API Evangelist papers — single-PDF deep dives on one practice or topic, with outlines.
| 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 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description must carry behavioral transparency. It states the content type ('single-PDF deep dives') but omits key behaviors: return type (list of papers?), pagination behavior, read-only nature, auth/permissions, or effect of sort/match. An agent cannot predict side effects or response shape.
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?
A single well-structured sentence that front-loads the resource type and unique attribute. No fluff; each word earns its place. It is concise without being cryptic.
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 search tool with 7 configurable parameters)Skip, no annotations, and no output schema, the description is heavily underspecified. It omits return format, pagination defaults, match semantics, field selection, and any cautions. It provides only a loose content description, leaving the agent to infer behavior entirely from parameter names.
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 covers only q and tags (2 of 7 fields, ~29%). The description adds nothing about page, sort, match, or fields. With low schema coverage, the description should compensate, but it doesn't clarify any parameter or filtering behavior beyond what's in the schema.
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 identifies the resource ('API Evangelist papers') and adds a distinguishing characteristic ('single-PDF deep dives... with outlines'). The verb is implicit in the tool name, but the noun is specific and well-defined. It does not reference sibling tools to clarify differentiation, but the purpose is unambiguous.
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?
There is no guidance on when to use this tool vs alternativesate. No mention of scenarios, exclusions, or relationships to other tools (e.g., find_posts or find_solutions). The description is descriptive, not prescriptive.
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.
