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Skeego

opendata-mcp

by Skeego

approve_request_v1_requests__request_id__approve_post

Approve a dataset request by ID, changing its status to approved. Optionally include an expected version or comment.

Instructions

POST /v1/requests/{request_id}/approve (auth: Bearer OPENDATA_API_KEY) — Approve Request — Approve a dataset request (pure status change, no pipeline trigger).

Admin-only. Transitions status to approved. The actual dataset creation and ingestion happens separately via the fulfill endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_idYes
bodyNoRequest body (application/json) for POST /v1/requests/{request_id}/approve
Behavior3/5

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

No annotations, so description carries full burden. It discloses that it's a status change without pipeline trigger and admin-only. But lacks details on side effects, reversibility, error scenarios, or rate limits.

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?

Three sentences, front-loaded with endpoint and auth info. Every sentence adds value with no redundancy.

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?

Covers core purpose and distinguishes from fulfill, but lacks parameter explanations and output details. Given no output schema, tool is simple but completeness is adequate.

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

Parameters2/5

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

The description adds no meaning to parameters; request_id and body (with expected_version, comment) are not explained. Schema coverage is 50% but property descriptions are missing in schema too, so description does not compensate.

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 it approves a dataset request, specifies it's a pure status change without pipeline trigger, and differentiates from the fulfill endpoint. The verb 'approve' is specific and the scope (admin-only) is explicit.

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?

It explains when to use (approve a request) and notes that actual dataset creation is done via fulfill. It mentions admin-only prerequisite. However, no explicit exclusions for other sibling tools like reject or in-progress.

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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