Compare AI tools
compare_ai_toolsSide-by-side comparison of 2 to 4 AI tools: traffic rank, trend, pricing, free plan, score and alternatives.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| tools | Yes | Tool names, e.g. ["Cursor", "GitHub Copilot"]. |
compare_ai_toolsSide-by-side comparison of 2 to 4 AI tools: traffic rank, trend, pricing, free plan, score and alternatives.
| Name | Required | Description | Default |
|---|---|---|---|
| tools | Yes | Tool names, e.g. ["Cursor", "GitHub Copilot"]. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description goes further by enumerating what the comparison returns (traffic rank, trend, pricing, free plan, score, alternatives), which matters because there is no output schema. It still omits what happens when a supplied tool name isn't found.
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 front-loaded sentence that names the operation, the constraint, and the returned dimensions with no filler. Nothing could be removed without losing information.
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 one-parameter read-only tool with no output schema, listing the returned metrics makes the description essentially self-sufficient. The only meaningful gap is error/partial-match behavior for invalid tool 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?
With 100% schema description coverage and the minItems/maxItems bounds already encoded in the schema, the description adds little beyond restating the 2–4 range. The example format lives in the schema, not the description, so this is baseline territory.
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 names a specific verb (side-by-side comparison) and resource (AI tools), and scopes it with a count range of 2 to 4 and the exact data points compared. It implicitly distinguishes itself from single-tool siblings like get_ai_tool, though it never names an alternative explicitly.
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?
Usage is only implied: the '2 to 4 tools' framing signals 'use this when comparing multiple tools at once.' There is no explicit statement of when to prefer this over search_ai_tools or get_ai_tool, and no mention of prerequisites or failure modes (e.g., unknown tool names).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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