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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower — but the description still adds real value by disclosing the versioning model (old terms retained as current=false rows) and the provenance caveat that press-only figures are flagged via source_type. It stops short of describing result ordering or pagination behavior.

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?

Two tight sentences with the core purpose front-loaded and the data-model caveats following. The fact-type enumeration is slightly redundant with the field enum but serves the purpose statement, so almost nothing is wasted.

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?

Six optional parameters are all schema-documented and the description supplies the conceptual model (dated facts, version history, source provenance) an agent needs to filter correctly. With no output schema, a brief note on result shape or default ordering would be the remaining gap, but nothing blocking is missing.

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is 3, and the description earns above that by explaining the semantics behind two parameters: current=false retrieves superseded terms, and source_type=press marks non-primary figures. It does not clarify since/limit behavior, but the schema handles those adequately.

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 resource (dated, sourced market facts across programs) and enumerates the concrete fact types covered — payout ranges, rates, caps, fees, timing, eligibility — so an agent knows what comes back. It is distinguishable from get_buyer/list_buyers by being fact-level rather than entity-level, though it never names those siblings explicitly.

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?

Usage is implied rather than stated: the field enumeration tells the agent what questions this answers, and 'History is kept when a term changes (current=false rows)' hints at when to ask for superseded terms. There is no explicit routing guidance against get_buyer, get_tool_terms, or list_buyers, and no stated prerequisites.

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