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futpicks-mcp

futpicks-mcp

by Khavel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Export Picks (CSV)

flab_export_picks
Read-onlyIdempotent

Export settled football picks into a CSV file for a specified date range, applying optional market or rating filters to analyze the verified public track record.

Instructions

Export settled/published picks as CSV for a date range with optional market/rating filters. Returns raw CSV text. Requires Pro token.

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": "flab_export_picks"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoEnd date YYYY-MM-DD
fromNoStart date YYYY-MM-DD
marketNoFilter by market
ratingNoFilter by rating

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds meaningful context beyond annotations by stating that it returns raw CSV text and requires a Pro token, which are useful operational constraints not otherwise visible.

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?

Two concise sentences with no filler. The first sentence communicates the core action, scope, and filters; the second covers return type and auth. Essential information is front-loaded and every phrase earns its place.

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 the output format (raw CSV), the auth requirement (Pro token), and the core filtering dimensions. Without an output schema, stating the return format is important and handled well. Minor gap: since all parameters are optional, defaults for date range or filtering behavior are not specified, but this does not undermine the core call.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema fully documents to, from, market, and rating. The description only summarizes these as 'date range with optional market/rating filters' without adding extra semantic detail, which is acceptable given the schema already carries the burden.

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 states a specific action (Export), a specific resource (settled/published picks), and a concrete output format (CSV). It clearly distinguishes this from sibling list/query tools by framing it as an export operation with date range and optional market/rating filters.

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?

The description gives clear context: use this when you need settled/published picks as CSV within a date range, with optional filtering. It does not explicitly name alternative tools or exclusion conditions, but the export-oriented wording and raw CSV return signal a distinct use case from sibling tools such as flab_picks_history or flab_pick_details.

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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