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

Annotations already declare readOnly, idempotent, non-destructive, and open-world, so the safety profile is covered. The description adds genuinely new behavioral context by flagging it as a free-tier endpoint (a quota/cost signal an agent should weigh) and by listing the return payload fields, which matters since no output schema exists.

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 tier/cost caveat front-loaded, followed by the payload and a concrete example query. The field enumeration is dense but earns its place because no output schema exists.

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?

For a one-parameter, read-only lookup with no output schema, the description supplies the return fields, the cost tier, and a representative question. There is nothing an agent would need to know before calling it that 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?

With a single parameter at 100% schema description coverage, the schema already documents sport_key and its example format. The description only says 'for a sport,' adding no new syntax, enumeration, or fallback guidance beyond the structured field, so the baseline of 3 applies.

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 states a specific verb+resource (retrieving per-book odds history coverage for a sport) and enumerates the returned fields, so the agent knows exactly what data comes back. It does not, however, differentiate itself from look-alike siblings such as propline_get_market_coverage or propline_get_odds_history, which a 'coverage' tool arguably should.

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 conveyed only by implication plus one quoted example question ('how far back do we have Fanatics MLB props'), which anchors the use case well. There is no explicit when-not guidance and no named alternative for adjacent questions like market coverage or actual historical odds values.

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