analyze_biomarkers

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It clearly states the endpoint is stateless and does not store inputs, which is a key safety trait. It also specifies the output format (3-tier recommendations). This goes beyond basic disclosure, though it does not cover every possible side-effect or require permissions. For an analysis tool, this is strong 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 compact and front-loaded with the core purpose. Each sentence adds value: the action, the output, the data constraints, and the statelessness. There is no filler or redundancy. Despite being slightly longer than typical, it is appropriately detailed given the safety-critical data-handling instructions.

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 main purpose, output, and important data-handling behavior. It does not mention that users should consult list_supported_biomarkers to ensure valid biomarker names, nor does it explain how age or biologicalSex affect recommendations. Given the moderate complexity (nested object, 5 params) and the absence of an output schema, the description is mostly complete but has notable gaps in prerequisites and parameter influence.

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 60%, so the description should compensate for the undocumented parameters (age, biologicalSex). The description only refers to 'biomarker panel' and the output tiers, adding little detail about how age, biologicalSex, conditionFocus, or include_partner_options affect results. The schema itself describes biomarkers, conditionFocus, and include_partner_options, but age and biologicalSex remain unexplained in both schema and description, leaving a gap.

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's function: it analyzes a SYNTHETIC biomarker panel using the PRISM engine and returns 3-tier recommendations. This distinguishes it from siblings list_supported_biomarkers (which lists biomarkers) and get_methodology (which explains methodology). The verb 'analyze' plus the resource 'biomarker panel' makes the purpose unmistakable.

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 strong context for when to use the tool: it is intended for research/education with synthetic or de-identified data, explicitly forbids PHI, and notes the stateless nature. However, it does not explicitly contrast this tool with its siblings or state conditions like 'use when you need recommendations' versus 'use list_supported_biomarkers when checking available biomarkers'. The usage is implied rather than fully explicit.

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