Skip to main content
Glama

MLB model picks and graded record

invoke_mlb_sim_picks
Read-onlyIdempotent

The BankrollSZN MLB Monte Carlo picks for the day with edge, model chance, no-vig market chance and stake, the game sim numbers, and the graded record (season, last 30 and last 7 days, by bet type, in units, with closing line value). Each pick shows the blended chance it was published at, the raw sim chance, the market weight, and the starters the sim had when it wrote the pick.

Input Schema

NameRequiredDescriptionDefault
teamNo
bet_typeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds rich context about the returned data — edge, model chance, no-vig market chance, stake, sim numbers, graded record, and per-pick fields — which is valuable beyond annotations, though it omits auth or rate limit details.

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 front-loaded with the tool's purpose and return content, and every sentence carries useful detail since there is no output schema. However, the long comma-separated lists are dense and could be easier to parse with structure.

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

Completeness2/5

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

While return values are described thoroughly enough to substitute for a missing output schema, the two input parameters remain completely unexplained. An agent cannot know how to filter by team or bet_type, leaving a significant gap for a tool with optional filters.

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

Parameters1/5

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

The schema has 0% description coverage for team and bet_type, and the description never mentions either parameter. No format, allowed values, or effect of filtering is given, so the description does not compensate for the schema gap.

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

Purpose4/5

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

The description states a specific resource — daily BankrollSZN MLB Monte Carlo picks — and lists the output fields, so an agent knows what it returns. It does not explicitly distinguish itself from other MLB siblings like invoke_mlb_projections or invoke_mlb_game_odds, keeping it from a 5.

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

Usage Guidelines2/5

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

No when-to-use guidance or alternatives are provided. The description implies daily picks retrieval but never says when to choose this over other MLB tools or whether filters are needed.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources