Get a token-efficient overview of any project using the TLDR stack
npx skills add https://github.com/parcadei/Continuous-Claude-v3 --skill tldr-overview
Get a token-efficient overview of any project using the TLDR stack.
/overview or /tldr-overviewtldr tree . --ext .py # or .ts, .go, .rs
tldr structure src/ --lang python --max 50
Returns: functions, classes, imports per file
tldr calls src/
Returns: cross-file relationships, main entry points
For each entry point found:
tldr cfg src/main.py main # Get complexity
## 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)
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])
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Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
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Take parcadei/tldr-overview from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.