get_unit_economics

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

No annotations provided, but the description explains the tool's behavior: it calculates unit economics ratios using a configurable time window. It does not indicate any destructive side effects, and the need for prerequisite setup is clearly communicated.

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 and well-structured, starting with a clear purpose statement, followed by a list of example ratios, a prerequisite note, parameter documentation, and usage examples. 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?

The description covers the tool's purpose, prerequisite, parameter, and provides example queries. While it does not describe the exact return format, the examples imply the kind of output expected. For a tool without output schema, this is reasonably complete.

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 only parameter, period_days, is explained as 'Cost window to use for the calculation (default 30 days).' This adds meaning beyond the schema's default value. Even though schema description coverage is 0%, the description adequately covers this parameter.

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 it connects cloud/SaaS spend to business metrics, listing specific ratios like cost per customer, cost per MAU, etc. It distinguishes itself from sibling tools like get_business_metrics and get_llm_unit_economics by focusing on aggregated unit economics across all spend.

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?

Explicitly states the prerequisite: 'Requires business metrics to be set with set_business_metrics() first.' Provides examples of queries. While it doesn't explicitly state when not to use, the prerequisite and examples imply appropriate use cases.

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