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

Annotations already cover the safety profile (readOnly, idempotent, closed-world, non-destructive), but the description adds genuinely new facts: the result is identical for every caller and portfolio, and it reads no account data. It also sketches the return shape (topics in reading order, each with a summary and sections), which the output schema also covers, so the marginal value there is small.

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 core definition is front-loaded in the first clause, followed by parameter guidance and then scope limits. Slightly longer than needed — the parenthetical examples of volatility and expected return could be trimmed — but each sentence contributes.

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?

With a rich output schema and full annotations, the description only needs to cover intent, parameter meaning and behavioral scope, all of which it does. An agent has enough to pick the right `tool_name` and understand it will get a static, account-agnostic explanation.

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?

The schema has zero description coverage on the single enum parameter, so the description must carry the load, and it does: it defines `tool_name` as the tool whose figures are in question and illustrates it with two valid values. It stops short of explaining what happens for the more obscure enum values, but the enum list itself bounds the choice.

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 and resource ('How the figures another tool returns are calculated') and clarifies the scope as the model, its assumptions and rationale. This cleanly separates it from the sibling `describe_portfolio_risk` / `describe_portfolio_outlook` tools, which return figures rather than explaining them.

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?

Explains the selection condition for `tool_name` ('the tool whose figures are in question') with two concrete examples, and draws a boundary by saying it 'describes how a model is built, not calibrated values.' It never explicitly says when not to call it, but the boundary sentence does most of that work.

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