tldr-deep

安装量: 179
排名: #4810

安装

npx skills add https://github.com/parcadei/continuous-claude-v3 --skill tldr-deep

TLDR Deep Analysis

Full 5-layer analysis of a specific function. Use when debugging or deeply understanding code.

Trigger /tldr-deep "analyze function X in detail" "I need to deeply understand how Y works" Debugging complex functions Layers Layer Purpose Command L1: AST Structure tldr extract L2: Call Graph Navigation tldr context --depth 2 L3: CFG Complexity tldr cfg L4: DFG Data flow tldr dfg L5: Slice Dependencies tldr slice Execution

Given a function name, run all layers:

First find the file

tldr search "def " .

Then run each layer

tldr extract # L1: Full file structure tldr context --project . --depth 2 # L2: Call graph tldr cfg # L3: Control flow tldr dfg # L4: Data flow tldr slice # L5: Slice

Output Format

Deep Analysis:

L1: Structure (AST)

File: {file_path} Signature: {signature} Docstring: {docstring}

L2: Call Graph

Calls: {list of functions this calls} Called by: {list of functions that call this}

L3: Control Flow (CFG)

Blocks: {N} Cyclomatic Complexity: {M} [Hot if M > 10] Branches: - if: line X - for: line Y - ...

L4: Data Flow (DFG)

Variables defined: - {var1} @ line X - {var2} @ line Y Variables used: - {var1} @ lines [A, B, C] - {var2} @ lines [D, E]

L5: Program Slice (affecting line {target})

Lines in slice: {N} Key dependencies: - line X → line Y (data) - line A → line B (control)


Total: ~{tokens} tokens (95% savings vs raw file)

When to Use Debugging - Need to understand all paths through a function Refactoring - Need to know what depends on what Code review - Analyzing complex functions Performance - Finding hot spots (high cyclomatic complexity) Programmatic API from tldr.api import ( extract_file, get_relevant_context, get_cfg_context, get_dfg_context, get_slice )

All layers for one function

file_info = extract_file("src/processor.py") context = get_relevant_context("src/", "process_data", depth=2) cfg = get_cfg_context("src/processor.py", "process_data") dfg = get_dfg_context("src/processor.py", "process_data") slice_lines = get_slice("src/processor.py", "process_data", target_line=42)

返回排行榜