tldr-deep

parcadei/continuous-claude-v3 · updated Apr 8, 2026

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

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

skill.md

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)

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.559 reviews
  • Soo Abebe· Dec 28, 2024

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

  • Arjun Bansal· Dec 16, 2024

    Useful defaults in tldr-deep — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Dhruvi Jain· Dec 4, 2024

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

  • Arjun Agarwal· Dec 4, 2024

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

  • Oshnikdeep· Nov 23, 2024

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

  • Meera Abebe· Nov 23, 2024

    Useful defaults in tldr-deep — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Meera Diallo· Nov 19, 2024

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

  • Nia Srinivasan· Nov 15, 2024

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

  • Kofi Mehta· Nov 11, 2024

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

  • Kofi Khanna· Nov 7, 2024

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

showing 1-10 of 59

1 / 6