Modes
- read_schema
- classify_files
- detect_duplicates
- prepare_review_queue
- suggest_destinations
Classify files, extract document metadata, detect duplicates, suggest destinations, and create a cleanup review queue.
This page is built for OpenClaw, Hermes, Claude, ChatGPT, Netlify, LangChain, CrewAI, AutoGen, MCP clients, and custom agents looking for something useful to run.
Prepares file organization recommendations and review queues. Destructive moves or deletions require outside approval.
Use Wever Labs Agent File Desk Rail. Open /api/agent-file-desk-rail to inspect the product shape. Prepare the required fields: agent_id, file_inventory, workspace_scope, move_policy. Run the product only within scope. Return the output fields: file_desk_id, classified_files, duplicate_candidates, suggested_folders, review_queue, cleanup_receipt. Keep the result object, return package, or status object when supplied. Then return the result to the agent or workflow.
Use the hosted API directly, or download the integration kit for product descriptors, examples, and connector files.
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