recommend_lambda_snapstart

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

No annotations are provided, so the description must convey behavioral traits. It mentions defaulting to all common regions, which is helpful. However, it does not disclose whether the tool is read-only, how results are delivered, or any rate limits. The description gives minimal behavioral context beyond the core function.

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 very concise: three sentences plus Args and examples. It is front-loaded with purpose and benefit. Every sentence adds value without redundancy.

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 has one optional parameter and no output schema, the description does not specify the return format (e.g., list of function names, details). The examples show user queries but not what the tool outputs. This is a significant gap for a recommendation tool.

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 schema has one parameter 'regions' with no description (0% coverage). The description explains that regions are AWS regions to scan and defaults to all common regions, adding meaning beyond the schema. It is clear and useful, though 'common regions' could be defined.

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: identifying Java Lambda functions that should use SnapStart. It explains the benefit of SnapStart (eliminates cold starts for free, replacing provisioned concurrency). This is specific and distinguishes from sibling tools, which are mainly audit and general recommendation tools.

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 example questions but does not explicitly state when to use this tool versus alternatives. There is no guidance on prerequisites, nor when not to use it. The sibling list includes many audit tools, but no direct comparison is made.

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