Agent skill

tldr

TLDR code analysis for token-efficient codebase understanding. AUTO-INVOKE when: - User asks "who calls X", "what affects X", "find implementation" - Need to trace dependencies, call graphs, or data flow - Semantic search for code by meaning (not exact string) - Understanding large codebases efficiently - Before reading any large file (use context first) - Debugging "why is X null/undefined here" - Before refactoring (impact analysis) PREFER TLDR over raw file reads - 95% token savings.

View SKILL.md on GitHub Repository
Stars 163
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/tldr

SKILL.md

TLDR Code Analysis

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

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

Commands

Semantic Search (Natural Language)

Find code by meaning, not exact text:

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:

mcp__tldr__calls { "project": ".", "language": "typescript" }

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:

mcp__tldr__change_impact { "project": "." }

Dead Code Detection

Find unreachable code:

mcp__tldr__dead { "project": ".", "entry_points": ["main", "test_"] }

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/", "language": "typescript" }

Structure Overview

Functions, classes, methods per file:

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

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

bash
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

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

Recommended Agent Skills

Expand your agent's capabilities with these related and highly-rated skills.

majiayu000/claude-skill-registry

agent-ops-spec

Manage specification documents in .agent/specs/. Use when user provides requirements, acceptance criteria, or feature descriptions that need to be tracked and validated against implementation.

163 31
Explore
majiayu000/claude-skill-registry

agent-ops-state

Maintain .agent state files. Use at session start, after meaningful steps, and before concluding: read/update constitution/memory/focus/issues/baseline consistently.

163 31
Explore
majiayu000/claude-skill-registry

agent-ops-spec

Manage specification documents in .agent/specs/. Use when user provides requirements, acceptance criteria, or feature descriptions that need to be tracked and validated against implementation.

163 31
Explore
majiayu000/claude-skill-registry

agent-ops-testing

Test strategy, execution, and coverage analysis. Use when designing tests, running test suites, or analyzing test results beyond baseline checks.

163 31
Explore
majiayu000/claude-skill-registry

agent-ops-testing

Test strategy, execution, and coverage analysis. Use when designing tests, running test suites, or analyzing test results beyond baseline checks.

163 31
Explore
majiayu000/claude-skill-registry

agent-ops-state

Maintain .agent state files. Use at session start, after meaningful steps, and before concluding: read/update constitution/memory/focus/issues/baseline consistently.

163 31
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results