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/tldr-deep

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

From plugin
continuous-claude-v3
3.9k156 skills32 agents
Install
$ npx -y skills add parcadei/Continuous-Claude-v3 --skill tldr-deep --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/tldr-deep

Context preview

The summary Claude sees to decide when to auto-load this skill.

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

SKILL.md

tldr-deep.SKILL.md
name: tldr-deep
description: Full 5-layer analysis of a specific function. Use when debugging or deeply understanding code.

TLDR Deep Analysis

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

Trigger

  • `/tldr-deep <function_name>`
  • "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 <file>` | | L2: Call Graph | Navigation | `tldr context <func> --depth 2` | | L3: CFG | Complexity | `tldr cfg <file> <func>` | | L4: DFG | Data flow | `tldr dfg <file> <func>` | | L5: Slice | Dependencies | `tldr slice <file> <func> <line>` |

Execution

Given a function name, run all layers:

# First find the file
tldr search "def <function_name>" .

# Then run each layer
tldr extract <found_file>              # L1: Full file structure
tldr context <function_name> --project . --depth 2  # L2: Call graph
tldr cfg <found_file> <function_name>  # L3: Control flow
tldr dfg <found_file> <function_name>  # L4: Data flow
tldr slice <found_file> <function_name> <target_line>  # L5: Slice

Output Format

## Deep Analysis: {function_name}

### 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

1. **Debugging** - Need to understand all paths through a function 2. **Refactoring** - Need to know what depends on what 3. **Code review** - Analyzing complex functions 4. **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)
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