Search the governance building blocks by type: guidance (177), rules (617), policies (283), standards (432), strategies (75), schema (11), properties (790), experiences (46), lifecycle (29).
| 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. | |
| type | Yes | ||
| limit | No | ||
| match | No | any | |
| fields | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only mentions searching by type and lists counts, but does not describe pagination, sorting, filtering behavior, or that it returns a list of building blocks. The agent lacks info on result structure and side effects.
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 sentence listing types and counts, which is concise and front-loads the key purpose. However, it could be slightly more structured without losing conciseness.
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 8 parameters, low schema coverage, no output schema, and the tool's complexity as a search function, the description is insufficient. It omits pagination, sorting, match logic, and field selection, leaving significant gaps for the agent.
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% (2 of 8 parameters have descriptions). The description adds no parameter details beyond listing allowable types. It does not explain 'q', 'page', 'sort', 'limit', 'match', or 'fields', leaving the agent to guess their meaning.
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 searches governance building blocks by type, listing all types with counts. It identifies the specific resource (governance building blocks) but does not differentiate it from other search sibling tools like find_papers or find_posts, which also search by similar parameters.
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 provides no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusion criteria. It only states the basic function, leaving the agent to infer usage context.
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.
