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ParlayAPI

by io.github.JacobiusMakes
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parlayapi_set_bettable_books

Remember which books the user can bet at, so parlayapi_verdict scopes its best-price and shop recommendations to them automatically (no need to pass region/books every call).

Call this once when a user tells you where they bet ("I'm in the US on
DraftKings and FanDuel"). Pass region OR an exact books list.

Args:
    region: us | eu | uk | au | ca.
    books: exact CSV of book keys, e.g. "draftkings,fanduel,novig". Overrides region.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "parlayapi_set_bettable_books"
  }
}

Input Schema

NameRequiredDescriptionDefault
booksNo
regionNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden. It reveals the stateful nature ('Remember'), the downstream effect on parlayapi_verdict, and the parameter precedence rule ('Overrides region'). It does not explicitly mention whether calling again replaces or merges the stored books, but the core side effect is clearly communicated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the tool's purpose and side effect, then gives a brief when-to-use trigger, then a compact Args section. Every sentence earns its place, and the example input makes the intent instantly clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers when to call, what the tool does, parameter values, and precedence, while the output schema covers return values. Minor gaps exist around whether repeated calls overwrite the saved list and whether there are constraints on valid book keys, but overall the agent has enough to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

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. It does so thoroughly: region values are enumerated, books format is specified with an exact CSV example, and the relationship between the parameters ('Pass region OR an exact books list' and 'Overrides region') is explained. This is much more useful than the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool remembers the user's bettable books and tells how that affects parlayapi_verdict's recommendations. This specific verb+resource combination distinguishes it from the siblings, which compute odds or verdicts rather than store user preferences.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says 'Call this once when a user tells you where they bet' and gives a concrete user utterance as an example. It also clarifies the tool exists so the user no longer needs to pass region/books on every call, though it does not name an exclusionary alternative because no close sibling exists.

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

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