medical.framingham_cvd_10y

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

Annotations already cover read-only/idempotent/safe profile, and the description adds meaningful non-obvious behavior: output is a 0-1 probability with 10 significant digits, and the computation uses a float64 log regression so results are not exact Decimal arithmetic. This numerical-precision caveat is exactly the kind of context annotations cannot provide.

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?

Dense but front-loaded: purpose and model first, then parameter/unit conventions, then output and precision caveat. Slightly packed into a single block with no separation, but no sentence is filler.

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?

For an 8-parameter clinical calculator with an output schema, the description supplies the units, ranges, types, output semantics, and a precision caveat, leaving nothing an agent needs to call it correctly.

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 0%, so the description must carry all parameter meaning, and it does: it specifies the sex enum, the 30-74 integer age range, units for total_chol/hdl (mg/dL) and sbp (mmHg), notes they are Decimal strings, and identifies the three boolean flags. Every one of the 8 required parameters is covered.

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?

States a specific verb+resource (10-year cardiovascular disease probability) and cites the exact model (D'Agostino 2008 general CVD), which clearly separates it from risk-score siblings like cha2ds2_vasc and from the unrelated qtc_framingham.

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?

Gives concrete applicability constraints (age must be 30-74 integer, sex male|female) and explicitly says it cannot be used for out-of-range ages. It stops short of naming an alternative tool for out-of-range ages, so it is clear context without full routing guidance.

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