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Create API Request

unfour.api.create_request

Create a saved API request record in your workspace without sending network traffic. Returns the new request ID and a redacted summary for later reference.

Instructions

Creates a saved API request record in the workspace through the Unfour command bus. This mutates local Unfour metadata only; it does not send traffic. Dev/test allow it by default, while prod blocks by workspace policy. Returns the new request id and a redacted summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
authNo
bodyNo
nameYes
queryNo
methodYes
headersNo
authJsonNo
bodyKindNo
parentIdNo
workspaceIdNo
collectionIdNo
parentFolderIdNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations are limited to safety flags, but the description adds rich behavioral detail: it 'mutates local Unfour metadata only,' avoids sending traffic, explains production policy differences, and notes the return includes a new request ID and redacted summary. This significantly improves the agent's ability to predict side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three short sentences, front-loaded with the core operation, and every sentence adds useful behavioral or contextual information. There is no filler or redundant repetition of the tool name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description effectively covers tool behavior, environment constraints, and result shape, and the output schema may fill in return details. However, with 13 input parameters and no input schema descriptions, the record/model for required fields (name, method, url) and optional override (auth, body, headers, collection fields) still remains too vague for a complete understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, yet the description gives no input guidance for the 13 parameters. Fields like auth vs authJson, body vs bodyKind, and parentId/collectionId/parentFolderId remain completely unexplained; the description must compensate but does not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'Creates a saved API request record in the workspace' and distinguishes it from a live request by explicitly confirming 'it does not send traffic.' This separates it from sibling tools like send_request and update_request.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when the tool is usable ('Dev/test allow it by default') and when not ('prod blocks by workspace policy'). It also gives an implicit when-not by saying it does not send traffic, though it does not name an alternative tool explicitly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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