detect_azure_cost_anomalies

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

With no annotations, the description carries the full burden. It discloses the comparison algorithm (period average) but does not describe the output format, whether the operation is read-only, or any side effects. For a detection tool, the behavior is partially transparent but incomplete.

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, focused sentence with no filler, front-loaded with the core purpose. It earns its place and is appropriately concise for the tool's simplicity.

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?

The tool has two simple parameters and no output schema, yet the description omits what the tool returns (e.g., a list of dates, amounts, anomaly summary). While the purpose is clear, the lack of output or usage context makes it incomplete for an agent deciding how to invoke and interpret the 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?

Schema description coverage is 100%, so the parameters are already well-documented. The description adds the algorithmic context of comparing against the period average, but this is largely redundant with the schema's min_spike_percentage description ('above average'). No additional parameter-level meaning is provided.

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 ('detects') and resource ('Azure cost spikes'), and explains the detection method ('comparing each day's spend against the period average'). It clearly distinguishes itself from GCP or generic anomaly detection siblings by naming Azure.

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 for Azure cost spike detection via the tool name and the word 'Azure', but it does not explicitly state when to use this tool over alternatives like detect_cost_anomalies or detect_gcp_cost_anomalies. No exclusions or alternative references are provided.

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