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Swagger: Scan API Standardization

swagger_scan_api_standardization
Read-onlyIdempotent

Scan an OpenAPI/AsyncAPI definition against governance rules to return validation errors, total issue count, and severity counts. Validate raw YAML or JSON for API standardization compliance.

Instructions

Run a standardization scan against an API definition using the organization's governance and standardization rules. Accepts a raw YAML or JSON OpenAPI/AsyncAPI definition and returns a list of validation errors, the total issue count, and counts grouped by severity. Use this tool when the user provides the API definition content directly (as raw YAML or JSON) and asks to validate, scan, or check the governance or standardization of the API.

Toolset: Registry API

Parameters:

  • orgName (string) required: The organization name to use for standardization rules

  • definition (string) required: API definition content (OpenAPI/AsyncAPI specification in JSON or YAML format) to scan for standardization errors

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgNameYesThe organization name to use for standardization rules
definitionYesAPI definition content (OpenAPI/AsyncAPI specification in JSON or YAML format) to scan for standardization errors

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
validationNo
countsBySeverityNo
Install Server

TDQS

A4.2/5.0
Behavior4/5

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

Over and above the readOnly/idempotent/non-destructive annotations, it discloses accepted input formats (raw YAML/JSON) and the return shape (validation errors, total issue count, severity counts). No contradiction; it adds useful operational detail without claiming 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.

Conciseness4/5

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

Information is front-loaded: purpose, use-case, toolset, parameters. It is slightly redundant by duplicating the schema's parameter descriptions, but remains compact and scannable for an agent.

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

Completeness5/5

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

For a 2-param, idempotent, read-only tool with an output schema, the description covers what the tool does, what it accepts, what it returns, and when to use it. Nothing necessary for correct invocation is missing.

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

Parameters3/5

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

Schema coverage is 100% for both params, so baseline 3 applies. The description repeats the schema's parameter meanings but adds little new semantic value beyond emphasizing 'raw' content for definition and orgName as rule selection context.

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 first sentence names a concrete verb/resource pair: running a standardization scan against an API definition using governance rules. It distinguishes itself from registry-based scanning by explicitly limiting to raw YAML/JSON definitions, and from sibling swagger_scan_api_standardization_from_registry by saying 'when user provides content directly'.

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?

Description clearly states the intended trigger ('when the user provides the API definition content directly... asks to validate, scan, or check'), which routes agents appropriately. It does not explicitly name alternatives or when-not-to-use cases, but the context is clear enough.

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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