Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only and idempotent behavior, lowering the burden. The description adds context about 'live, same-category' and clarifies that the target is a well-known slug, not a listing slug, which is useful behavioral detail. No contradiction with annotations.

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, front-loaded with the action and resource, then gives examples, a trigger condition, and a critical param clarification. Every sentence earns its place with no fluff.

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 single-parameter tool with a clear output schema, the description covers the trigger, the object, and the differentiating constraint. It is complete enough for an agent to correctly invoke the tool without ambiguity.

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 for target is 100%, so baseline is 3. The description adds value by clarifying that target is a well-known slug and not a listing slug, which prevents a common misuse. This extra disambiguation justifies one point above 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 clearly states the tool lists live, same-category alternatives to a well-known AI tool, with concrete examples. It distinguishes from siblings like search_tools or get_tool by focusing on alternatives rather than general search or retrieving a single tool.

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?

It explicitly says to call this when a user asks for alternatives or competitors, which is strong usage guidance. However, it doesn't explicitly contrast with sibling tools like search_tools, so the when-not guidance is implied rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.