Validate an API Onboarding Descriptor (AID) against the api-commons schema and report which optional sections it fills in.
| Name | Required | Description | Default |
|---|---|---|---|
| descriptor | Yes | An API Onboarding Descriptor (AID) to validate. Aliases: `aid`, `document`. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full transparency burden. It communicates a read-only validation and reporting behavior, but it does not explicitly confirm that no state changes occur or disclose error-handling, permission, or side-effect details. The 'report' clause adds useful return-oriented transparency.
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 focused sentence that leads with the action, names the object, specifies the validation target, and states the extra reporting behavior. Every clause earns its place, with no redundancy or filler.
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?
Given the low complexity of one required parameter and no output schema, the description sufficiently covers what the tool accepts and what it produces at a high level. It could be more explicit about the exact response structure and failure behavior, but it is complete enough for an agent to select and invoke the tool correctly.
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 single parameter descriptor is already fully documented in the schema with type and aliases, so schema coverage is 100% and the baseline is 3. The description restates the AID concept but does not add meaningful parameter-format details beyond what the schema already provides.
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?
Description uses a specific verb and resource: 'Validate an API Onboarding Descriptor (AID) against the api-commons schema.' It also states a distinguishing result, 'report which optional sections it fills in,' which separates it from siblings like validate_api that likely target ordinary API definitions.
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 it: whenever an AID needs schema validation and optional-section reporting. However, it provides no explicit when-not-to-use guidance or comparison with sibling tools such as validate_api or audit_pipeline, so the agent must infer the right condition from the tool name and description.
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.
