AWS MCP Server

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

No annotations provided, so description carries full burden. Discloses mutation nature ('Blocked in --readonly mode'), return value type ('query execution ID'), and asynchronous pattern (separate check results step). Missing explicit details on IAM permissions, timeouts, or costs, but covers primary behavioral traits.

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?

Three sentences, each earning its place: purpose statement, operational constraint, and return value/workflow. Front-loaded with action. Zero redundancy or filler. Efficient density of actionable 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?

Appropriate for an execution starter with 6 well-documented parameters and no output schema. Compensates for missing output schema by describing return value (query execution ID). Mentions workflow continuation. Minor gap on explicit async/queuing behavior or cost implications, but adequately complete.

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% (all 6 parameters documented in schema). Description adds no parameter-specific semantics, but this aligns with the baseline score of 3 when schema coverage is high. No compensation needed.

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?

Specific verb ('Start') + resource ('Athena SQL query execution'). Clearly distinguishes from siblings like aws_athena_get_query_results and aws_athena_list_databases by indicating this initiates execution rather than retrieving results or metadata.

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?

Mentions '--readonly mode' constraint indicating when the tool is unavailable. Explicitly references sibling tool 'get_query_results' as the follow-up to check results, establishing the execution workflow. Lacks explicit contrast with list/describe alternatives but implies active execution use case.

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