parlayapi_verdict

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

Even though no annotations are provided, the description goes into substantial behavioral detail: it returns no-vig fair price, best available price and book, EV grading, line-shopping nudge, a verdict label, Kelly stake feedback, region-scoped recommendations, and the edge_alert edge case. It also reveals that bettable-books configuration is remembered per key, so the agent understands persistence and configuration behavior without inspecting state.

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 unusually well structured: a high-level verdict, a list of outputs, explicit when-to-use guidance, scoping notes, then a complete Args block with minimal redundancy. Every sentence earns its place, and the most important purpose and usage guidance are front-loaded.

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 complex, 14-parameter tool, this description is complete: it covers the full input space, expected outputs, exceptions (NO_DATA), configuration dependencies, price-risk edge conditions, and the alternative behavior for +EV stakes. It leaves little room for an agent to call the tool without understanding what it needs or what it will produce.

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?

The schema has 0% description coverage, but the description's Args section covers every parameter with practical semantics: sport key format, side options, market values, home/away vs team alternative, player requirement, price override semantics, region values, books CSV format, bankroll meaning, and kelly. This is far beyond the bare schema and fully compensates for the absence of schema-level descriptions.

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 plain-English purpose ('Should I bet this?') and states the tool is a one-call verdict for a specific bet. It clearly identifies the resource (a bet verdict) and the operation (returning fair price, best price, EV grading, and a verdict), which distinguishes it from sibling tools that focus on odds, props, or parlay verdicts.

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 gives explicit when-to-use guidance: use it when a user asks whether a specific bet is worth making or whether they are getting a good number. It also tells the agent NOT to stitch /ev + /consensus + /best-line together, which is a concrete alternative that would otherwise be a common mistake.

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