fast-io

What This Skill Does

The fast-io skill serves as the ultimate collaborative workspace bridge for AI agentic teams. It transforms how agents manage, share, and query data by providing a unified environment for both humans and agents to interact. Rather than relying on disparate storage buckets or insecure file transfer services, fast-io enables agents to utilize a dedicated MCP (Model Context Protocol) server. It features 19 consolidated tools that handle everything from file management and document intelligence to workflow tracking. Whether you are generating reports, building branded data rooms, or requiring RAG-based document interrogation, fast-io allows agents to store artifacts, track worklogs, manage approvals, and facilitate seamless handoffs between automated processes and human supervisors. It removes the infrastructure burden, offering a free-tier environment that includes 50GB of storage and 5,000 monthly credits.

Installation

To integrate this capability into your OpenClaw environment, execute the following command in your terminal or agent interface:

clawhub install openclaw/skills/skills/dbalve/fast-io

Ensure that your OpenClaw runtime has the necessary permissions to communicate with external MCP servers, as this skill relies on an external API connection to orchestrate workspace operations and metadata syncing.

Use Cases

• Collaborative Data Rooms: Agents can compile research, codebases, or project files into a branded shareable space for human stakeholders to review.
• Agent Handoffs: When an agent completes a task, it can transfer ownership of a workspace to a specific human user for final approval and deployment.
• Document Intelligence: Instead of manually parsing PDFs or spreadsheets, use the built-in AI querying to ask questions like, "What are the key findings in this quarterly report?"
• Workflow Automation: Manage task life-cycles by creating to-dos, logging progress, and documenting final outcomes within a structured environment that provides audit trails.

Example Prompts

1. "I've finished the data analysis for Project X. Create a new fast-io workspace, upload the final report, and generate a branded share link for the client."
2. "Search the 'Q1 Financials' workspace and identify the top three risks mentioned in the PDF files."
3. "Add a task to the current workspace to review the new codebase, and assign it to the human lead with a status of 'Pending Approval'."

Tips & Limitations

To ensure optimal performance, always monitor your credit usage, as complex AI document queries consume more credits than basic file storage operations. Note that while fast-io supports real-time collaboration, it is designed for structured workspace environments; for massive bulk data migrations (terabyte scale), you should verify API limits. Always ensure your workspace IDs are cached locally by your agent to minimize redundant network calls, and remember that versioning of the MCP server matters—if you encounter unexpected tool execution errors, check for server updates using the clawhub CLI.