Biotech Pipeline Valuation

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, and the description adds genuine context beyond them: pure arithmetic with no I/O or external calls, results rounded to 2 decimals, no authentication or rate limits, and concrete failure semantics (unknown method or missing required param returns an error instead of a value).

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?

Front-loaded with purpose and method mapping, then behavior, then error semantics — a logical order. It loses a point for repeating the hardware/deep-tech exclusion twice ('for hardware or deep tech use valuation_hardware' and again later), and the return-field enumeration is somewhat redundant given an output schema exists.

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 a 9-parameter tool with one required parameter, the description covers method selection, per-method parameter requirements, defaults behavior, arithmetic purity, rounding, and error conditions. Since an output schema exists, listing return fields is optional and not a gap.

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 100%, so per-parameter meaning is already documented and the baseline is 3. The description adds real value on top by mapping each method to the parameters it needs (peak_sales → patient_population + penetration + price, decision_tree → probabilities + terminal_value, pipeline → drugs + discount_rate) and clarifying that only method is required while others are method-dependent.

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 opens with a specific verb+resource: 'Risk-adjusted biotech valuation' covering three named methods (peak sales, decision-tree EV, pipeline rNPV). It explicitly distinguishes the tool from the sibling valuation_hardware by domain (pharma/drug pipelines vs. hardware/deep tech), so an agent can route without opening schemas.

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?

It states when to use it ('pharma/drug pipelines') and names the alternative for the excluded case ('for hardware or deep tech use valuation_hardware'), plus model-selection guidance ('Method selects the model'). It also states which parameters to supply per method and to omit the rest, leaving little to inference.

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