Atris is a codebase intelligence tool that generates structured navigation maps with exact file and line references to eliminate redundant file scanning by AI agents.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install atris
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install atris using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Atris provides a persistent, structured intelligence layer for any codebase. By generating a central navigation index in atris/MAP.md, it allows AI agents to bypass repetitive full-project scans, leading to an 80-95% reduction in token consumption. This tool is a cornerstone for developers using Openclaw Skills to maintain context across sessions.
The skill follows a MAP-first philosophy: always consult the existing map before performing a search. If a symbol isn't found, the agent performs a targeted search once and immediately updates the map. This ensures that the codebase intelligence grows more comprehensive with every interaction, making it an essential addition to your Openclaw Skills library.
First, ensure ripgrep (rg) is installed on your system. To initialize this skill within your Openclaw Skills environment, create the directory and generate the initial map using the following commands:
mkdir -p atris
# Extract key definitions to seed the map
rg "^(export|function|class|const|def |async def |router\.|app\.|@app\.)" --line-number -g "!node_modules" -g "!.git" > atris/MAP.md
Once the file is created, use it as the primary source of truth for all codebase navigation tasks.
The skill organizes codebase intelligence into a specific hierarchy within the atris/MAP.md file:
| Section | Content Type | Purpose |
|---|---|---|
| Quick Reference | Symbol definitions | Provides immediate file:line access for common functions and classes. |
| By-Feature Map | Grouped logic | Maps files and line ranges to specific business features like Auth or UI. |
| By-Concern Map | Cross-cutting patterns | Identifies common patterns like error handling, logging, and middleware. |
| Entry Points | Execution flow | Documents server initialization, request lifecycles, and build pipelines. |
| Critical Files | High-impact assets | Flags essential configuration, schemas, and model files with usage notes. |
Loading
A comprehensive browser automation tool for form filling, data extraction, and scheduled monitoring.

A specialized automation tool for extracting, summarizing, and tracking the latest AI product developments and research from premier technical sources.

An advanced AI news aggregator that utilizes LLMs to score, filter, and push high-value industry updates automatically to team channels.

A streamlined interface for calling RouteMesh's unified JSON-RPC endpoint across multiple EVM chains using a Python-based helper.

A methodical AI research agent providing exhaustive, multi-cycle investigations with APA-compliant documentation.

Integrate ActiveCampaign CRM functionality into your AI agent workflows for seamless lead management and automated sales pipelines.








































