aws_catalog

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds the context that this is a discovery mechanism and that results are 'read-only views', which is consistent with annotations. It does not disclose additional behavioral traits like pagination, response size, or rate limits, but for a catalog tool the annotations carry most of the burden. 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 remarkably concise: two sentences that deliver the purpose and entry-point advice, followed by a terse but informative args block. Every sentence earns its place, and the most critical information (what the tool does and where to start) is front-loaded. No filler.

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?

Given the tool's simplicity and the presence of an output schema (not shown but indicated), the description covers the core purpose and both parameters thoroughly. It does not mention output format, but the output schema likely handles that. The description is complete enough for an agent to call it correctly, though a note on return structure could push it to a 5.

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?

The description provides explicit, meaningful explanations for both parameters, including concrete examples for service ('ec2', 'eks', 'account') and the matching behavior for query. This goes well beyond the schema, which only lists types and defaults. With 0% schema coverage, the description fully compensates and adds significant value.

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 a specific action ('List') and resource ('read-only views'), and explains the output format (view ids with one-line summaries). It also positions itself as the entry point ('Start here'), which distinguishes it from sibling tools like aws_query or aws_read_resource that actually fetch data. This is a precise, non-tautological purpose.

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 phrase 'Start here' provides clear contextual guidance on when to use this tool – as the first step for discovering available views. It also explains how to filter via service and query parameters. However, it does not explicitly name alternative tools or state when to avoid using it, though the sibling names suggest different roles. The guidance is adequate but not exhaustive.

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