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Data Fetching

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lobehub·vlatest·backend

Automatically retrieves relevant data from external sources to enhance chatbot responses and provide up-to-date information.

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This skill no longer installs under the name data-fetching. lobehub/lobehub has no skill named "data-fetching" any more. It was renamed, moved or deleted upstream.

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Repository install instructions

What we know about this skill

Publisher

lobehub

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

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scanned

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Not scanned. none of the 52 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as lobehub/lobehub.
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About this skill

What it does

This Data Fetching skill enables AI agents to retrieve data from external sources and incorporate that information into responses. It utilizes a layered architecture involving a Service Layer, Zustand Store with SWR hooks, and a lambdaClient (TRPC client) for API interactions. The primary goal is to provide up-to-date information and enhance chatbot capabilities by automatically fetching relevant data.

When to use it

  • When your agent needs access to real-time or frequently changing data that isn't directly available in its internal knowledge base.
  • To populate lists of items (e.g., a list of benchmarks).
  • To retrieve detailed information about specific entities (e.g., details for a particular benchmark).
  • When performing write operations like creating, updating, or deleting data entries.

Key capabilities

  • Service Layer: Encapsulates API calls to lambdaClient and provides typed interfaces.
  • Zustand Store with SWR Hooks: Manages client-side state and handles data fetching with caching.
  • lambdaClient (TRPC Client): Used for making requests to external APIs.
  • Read Operations: query methods within the Service Layer are used for retrieving data.
  • Write Operations: mutate methods within the Service Layer are used for creating, updating, and deleting data.
  • Data Structure Patterns: Relies on structured data patterns (List vs Detail) as defined in the store-data-structures skill.

Example prompts

  • "List all available benchmarks."
  • "Get details about benchmark with ID 'xyz123'."
  • "Create a new benchmark with these parameters: [parameters]."

Tips & gotchas

  • Service Layer is Required: All API calls must be made through the Service Layer. Direct lambdaClient calls are prohibited.
  • Data Structures Matter: Ensure data is structured according to patterns defined in the store-data-structures skill for optimal functionality.
  • SWR Hooks Only: Use SWR hooks within stores, not useEffect, for data fetching.