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 the tool returns a dictionary but doesn't describe the structure, format, or keys of the output. It also doesn't disclose authentication requirements, rate limits, side effects, or error handling. The description adds minimal behavioral context beyond the basic purpose.

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 with a clear purpose statement followed by organized 'Args' and 'Returns' sections. It's appropriately sized for an 8-parameter tool, though the AWS credential parameters could be grouped conceptually. Every sentence adds value, with no redundant 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?

Given the tool's complexity (8 parameters, no annotations, but with output schema), the description is moderately complete. It explains parameters well and mentions the return type, but lacks behavioral context like authentication needs or performance characteristics. The output schema existence reduces the need to detail return values, but more operational guidance would help.

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 detailed parameter semantics in the 'Args' section, explaining each parameter's purpose (e.g., 'AWS region name', 'Lookback period in days'). Since schema description coverage is 0%, the description fully compensates by adding meaning beyond the schema's titles, clarifying defaults and optionality for all 8 parameters.

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 RDS instances with low CPU utilization (≤20%)'. It specifies the verb ('Find'), resource ('RDS instances'), and the exact criterion ('low CPU utilization ≤20%'). This distinguishes it from sibling tools like 'find_overutilized_rds_instances' and 'analyze_rds_performance_insights'.

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. It doesn't mention sibling tools like 'find_overutilized_rds_instances' or 'analyze_rds_performance_insights', nor does it specify prerequisites, typical use cases, or exclusions. The agent must infer usage from the purpose alone.

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