tldr-deep▌
parcadei/continuous-claude-v3 · updated Apr 8, 2026
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
- 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)
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★59 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.
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