The standards bodies API Evangelist has actually MEASURED — repositories, maturity, governance, coalition. Distinct from find_standards, which searches 613 catalog entries describing what a standard IS. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool is 'Free' (suggesting no cost) and implies it returns measured data, but it does not mention pagination behavior, output structure, or any side effects. This is minimal but not misleading.
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 extremely concise: two sentences. The first clearly states what the tool does, and the second adds a key distinction and a cost note. No filler or redundancy.
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 a pagination-only schema, no output schema, and no annotations, the description provides the essential contrast with find_standards but lacks details on what the returned items look like (e.g., whether they include the measured properties). It mentions the measured attributes (repositories, maturity, etc.) but does not describe the result shape. It is adequate but not comprehensive.
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 0%, so the description must compensate for the two parameters (page, limit). It does not mention them at all, nor does it explain any other behavioral details like sorting or defaults. The parameters are common pagination fields, but the description provides no guidance on their usage or expected values.
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 tool finds standards bodies that have been measured, with specific attributes (repositories, maturity, governance, coalition). It explicitly distinguishes from sibling tool find_standards, which searches catalog entries. This is a specific verb-resource pair with clear differentiation.
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 explicitly contrasts with find_standards, telling the agent when to prefer this tool (when measured data is needed vs. catalog lookup). It doesn't mention other potential alternatives like standard_repositories or standard_coalition, but the primary alternative is addressed well.
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.
