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112,509 tools. Last updated 2026-04-19 22:03
  • Get a comprehensive step-by-step guide for preparing all inputs required for a specific circuit. Read this BEFORE attempting proof generation — the guide covers how to compute signal_hash, nullifier, scope_bytes, merkle_root, how to query EAS GraphQL for the attestation, how to RLP-encode the transaction, how to recover secp256k1 public keys, and how to build the Merkle proof.
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  • Submit feedback about an AI topic or project. Categories: bug (broken/wrong data), feature (buildable thing), observation (strategic context), insight (analytical finding). Default 'observation' when unsure. All submissions are PUBLIC -- do not include sensitive data.
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  • Explain a single finding in natural language. Requires the finding as a JSON dict and the file_path to load a profile for context.
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  • List all databases in a given catalog. ⚠️ WORKFLOW: Call this after list_catalogs_tool to explore a specific catalog. 📋 PREREQUISITES: - Call search_documentation_tool first to understand what you're looking for - Call list_catalogs_tool to discover available catalogs 📋 NEXT STEPS after this tool: 1. Use list_tables_tool to find tables in a database 2. Use describe_table_tool to get table schemas before writing queries This tool retrieves all databases within a specified catalog. Parameters ---------- catalog : str The name of the catalog. ctx : Context FastMCP context (injected automatically) Returns ------- DatabaseListOutput A structured object containing database information. - 'catalog': The catalog name. - 'databases': List of database names. - 'count': Number of databases found. Example Usage for LLM: - When user asks for a specific catalog's databases. - Example User Queries and corresponding Tool Calls: - User: "List all databases in the 'wherobots' catalog." - Tool Call: list_databases('wherobots') - User: "What databases are in the foursquare catalog?" - Tool Call: list_databases('foursquare')
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