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

Annotations already declare read-only, idempotent, non-destructive, closed-world behaviour, and the description does not contradict that. It adds genuinely non-obvious context: a null request silently falls back to a shipped synthetic example, and supplying data requires permission with rights_confirmed=true — plus the important disclaimer that the flag does not verify a licence.

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 tight sentences, front-loaded with what is computed and followed by the two operational conditions. No filler, though the regulatory citation and the licensing caveat are packed densely into single clauses.

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 output schema covers return values, so that is not a gap, and the synthetic-vs-supplied-data and rights caveats are valuable. But for a tool whose main payload is a deeply nested request with zero field-level documentation, the description leaves too many request fields unexplained to be considered 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 description coverage is 0%, so the description must carry the burden, and it only explains the two top-level parameters: request's null/synthetic semantics and rights_confirmed's meaning. It adds nothing about data_mode, source, apply_specified_pair_reduction, or the delta/vega bucket structures, which are the fields an agent is most likely to get wrong.

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 names a specific computation: FRTB standardised sensitivities-based method (MAR21) FX delta and vega capital, which pins down both the regulatory framework and the risk class. That is enough to separate it from IMA/backtest/SA-CCR siblings without opening any schema, though it never names an alternative explicitly.

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 gives concrete conditional guidance: omit the request to run the shipped synthetic example, and supply data plus rights_confirmed=true for real data. What is missing is any statement about when to pick this tool over a neighbouring FRTB or VaR tool, so the guidance is strong within the tool but not comparative.

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