A powerful context retrieval layer that connects AI agents to workspace data across diverse applications like Slack, GitHub, and Jira.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install airweave
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install airweave using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Airweave?
Airweave serves as a sophisticated synchronization and indexing layer designed to empower AI agents with real-time organizational knowledge. By integrating with a wide array of workplace tools including Slack, GitHub, Notion, Jira, and Google Drive, it allows agents to access and understand information that usually remains siloed. This Openclaw Skills implementation ensures that your AI coding assistants can provide answers based on actual company data, specific project histories, and internal documentation rather than relying solely on static training sets.
Airweave Use Cases
- Retrieving specific discussion points from Slack or Microsoft Teams conversations.
- Locating technical documentation, project specs, or meeting notes within Notion and Confluence.
- Tracking bug reports and task statuses directly from Jira or Linear.
- Accessing recent GitHub pull request comments and issue history for context-aware code reviews.
- Answering factual workspace questions using the most current company data sources.
How Airweave Works
- The AI agent identifies a need for external context when a user asks a question about internal company data.
- A natural language query is formulated by the agent to target specific indexed information within Airweave.
- The agent executes the search script via Python, utilizing specific parameters like temporal relevance or hybrid search strategies.
- Results are retrieved from the collection and filtered based on relevance scores to ensure accuracy.
- The agent synthesizes the found data into a coherent response, citing the original application sources for user validation.
Airweave Setup
To integrate this skill, ensure you have Python 3 installed and have configured your credentials.
# Set required environment variables
export AIRWEAVE_API_KEY="your_api_key_here"
export AIRWEAVE_COLLECTION_ID="your_collection_id_here"
# Run a test search using the Openclaw Skills script
python3 scripts/search.py "your search query"
Airweave Data Schema & Taxonomy
Airweave organizes data into collections that aggregate synced content from various integrations. The retrieval output typically follows this structure:
| Attribute | Description |
|---|---|
| score | Relevance metric (0.0 to 1.0) indicating match strength |
| source | The origin application (e.g., Slack, GitHub, Notion) |
| content | The actual indexed text or record data |
| temporal | A weight indicating the freshness of the information |
Airweave Advanced Features
- Hybrid Search Strategies: Combine semantic vector search with traditional keyword matching for maximum precision.
- Temporal Relevance: Adjust search weighting (0-1) to prioritize the latest documents or messages.
- Query Expansion: Automatically broaden search terms to capture related context and synonyms.
- LLM Reranking: Utilize secondary model processing to ensure the most relevant results are surfaced to the top.
- Raw Data Mode: Retrieve unsummarized JSON results for complex data processing tasks.
SKILL.md
Loading
Related Openclaw Skills
Letundra
A comprehensive travel intelligence skill providing real-time visa info, aviation news, and cultural data from letundra.com.
Discord Project Manager
An automated infrastructure for managing Discord-based project collaboration between multiple AI agents and human teams.
Claude Usage Calculator
A specialized tool to track and visualize Claude Max subscription consumption and rate limits from session data.
qmd (Quick Markdown Search)
A local search engine designed for indexing and retrieving Markdown notes and documentation using keyword and semantic search.
skill-stats
A specialized utility for querying, analyzing, and tracking skill usage metrics across Claude Code and OpenClaw environments.
Outlit MCP Server
A specialized MCP server for querying customer intelligence, revenue metrics, and user activity directly within AI-powered development environments.
Featured*
