insights_dimensions
Cross-section ranking of the 40 tracked investment dimensions (AI, cloud, governance, …) by company signal. Free.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No |
Cross-section ranking of the 40 tracked investment dimensions (AI, cloud, governance, …) by company signal. 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 only says 'Free', which is ambiguous regarding read-only, auth needs, or side effects. It does not disclose any behavioral traits beyond being possibly cost-free.
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 very short (one sentence plus 'Free'), which is concise but too brief to be fully informative. It front-loads the core purpose but omits necessary details.
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 simplicity (2 optional params, no output schema), the description is incomplete. It does not explain return values or how the ranking is presented. The tool's function is hinted but not fully fleshed out.
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%, and the description does not mention the parameters (page, limit) at all. The parameter names are somewhat self-explanatory, but the description adds no value beyond the schema's structural definition.
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 ranks 40 investment dimensions by company signal. It uses a specific verb ('ranking') and resource ('dimensions'), making the purpose clear. However, it does not explicitly differentiate from siblings, though the focus on dimensions is unique among the listed tools.
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. The mention of 'Free' is a status note, not usage context. No prerequisites or situational advice is given.
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.