Tldr Deep

by parcadeid07ff4b06b62No license3.9K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 8 months ago

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

Instructions onlySoftware Development

AI-generated overview

Runs a five-layer static analysis of a single function using the tldr CLI to aid debugging and code understanding.

What it does: This skill guides an agent through a five-layer analysis of one function: AST structure, call graph, control flow graph, data flow graph, and program slice. It specifies the tldr commands for each layer and a structured output format covering signature, callers and callees, cyclomatic complexity, variable definitions and uses, and slice dependencies. It also documents a Python API for running the same layers programmatically.
When to use it: Use it when debugging a complex function, refactoring code and needing dependency information, reviewing intricate functions, or locating performance hot spots via cyclomatic complexity.
Requirements: Requires the tldr command-line tool and its Python API (tldr.api) to be installed and available; the skill itself ships no scripts and only provides instructions.

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:

bash

# First find the filetldr search "def <function_name>" .
# Then run each layertldr extract <found_file>              # L1: Full file structuretldr context <function_name> --project . --depth 2  # L2: Call graphtldr cfg <found_file> <function_name>  # L3: Control flowtldr dfg <found_file> <function_name>  # L4: Data flowtldr slice <found_file> <function_name> <target_line>  # L5: Slice

# First find the filetldr search "def <function_name>" .
# Then run each layertldr extract <found_file>              # L1: Full file structuretldr context <function_name> --project . --depth 2  # L2: Call graphtldr cfg <found_file> <function_name>  # L3: Control flowtldr dfg <found_file> <function_name>  # L4: Data flowtldr 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 GraphCalls: {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 YVariables 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)

## Deep Analysis: {function_name}
### L1: Structure (AST)File: {file_path}Signature: {signature}Docstring: {docstring}
### L2: Call GraphCalls: {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 YVariables 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

python

from tldr.api import (    extract_file,    get_relevant_context,    get_cfg_context,    get_dfg_context,    get_slice)
# All layers for one functionfile_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)

from tldr.api import (    extract_file,    get_relevant_context,    get_cfg_context,    get_dfg_context,    get_slice)
# All layers for one functionfile_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)

Source and attribution

Source:parcadei/continuous-claude-v3in.claude/skills/tldr-deepat commitd07ff4b

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

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Tldr Deep

TLDR Deep Analysis

Trigger

Layers

Execution

Output Format

When to Use

Programmatic API

Source and attribution

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