use tldr context BEFORE reading large files
2. ALWAYS use tldr impact BEFORE refactoring
3. ALWAYS use tldr semantic for "how does X work" questions
4. Use grep ONLY for exact string matching
5. Do NOT hardcode language param — auto-detection handles 17 languages

Output

Return findings with:

• Relevant code: Key functions/files found
• Call chain: How things connect
• Recommendations: Next steps based on analysis
• Store as learning if discovering non-obvious patterns