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Glama

Draft a generic entry from a spec

draft_entry
Read-onlyIdempotent

Preview and prepare generic MCP tool entries from an OpenAPI/Swagger source without saving them. Choose operations by ID or METHOD /path, set a limit, then review before saving.

Instructions

Draft a generic entry (tools straight from the API's own operations: name, description, input schema from the parameters and body, the HTTP mapping, the docs link) from an OpenAPI 3 / Swagger 2 description (URL, file path or text; same guards as ingest_openapi). No category vocabulary: the answer is passed through as data. Choose operations with operations (operationIds or 'METHOD /path') or filter; at most limit tools (default 25). The draft is not saved: review it, then save_entry with category 'generic'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
limitNo
filterNo
sourceYes
docs_urlNo
operationsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the read-only/idempotent/open-world profile; the description adds real value beyond them by flagging that 'the draft is not saved', the two-step review-then-save workflow, and that source parsing uses 'same guards as ingest_openapi'. It does not describe failure modes or fetch behavior for remote URLs, keeping it shy of a 5.

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

Conciseness4/5

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

Front-loaded with the purpose and dense but mostly waste-free across three sentences. The heavy parenthetical and multiple parenthetical asides make it slightly harder to scan than an ideal definition.

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

Completeness4/5

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

For a draft/transform tool with no output schema and no annotation-adjacent gaps, the description covers what gets produced, how to select operations, the limit default, and the required follow-up save step. Missing details are limited to the id and docs_url parameters, which are minor.

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

Parameters4/5

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

With 0% schema coverage, the description must carry the parameters, and it explains source (URL/file/text), operations (operationIds or 'METHOD /path'), filter, and limit (default 25). It leaves id and docs_url undocumented, so it compensates well but not completely.

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?

States a specific verb (Draft) plus resource (a generic entry from an OpenAPI 3 / Swagger 2 description) and defines what a 'generic entry' contains via a parenthetical. It clearly positions itself against siblings by referencing ingest_openapi (same guards) and save_entry (the persistence step).

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?

Explains when to use it (draft from an OpenAPI/Swagger spec given as URL, file path, or text) and describes the follow-on flow ('review it, then save_entry with category generic'). It does not explicitly contrast against template_entry or state when-not to use it, so it falls short of full alternative routing.

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