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HTTP Request Assistant

AI Agent Updated 2026.08.29

Paste the following prompt into your AI chat to install this skill:

Please install @user_57562667/http-request according to https://skillhub.cn/install/skillhub.md.

About this skill

Problem

When an agent needs to read an API, submit structured data, or pass an external response into the next step, manually assembling request headers, choosing methods, and parsing responses creates repetitive work. This skill targets a narrow, reusable action: given a URL, method, and JSON payload, make one HTTP request and return a parseable result. It is closer to a stable external-interface call node in a toolchain than a replacement for a full HTTP library.

How It Works

The skill centers on three key parameters:
- --url: required target endpoint.
- --method: request method, supports GET / POST, defaults to GET.
- --data: request data for POST, as a JSON string.
It also supports custom headers, which can carry format or identifier information needed by the request. After the call, it returns JSON-formatted response content, making it easier to extract fields, check status, or continue with model reasoning.

Boundary

The provided material only explicitly covers GET / POST, custom headers, and JSON responses. If an endpoint requires file upload, streaming, complex authentication, automatic retries, or special TLS configuration, confirm the underlying capability separately; do not treat this simple request helper as a general-purpose network debugging tool.

Use Cases

  • When debugging an endpoint, send a GET request to the target URL and verify the returned JSON fields.
  • When submitting a form, call POST with JSON data and receive the service result.
  • When tracing data sync issues, use a custom header to call the API and confirm the required identifier is sent.
  • When integrating an external system, fetch config via GET and submit processed results via POST to validate one call.

Best For

  • Backend engineers debugging internal APIs: need to quickly send GET/POST requests and inspect JSON responses.
  • Platform engineers integrating data sources: need to call APIs with custom headers and verify returned fields.
  • Application engineers building agent workflows: need to feed JSON API results into downstream steps.
  • QA engineers validating interface integration: need to issue one request by URL, method, and JSON payload.