The API vocabulary — thousands of resources, actions, personas, domains, schemas, and tags extracted from the API landscape. Filter by category.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Free text over title, summary, tags, and body. | |
| page | No | ||
| sort | No | ||
| tags | No | Tag slugs; match any by default. | |
| limit | No | ||
| match | No | any | |
| fields | No | ||
| category | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only mentions 'Filter by category', ignoring pagination, sorting, match modes, or output format. The agent learns little about side effects (likely read-only) or constraints beyond what the schema defines.
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?
Single sentence is efficient, front-loading the tool's scope. However, it omits critical details that could be included without bloating (e.g., a brief note on pagination or match logic).
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?
With 8 parameters (0 required) and no output schema, the description fails to cover pagination, sorting, match behavior, fields selection, or return format. An agent cannot reliably invoke this tool without external knowledge.
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 only 25% (q and tags have descriptions). The overall description adds no parameter explanation beyond 'Filter by category', which maps to the category enum. It does not clarify sort, match, page, limit, fields, or tags usage.
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 states the tool covers 'the API vocabulary' and lists content types (resources, actions, etc.), clearly distinguishing it from sibling find_* tools that target specific subdomains (e.g., find_areas, find_building_blocks). However, it lacks an explicit verb like 'search' or 'list', slightly obscuring the action.
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?
No guidance on when to use this tool vs. alternatives. The description implies generic filtering but does not help an agent decide, e.g., when to use find_vocabulary vs. find_tags. Exclusions and context are missing.
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.
