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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description does not need to repeat safety. It adds meaningful behavioral detail: the tool runs a regression, reports which sensitivities are statistically distinguishable from zero, and shows explanatory power (R²). This goes beyond a generic 'calculate factor exposure' and gives the agent a clear mental model of the operation.

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 a single, focused sentence that front-loads the core purpose and includes essential output characteristics (significance, explained variance). It is concise without being terse, though it could arguably be split into two sentences for readability. No waste or redundant phrasing.

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's complexity, the description adequately conveys what the tool does and what the agent will learn (sensitivities, significance, fit). An output schema exists, so return values are covered elsewhere. The description does not mention edge cases like handling of missing data or specific constraints, but these are not critical for tool selection and invocation, especially with schema covering inputs.

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%: both 'holdings' and 'base' are fully described in the input schema. The description itself adds no parameter-specific detail, so the baseline 3 applies. It does not introduce ambiguities or require additional explanation.

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 a specific analytical resource: a four-factor regression (market, size, value, momentum) on portfolio daily moves, and explicitly mentions the outputs (sensitivities, significance, explained variance). This distinguishes it from sibling tools like measure_portfolio or portfolio_structure, which address different analytical questions.

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 implies when to use this tool—when analyzing portfolio exposure to common return factors—but does not explicitly mention alternatives, exclusions, or conditions. It lacks guidance on when not to use it or how it compares to siblings like test_a_change or currency_effect, leaving some inference to the agent.

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