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

Annotations already mark the tool as read-only, idempotent, and non-destructive, and the description adds valuable context: it is a research signal, not investment advice, costs $0.05 per call, and returns a payment-required error when unpaid. It also discloses the renormalization of composite_score and the inclusion of governance flags, going beyond what annotations convey.

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 long but every sentence carries distinct information: output composition, factor categories, derived metrics, alternative tool, disclaimer, and cost. It is front-loaded with the core purpose and structured so an agent can quickly extract behavior, alternatives, and constraints.

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 and the presence of an output schema, the description covers the purpose, output contents, factor weighting behavior, alternative tool, cost, and error condition. An agent has sufficient context to invoke the tool correctly and interpret its results without missing critical details.

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%, with detailed parameter descriptions for both cik and weights, including defaults, factor names, and behavior for invalid keys. The description itself does not add parameter-level meaning beyond the schema, so the baseline score of 3 is appropriate.

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 is a composite factor scorecard for one company, enumerating the specific factor categories and output components. It also distinguishes itself from top_signals by noting that tool is used to rank every company, leaving no ambiguity about the tool's scope.

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 explicitly names top_signals as the alternative for ranking companies, which helps an agent choose between single-company scoring and cross-company ranking. It does not enumerate all possible exclusions, but the single-company focus and sibling differentiation provide clear enough guidance for typical use.

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