get_labor_summary

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

With no annotations, the description carries full responsibility for behavioral disclosure. It reveals an important trait: the tool's output depends on whether real Toast data is imported. However, it does not state read-only nature, auth requirements, or rate limits. The single behavioral detail is helpful but insufficient for full transparency.

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 two concise sentences, front-loaded with the purpose. Every word adds value: the first sentence states what it returns, the second clarifies data source context. No waste or 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 the tool's simplicity (2 params, no output schema), the description provides the core return fields but lacks detail on output structure (e.g., format of 'cost' or 'percentage'). The phrase 'current known metrics' is vague. With no output schema, the description should more fully explain what the agent can expect.

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 only 50% (business has description, days does not). The description adds no additional meaning to the parameters beyond the schema. It does not explain how 'business' values like 'both' affect results or what 'days' range is valid. For low coverage, the description should compensate, but it fails to do so.

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 explicitly states 'Get labor hours, cost, and labor percentage', using a specific verb and resource. It clearly communicates the tool's output and distinguishes it from siblings like get_employee_hours by combining hours and cost. The context about data sources further clarifies its scope.

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 needing a labor summary, but does not provide explicit when-to-use or when-not-to-use guidance, nor does it reference alternatives like get_employee_hours or get_sales_summary. The conditional data source hint provides minor context but lacks clear decision criteria.

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