Parse an OpenAPI 3.x schema object or GraphQL SDL string. Returns a structured list of endpoints (and GraphQL types).
| Name | Required | Description | Default |
|---|---|---|---|
| schema | No | OpenAPI 3.x schema object | |
| graphql_sdl | No | GraphQL SDL string (alternative to schema) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It discloses the input formats and return value, but does not mention potential errors, the fact that exactly one of the two parameters must be provided, or any side effects. As a parser, it is likely safe, but this is not explicitly confirmed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant wording. Every phrase adds value: the action, the accepted inputs, and the output shape.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool handles two distinct input formats and has no output schema, yet the description only states the general output shape. It does not clarify that one parameter is required, nor does it explain the structure of the returned list. However, for a parser, the core behavior is adequately covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and both parameters are well-described in the schema. The description adds the relationship between the parameters ('alternative to schema') but does not provide additional format or constraint details beyond what the schema already includes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Parse') and names distinct resources ('OpenAPI 3.x schema object' or 'GraphQL SDL string'), clearly distinguishing it from siblings like api_executor or code_generator. It also states the output ('structured list of endpoints (and GraphQL types)').
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool: whenever you need to extract endpoints or types from a schema. It does not explicitly describe exclusions or alternatives, but the sibling tool names and the clear parse-only purpose provide adequate context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool addresses a distinct phase of the API playground workflow: parsing, rendering, executing, code generation, and history tracking. No two tools overlap in purpose, so an agent can select the right one without ambiguity.
All tool names follow the same pattern: a domain noun combined with an agent suffix (e.g., api_executor, schema_parser, history_tracker). This consistent structure makes the set predictable and easy to navigate.
The server has 5 tools, which is well within the ideal range. Each tool contributes a unique, essential capability to the playground experience, with no bloat or redundancy.
The tool set covers the entire lifecycle of building and using an API playground: parse a schema, render an interactive UI, execute live requests, generate code snippets, and inspect history. No obvious gaps or dead ends exist.