Search Gartner Peer Insights software markets by keyword to find relevant categories, returning up to 250 matching records for market research and vendor analysis.
Search Gartner Peer Insights markets (software categories) by keyword. 1 point per returned record.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search term. e.g. data loss prevention | |
| max_items | No | Max items (up to 250) |
Changes observed during successful MCP inspections.
v1.0.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It usefully discloses the cost model ('1 point per returned record'), but it does not state that the operation is read-only, describe the return format, or mention pagination beyond the schema's max_items.
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 two sentences with no waste, and the core purpose is front-loaded. It communicates the action and cost model efficiently.
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 simple two-parameter search tool with full schema coverage, the description is mostly complete: it names the resource and cost model. It could be stronger by clarifying how results differ from run_gartner_categories or run_gartner_market, but no output schema means return values need not be explained.
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 coverage is 100%, so the query and max_items parameters are already documented in the schema. The description adds that the search is by keyword but does not elaborate on parameter semantics beyond that baseline.
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 a specific verb and resource: 'Search Gartner Peer Insights markets (software categories) by keyword.' This clearly identifies the operation. However, it does not explicitly distinguish this tool from sibling tools like run_gartner_categories or run_gartner_market, leaving some ambiguity about when to use each.
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 gives no explicit guidance on when to use this tool versus alternatives such as run_gartner_categories or run_gartner_market. It implies a keyword search but provides no exclusions, prerequisites, or routing advice among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.