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

With no annotations, the description carries the full burden and does substantial work: it declares the return shape (variance percentage, descending sort), the covered domain (five named pro leagues, college excluded), and output formatting conventions (Kalshi as 42¢ (+138), sportsbooks as -110/+125). It does not cover rate limits, auth requirements, or how ties/identical quotes are handled, which keeps it below the top score.

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?

Front-loaded with the core operation and return shape, then scope rules, then formatting conventions. All five sentences carry information, though the Kalshi/American odds formatting sentence is somewhat tangential to selecting or invoking this specific tool and could be trimmed.

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 5-parameter read tool with no output schema and no annotations, the description supplies the return-value explanation the missing output schema would otherwise provide, plus domain scoping. Remaining gaps are minor: no statement of ordering ties, pagination behavior beyond the limit default, or whether partial data degrades results.

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%, so the baseline is 3; the schema already documents limit, sport/league aliasing, market_name, and min_variance_pct. The description reinforces the omit-sport-for-aggregate behavior and the exclusion of collegiate rows, but adds no new syntax or semantics beyond what the schema fields already state.

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 verb and resource: 'surveys every sportsbook quote for the same side of the same market/line' and returns 'cross-book price variance (best vs. worst decimal odds) as a percentage, sorted descending.' This is unambiguous about what is computed and returned. It stops short of naming the sibling tools (get_arbitrage_opportunities, get_sharp_consensus), so the agent must infer the distinction from 'line-shopping and detecting stale quotes.'

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 explicit usage context ('useful for line-shopping and detecting stale quotes') and concrete scoping rules ('Omit sport for the all-league aggregate', 'Collegiate and NCAA rows are never returned'). What is missing is an explicit when-to-use-this-instead-of-sibling statement; the alternatives are never named or contrasted.

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