Detect Cost Anomalies

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only restates the purpose and never reveals output format, whether the operation is read-only, how detection thresholds affect results, or any side effects. 'Detect' weakly implies a read operation, but that is not explicit.

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 sentence with no filler, directly front-loading the tool's purpose. It is appropriately concise and free of redundant phrasing.

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 tool with no annotations and no output schema, this description is not enough. It fails to state what kind of output the agent should expect, how lookbackDays and thresholdPercentage influence detection, or when a sibling tool would be a better fit for similar billing analyses.

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 100%, so the baseline 3 applies. The description itself adds no parameter-level meaning, but the schema already documents each parameter with types, ranges, defaults, and examples, which is adequate.

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 uses a specific verb ('Detect') and names the resource ('unusual cost patterns and spending anomalies in Google Cloud billing data'), making the core function clear. However, it does not explicitly contrast with sibling tools like gcp-billing-analyse-costs or gcp-billing-cost-recommendations, so differentiation relies on the word 'anomalies' rather than an explicit statement.

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 such as gcp-billing-analyse-costs, gcp-billing-cost-recommendations, or gcp-billing-service-breakdown. The agent must infer the appropriate context from the tool name and schema, which is not sufficient.

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