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

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating safe operation. The description adds behavioral details: weights are normalized internally (revealing stateless transformation), returns aggregate score, stressed positions, hedges, and plain-language summary. With annotations providing safety info, description compensates well with richer behavioral context.

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 description is three concise sentences with no waste. First sentence states core function, second explains parameters and returns, third gives concrete use case — front-loaded with essential information.

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?

Given the tool has one parameter with 100% schema coverage, an output schema (not shown to me but present per context signals), and no nested objects, the description sufficiently covers input requirements, return value categories, and target audience. No gaps remain for an agent to misuse it.

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 coverage is 100%, so baseline is 3. The description adds value by clarifying that weights can be percentages or fractions (flexible formats), that they are normalized internally, and that up to 20 positions are allowed — supplementing the schema's 'maxItems' constraint and abstract weight description.

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 clearly states the tool performs a 'climate stress test' for a 'multi-commodity portfolio', using a specific verb ('stress test') and resource ('portfolio'), with explicit constraints (up to 20 positions, normalized weights). It distinguishes from sibling tools like 'forecast.commodity_outlook' or 'forecast.scenario' by focusing on portfolio-level stress testing with climate scoring and hedging insights.

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 calls out a specific use case ('useful for commodity fund managers evaluating aggregate climate exposure before rebalancing'), which helps decide when to use it. However, it does not explicitly say when not to use this tool or name alternative tools for different scenarios (e.g., single-commodity stress testing could use forecast.scenario).

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