Build a compact overview of an unfamiliar codebase with TLDR. Summarize its file tree, functions, classes, and calls between components, then highlight complex functions while reducing the amount of source text the agent needs to read.
中文简介正在准备中。当前显示英语简介。
Get a token-efficient overview of any project using the TLDR stack
安装前可以查看交给 AI 代理的指令内容。
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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Coordinate background agents through saved files, keeping lengthy work transcripts out of the main conversation. It defines how to pass results between agents, monitor progress, and verify completed work with tests.
中文简介正在准备中。当前显示英语简介。
Delegate implementation, file reading, and testing to separate agents, then bring concise summaries back to the main conversation. The rules explain when delegation helps and when a small edit is better handled directly.
中文简介正在准备中。当前显示英语简介。
Organize implementation work across research, planning, validation, implementation, and review agents. Each stage passes files to the next, while implementation starts with failing tests and the main conversation coordinates the workflow.
中文简介正在准备中。当前显示英语简介。
Connect Agentica SDK agents to Claude Code CLI through a proxy, an intermediary server. Use setup and debugging guidance to address file permissions, streamed responses, result formatting, and agents reporting success without performing the requested operations.
中文简介正在准备中。当前显示英语简介。
Consult Agentica APIs when building workflows where multiple AI agents cooperate. This reference covers eleven coordination patterns, agent tracking, shared state, handoffs, and ways to combine results, with pointers to detailed API specifications.
中文简介正在准备中。当前显示英语简介。
Write clearer instructions for Agentica and REPL agents by specifying roles, file operations, and output formats. Includes templates for dividing research, coordinating specialists, reviewing solutions, and passing results between agents through files.
中文简介正在准备中。当前显示英语简介。