AWS FinOps MCP Server

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it's a read-only operation (implied by 'find' and 'identifies'), specifies criteria for 'unused', mentions a lookback period for traffic checks, and notes optional AWS credential parameters. However, it doesn't detail rate limits, pagination, or error handling, leaving some gaps.

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 well-structured and front-loaded with the core purpose, followed by detailed criteria, parameter explanations, and return value. Every sentence adds value without redundancy, making it efficient and easy to parse 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?

Given the tool's moderate complexity (8 parameters, no annotations, but with output schema), the description is largely complete. It explains the purpose, parameters, and return value. The output schema exists, so detailed return format isn't needed. However, it could benefit from more behavioral context like error cases or performance considerations.

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 input schema has 0% description coverage, so the description must compensate. It adds meaning for all 8 parameters: explains 'period' as 'lookback period in days for traffic check', 'max_results' as 'maximum results to return', and clarifies optional AWS credential parameters. This significantly enhances understanding beyond the schema's basic titles and defaults.

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's purpose with specific verbs ('find', 'identifies') and resources ('target groups'), and distinguishes it from siblings by specifying the criteria for 'unused' (no registered targets, no traffic, or not attached to load balancers). This is more specific than generic 'find' tools in the sibling list.

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 implies usage for identifying unused target groups based on specific criteria, but does not explicitly state when to use this tool versus alternatives (e.g., other 'find' tools for target groups like 'find_target_groups_with_high_error_rate'). It provides context but lacks explicit guidance on exclusions or comparisons.

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