AWS FinOps MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions what the tool finds but doesn't explain how it works—e.g., whether it requires specific AWS permissions, how it determines 'low' or 'high' thresholds, if it's read-only or modifies data, or what the output looks like. For a tool with 7 parameters and no annotations, this is a significant gap in transparency.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core functionality, making it easy to parse quickly. Every word earns its place, achieving ideal conciseness.

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 complexity (7 parameters, no annotations, but with an output schema), the description is incomplete. It doesn't address parameter meanings, behavioral traits like authentication needs or rate limits, or how it interacts with sibling tools. While the output schema might cover return values, the description lacks essential context for effective tool selection and use.

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 0%, meaning none of the 7 parameters have descriptions in the schema. The tool description doesn't mention any parameters, leaving all of them undocumented. While it implies criteria like 'period' might relate to the analysis timeframe, it doesn't explain parameter roles, defaults, or interactions, failing to compensate for the schema's lack of coverage.

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: 'Find Lambda functions with low invocation rates or high error rates.' It specifies the verb ('Find'), resource ('Lambda functions'), and criteria ('low invocation rates or high error rates'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'find_unused_lambda_functions' or 'analyze_lambda_cold_starts', which prevents a perfect score.

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 provides no guidance on when to use this tool versus alternatives. With many sibling tools focused on Lambda optimization (e.g., 'find_unused_lambda_functions', 'analyze_lambda_cold_starts'), there's no indication of how this tool's focus on underutilization differs or when it's most appropriate. This leaves the agent guessing about context or prerequisites.

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