Side-by-side comparison of 2-5 AI tools: pricing, rating, features, pros and cons. Use when the user is choosing between named products.
| Name | Required | Description | Default |
|---|---|---|---|
| tools | Yes | 2-5 slugs or display names. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses the key behavior: a side-by-side comparison of 2-5 tools covering pricing, rating, features, and pros/cons. It does not describe output format or failure modes, but these are minor for a non-destructive comparison tool.
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, front-loaded sentence with no filler. It states the action, scope, output dimensions, and usage trigger efficiently, so every part earns its place.
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 tool with no output schema, the description covers purpose, parameter range, output contents, and the trigger condition. It does not specify response formatting or edge-case handling, but nothing essential for selecting and invoking the tool is missing.
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 100%, so the baseline is 3. The description echoes the 2-5 count but does not add substantial meaning beyond what the schema already provides about the 'tools' parameter.
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: 'Side-by-side comparison of 2-5 AI tools.' It also lists concrete output dimensions (pricing, rating, features, pros and cons), which clearly distinguishes this tool from siblings like get_ai_tool or search_ai_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 an explicit trigger condition: 'Use when the user is choosing between named products.' It does not explicitly mention alternatives or when not to use the tool, but the intended context is clear enough for an agent to select it appropriately.
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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Each tool has a clearly distinct purpose: searching, retrieving details, comparing, finding alternatives, and listing categories. Even search and get are well differentiated by description, with search for discovery and get for the full catalog record.
All tools follow the same verb-first snake_case pattern: compare_, find_, get_, list_, search_. The naming clearly indicates both the action and the subject, making the tool set predictable and easy to navigate.
Five tools is an ideal size for a catalog-focused server. Each tool covers a distinct user need without redundancy or unnecessary surface area.
The catalog surface is complete for its read-only purpose: discovery via search, category browsing, detailed lookups, side-by-side comparison, and alternative suggestions. No obvious dead ends or missing operations are apparent.