get_waste_analysis

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

No annotations provided, so the description carries the full burden. It discloses the type of analysis and output (cost estimates, remediation actions), but does not mention whether it runs a fresh query or uses cached data, nor any potential side effects or access constraints.

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?

Three sentences clearly structured: first sentence states the high-level purpose, second lists identification criteria, third describes output. Every sentence adds value with no 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 zero parameters and no output schema, the description sufficiently explains what the tool returns and the criteria used. It also includes temporal specificity (24h, 7 days), making it mostly complete. Could ideally mention if it aggregates data across clusters or users, but not a major gap.

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?

There are zero parameters, so the tool relies entirely on the description. The description adds substantial meaning by detailing what findings are returned and the nature of the output (cost estimates and remediation actions), compensating for the lack of 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 returns GPU waste analysis of idle resources, specifying three identification criteria (GPU nodes with <10% utilization, deployments with zero jobs, over-provisioned replicas). This distinguishes it from sibling tools like get_gpu_metrics or get_spend_trend.

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?

No explicit guidance on when to use this vs alternatives, nor any exclusions or conditions. The purpose is implied but the description lacks direct recommendations for the agent.

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