scenario_analysis

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

Annotations already declare readOnlyHint, openWorldHint=false, and idempotentHint. The description adds meaningful behavior beyond these: it reports each case's validity issues rather than presenting a distorted number, invents no assumptions of its own, and performs no search. This is consistent with the annotations and gives an agent useful non-obvious expectations.

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?

Three dense sentences with no filler: the first states the core behavior, the second explains input ownership and validity handling, and the third gives the tool-type constraint. The length is justified by the tool's complexity and every sentence adds useful guidance.

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 complex nested-schema tool with no output schema, the description covers execution modes, input ownership, validity behavior, and the no-search constraint. It could be more explicit about the exact shape of returned fair-value outputs, but 'fair-value outcomes' and per-case validity reporting give adequate expectations.

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 low (~20%), so the description does meaningful compensation: it explains bull/bear deltas with a concrete example (+3% revenue growth, -1% WACC), clarifies that the base case is 'as given', and notes sensitivity grid values are typically WACC x terminal growth rate. It does not enumerate the required baseAssumptions fields, but those are standard DCF inputs largely inferable from property names.

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 states a specific verb ('Runs'), resource ('mechanical DCF'), and precise behavior: three cases (base, bull, bear) plus an optional 2D sensitivity grid. It also clearly distinguishes the tool from the sibling dcf_valuation by noting it runs the same DCF across scenarios rather than a single valuation.

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 positions the tool relative to dcf_valuation, explains that the caller must supply deltas/grid values from their own analysis, and explicitly says it is 'pure calculation — no search'. It provides clear context but does not enumerate exclusions or name alternatives like multi_stage_dcf_valuation or sotp_valuation.

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