get_savings_summary

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

No annotations are provided, so the description carries full disclosure burden. It reveals basic behavioral traits (30-day summary, fields returned) but omits important details such as whether the operation is read-only, required permissions, error handling, or rate limits. The description does not contradict annotations as none exist.

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 concise, starting with a clear one-sentence summary followed by a structured parameter list. Every sentence serves a purpose, and no redundant information is present. It is well-organized but could be slightly more streamlined by integrating the parameter descriptions into the main text.

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?

For a simple query tool with three parameters and an existing output schema, the description provides adequate purpose and parameter details. It does not need to explain return values due to the output schema. However, the lack of behavioral transparency and usage guidance reduces completeness, though it remains sufficient for an AI agent to invoke the tool correctly.

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?

With 0% schema coverage, the description fully compensates by explaining each parameter: cluster_id is exemplified with 'o-abc12345', account_id is optional with default from env var, and cloud specifies allowed values 'aws' or 'azure' with default. This adds critical semantic meaning beyond the schema's minimal titles and types.

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 retrieves a 30-day cost/savings summary for an Ocean cluster, specifying the verb, resource, and scope. It mentions total spend, spot savings, and cost breakdown, making the purpose clear. However, it does not explicitly differentiate from sibling tools like get_cluster_costs or get_cost_trending, which could cause confusion.

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 when a 30-day cost/savings summary is needed, but provides no explicit guidance on when to use this tool versus alternatives (e.g., get_cluster_costs for more detailed costs). No prerequisites, exclusions, or context-specific instructions are given, limiting clarity on appropriate invocation.

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