Apply an OpenAPI Overlay to a document and report what each action matched. Use it for deprecation and migration choreography without forking the contract.
| Name | Required | Description | Default |
|---|---|---|---|
| overlay | Yes | An OpenAPI Overlay document whose actions are applied to `document`. | |
| document | Yes | The API description to operate on — OpenAPI, AsyncAPI, Arazzo or JSON Schema. A YAML/JSON string or an already-parsed object; both are accepted. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does state that the tool 'report[s] what each action matched,' which is a behavioral output detail. However, it doesn't clarify whether the operation mutates the input document, returns a new version, or what error/failure behavior looks like. Given the lack of annotations, this is a moderate disclosure—adequate but not rich.
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?
Two sentences with zero fluff. The first sentence states the core action and expected outcome; the second sentence gives a concrete use case. It is front-loaded with the main purpose and efficiently covers all necessary information.
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?
For a tool with only two parameters, both documented in the schema, and no output schema, the description provides enough context to invoke it: it explains the purpose, the input types are clear from the schema, and it hints at the output via 'report what each action matched.' It lacks specifics on return format or side effects, but given the low complexity, this seems sufficient. I would rate higher only if more operational details were needed.
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?
The input schema has 100% coverage, meaning both parameters (overlay and document) have descriptive comments in the schema. The description adds no extra parameter-level detail beyond what the schema already provides, so the baseline of 3 is appropriate. The description does not conflict with or augment the schema's parameter documentation.
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 clearly states the function: 'Apply an OpenAPI Overlay to a document' with a specific verb (apply) and resource (OpenAPI Overlay on a document), plus an outcome ('report what each action matched'). It also mentions a clear use case (deprecation and migration choreography), which distinguishes it from sibling tools like validate_api or diff_api_versions by its focus on overlay application and matching reporting.
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?
It provides a direct usage context: 'Use it for deprecation and migration choreography without forking the contract.' This tells the agent when to reach for this tool. However, it doesn't explicitly name alternatives or conditions when NOT to use it, so I deduct one point for not covering exclusions or alternatives.
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.
Most tools have distinct purposes with clear descriptions, reducing ambiguity. However, some overlap exists between search tools like 'find_posts' and 'search_api_evangelist', though they target different scopes (stories vs. unified search). Overall, an agent can reasonably differentiate them.
The majority of tools follow a verb_noun pattern (e.g., find_areas, get_post), but several use noun_noun or inconsistent prefixes (e.g., api_coverage, company_gaps, insights_adoption). This inconsistency can confuse pattern recognition, though the pattern is still readable.
With 56 tools, the server is overloaded for a typical MCP context. While the domain is broad, the sheer number risks agent confusion and selection errors. Calibration suggests 25+ tools are excessive, and this server far exceeds that threshold.
The tool set covers a wide range of API governance, search, analysis, and generation tasks. There are no obvious dead ends for navigating the API Evangelist network, though some areas (e.g., direct API creation) are intentionally out of scope. Minor consolidation could improve efficiency.
