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

The annotations already establish readOnly and idempotent behavior, so the description does not need to restate safety. It adds useful behavioral context by specifying the results are 'live', the alternatives are 'same-category', and `target` must not be a catalog listing slug.

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 compact: one strong main sentence, one trigger-and-disambiguation sentence, and negligible filler. It is front-loaded with the core action and reads naturally for an AI agent.

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, low-complexity, read-only tool with a supporting output schema, the description fully covers the intended use, target semantics, and disambiguation from search_tools. There are no major omitted details.

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?

Although the schema already fully documents the single parameter, the description adds important disambiguation: `target` must be the well-known tool's slug and explicitly not a listing slug from the catalog. Examples like 'chatgpt' and 'notion-ai' reinforce this.

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 opens with a specific verb and resource: 'List live, same-category alternatives to a well-known AI tool.' It gives concrete examples ('chatgpt', 'notion-ai', 'figma') and clearly distinguishes itself from catalog search tools by requiring a well-known tool slug rather than a listing slug.

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, 'Call this when a user asks...', which gives clear trigger conditions for use. It does not explicitly name sibling tools as alternatives, but the target-slug caveat helps prevent a common misuse.

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