parlayapi_find_ev

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

With no annotations, the description carries the full burden, and it does well: it explains the comparison methodology, the sharp-book default, the no-vig derivation, and the special three-way soccer handling for draws. It doesn't mention rate limits, errors, or authentication, but for a data-querying tool the core analytical behavior is transparently described.

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 well-structured: the one-line summary leads, followed by an efficient explanation of the methodology and then a clear Args list. Every sentence contributes useful information without repetitious padding.

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 4-parameter tool with no annotations but with an output schema, the description thoroughly covers what the tool does, how it computes EV, which markets it handles specially, and the meaning of every argument. There is no significant missing context needed to invoke it correctly.

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%, so the description must compensate, and it does: every parameter is explained with practical examples (e.g., sport_key: 'baseball_mlb', min_edge: default 2). It even clarifies optionality of markets and defaults for sharp_book and min_edge.

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 opens with a specific verb+resource: 'Find positive-EV bets vs a sharp book's no-vig fair line,' which immediately tells the agent what the tool computes. It also distinguishes itself from arbitrage and middles by focusing on +EV relative to a sharp fair line.

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?

The description clearly explains the intended use: compare soft book prices against a sharp book's no-vig fair line, with defaults and optional filters. It does not explicitly name alternative sibling tools or when-not-to-use, but the algorithm and inputs are concrete enough that an agent can infer appropriate usage.

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