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AiAgentKarl

agent-validator-mcp-server

validate_openapi_spec

Validates an OpenAPI specification for AI agent compatibility, assessing documentation quality and providing a score with recommendations for improvement.

Instructions

Validate an OpenAPI spec for agent-friendliness.

Checks if the API documentation is good enough for AI agents to use the API effectively.

Args: spec_url: URL to OpenAPI/Swagger spec

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
spec_urlYes
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It explains the tool validates for agent-friendliness but lacks details on the validation process, criteria, or potential side effects. The description does not mention whether it is read-only, what happens on failure, or any prerequisites.

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 concise, with a clear front-loaded purpose statement and a brief parameter definition. Every sentence adds value without redundancy.

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

Completeness2/5

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

The tool has a simple interface with one parameter and no output schema. However, the description does not explain what the validation result looks like (e.g., pass/fail, error details), leaving a significant gap for the agent to understand the tool's output.

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?

The schema description coverage is 0%, so the description must compensate. It adds meaning by specifying that 'spec_url' should be a URL to an OpenAPI/Swagger spec, which clarifies the expected format beyond the bare 'string' type. However, it could provide more detail (e.g., format validation).

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 uses a specific verb 'validate' and resource 'OpenAPI spec for agent-friendliness', which clearly differentiates it from siblings like 'check_agent_interface_url' and 'validate_api_endpoint' that likely focus on different aspects.

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 clearly states the tool's purpose but does not explicitly mention when to use it over siblings or exclude alternatives. However, the context is clear enough for an agent to infer usage in validating entire specs for agent compatibility.

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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