calculate_caffeine_half_life

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

With no annotations, the description should disclose behavioral traits like assumptions (e.g., half-life value) or limitations (e.g., not for medical advice). It mentions output fields but does not cover these aspects, leaving some behavioral gaps.

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 extremely concise with two sentences: the first states the purpose, the second lists return fields and a pointer to related tools. No extraneous information, and the key information is front-loaded.

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 core functionality and output structure, but it omits assumptions like the standard caffeine half-life and does not detail the output schema beyond field names. However, given the tool's simplicity and presence of an output schema, it is nearly 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?

Schema coverage is 100%, so the schema already describes both parameters adequately. The description adds no additional meaning beyond what the schema provides, resulting in a baseline score.

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 calculates remaining caffeine after time elapsed, which is a specific verb-resource combination. It differentiates from siblings like calculate_caffeine_intake by mentioning output fields and pointing to related calculators via list_bundles.

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 does not explicitly state when to use this tool versus alternatives such as calculate_caffeine_intake or calculate_caffeine_clearance. It only hints at related calculators through list_bundles, lacking direct guidance on selection criteria.

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