roll_up_metric

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

Annotations already establish that this is a read-only, idempotent, non-destructive, closed-world computation, so the safety profile is covered. The description adds genuinely non-obvious behavior: below a paid plan the response omits `algorithm` and `contributions`, which changes how an agent should interpret results.

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 short sentences, front-loaded with the action and the trigger, closing with the plan-gating caveat. Every sentence adds information with no restatement of the name or annotations.

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?

An output schema exists, so return-value explanation is not required, and the description usefully flags the tier-gated omissions from that output. However, for a domain-specific aggregation tool with zero schema description coverage, the inputs an agent must supply are entirely unexplained, leaving a real gap.

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% for four parameters (entity_id, hub_concept_code, fiscal_year, fiscal_period_type with its FY default), and the description explains none of them. The only identifiers it mentions, `algorithm` and `contributions`, are output fields, not inputs, so it does not compensate for the schema gap.

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 action on a specific resource: rebuild a reported figure from its components when the figure is untagged. It also names the sibling it substitutes for (get_fact), so an agent can separate the two without opening schemas.

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?

Gives an explicit routing rule: 'Use when get_fact finds nothing for an aggregate.' The alternative tool and the condition that selects this one are both named, leaving nothing to inference.

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