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get_mlb_props_sheet

[$5 per call] News Gurus Intel API — the FULL daily MLB props sheet: News Guru's derived HR & hits+runs+RBIs picks, batter-vs-pitcher matchups, SP strikeout plays, F5 plays, per-game model predictions and per-game props. Park/weather/sim/Statcast used internally — not redistributed. Roster/injury/lineup verified. One call = the whole day's sheet ($5/day). Entertainment/educational only, not betting advice. 21+. HOW TO PAY: an x402-capable client settles the payment challenge automatically (USDC on Base, no account needed); wallet-less clients pass a subscriber API key instead (Authorization: Bearer , X-API-Key header, or ?api_key= query) for calls within their plan. Browse every tool + price first with the FREE get_catalog tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo

TDQS

A4.1/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does an excellent job: it discloses the $5 per call cost, one-call-for-whole-day behavior, payment authentication methods (x402 or API key), legal/age warnings, that proprietary park/weather/sim/Statcast data is used internally and not redistributed, and that roster/injury/lineup info is verified. This is exemplary transparency.

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

Conciseness4/5

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

The description is dense but well-structured, starting with the cost and core purpose, then drilling into content, disclaimers, and payment. Every sentence provides meaningful information, though it is longer than necessary and could be slightly more scannable with line breaks or a shorter payment explanation.

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?

Given no output schema and no annotations, the description covers nearly all critical context: content, cost, payment, legal, and data sourcing. Missing elements are explicit guidance on the 'date' parameter format/defaults and a description of the response structure. Otherwise it is very complete for a single-sheet daily data tool.

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

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has one parameter 'date' (type string, default '') with 0% description coverage. The tool description never mentions the date parameter at all—no format (e.g., YYYY-MM-DD), no default behavior, no example. While the parameter name is self-explanatory, the description adds no value beyond the schema and fails to clarify how to request a specific day.

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 identifies the tool as retrieving the 'FULL daily MLB props sheet' and enumerates specific content (HR & hits+runs+RBIs picks, batter-vs-pitcher matchups, SP strikeout plays, etc.). The use of 'FULL' and 'whole day's sheet' distinguishes it from sibling tools like get_mlb_top_picks and get_sports_props.

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 clearly states when to use the tool (for the full day's entire sheet) and directs users to browse the catalog first, but does not explicitly name alternative sibling tools or state when NOT to use this one. The distinction from a top-picks variant is implied but not explicit.

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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TDQS

B3.4/5.0
Disambiguation5/5

Every tool targets a unique resource or data feed, from agent status and macro snapshots to Polymarket whale analytics and MLB props. There is no overlap or ambiguity between tools, even those within the same domain (e.g., the multiple Polymarket tools are clearly distinguished by their focus on landscape, stats, new wallets, leaders, and flagged whales).

Naming Consistency5/5

The naming follows a consistent get_<resource> pattern for all 35 data retrieval tools, with only verify_memecoin deviating but still using a clear verb-noun structure. The pattern is uniform and predictable, making it easy for an agent to infer the purpose of any tool.

Tool Count2/5

With 36 tools, this significantly exceeds the typical well-scoped range of 3-15. While the server covers a broad range of market intelligence domains, the sheer number of tools makes navigation and selection challenging for an agent, placing it in the 'too many' category.

Completeness4/5

The API provides comprehensive coverage across signals, sentiment, on-chain data, institutional activity, sports, and macro, with both broad aggregate tools and per-symbol/asset specifics. Minor gaps exist, such as a lack of direct news headlines or a fear-greed index, but these are not critical dead ends given the stated purpose of delivering derived intelligence.

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