parcadei/continuous-claude-v3

tldr-overview

Get a token-efficient overview of any project using the TLDR stack

First seen Jan 24, 2026

Installation

$ npx skills add parcadei/continuous-claude-v3 --skill tldr-overview

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Gemini CLI Not declared
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Repository health

Stars 3.9K
License LICENSE
Default branch main
Open issues 30
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,878 B
  • docs SUMMARY.md 87 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 480 installs

SKILL.md

TLDR Project Overview

Get a token-efficient overview of any project using the TLDR stack.

Trigger

  • /overview or /tldr-overview
  • "give me an overview of this project"
  • "what's in this codebase"
  • Starting work on an unfamiliar project

Execution

1. File Tree (Navigation Map)

tldr tree . --ext .py    # or .ts, .go, .rs

2. Code Structure (What Exists)

tldr structure src/ --lang python --max 50

Returns: functions, classes, imports per file

3. Call Graph Entry Points (Architecture)

tldr calls src/

Returns: cross-file relationships, main entry points

4. Key Function Complexity (Hot Spots)

For each entry point found:

tldr cfg src/main.py main  # Get complexity

Output Format

## Project Overview: {project_name}

### Structure
{tree output - files and directories}

### Key Components
{structure output - functions, classes per file}

### Architecture (Call Graph)
{calls output - how components connect}

### Complexity Hot Spots
{cfg output - functions with high cyclomatic complexity}

---
Token cost: ~{N} tokens (vs ~{M} raw = {savings}% savings)

When NOT to Use

  • Already familiar with the project
  • Working on a specific file (use targeted tldr commands instead)
  • Test files (need full context)

Programmatic Usage

from tldr.api import get_file_tree, get_code_structure, build_project_call_graph

# 1. Tree
tree = get_file_tree("src/", extensions={".py"})

# 2. Structure
structure = get_code_structure("src/", language="python", max_results=50)

# 3. Call graph
calls = build_project_call_graph("src/", language="python")

# 4. Complexity for hot functions
for edge in calls.edges[:10]:
    cfg = get_cfg_context("src/" + edge[0], edge[1])