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Khavel

futpicks-mcp

by Khavel

Run a Backtest

flab_backtest_run

Backtest settled football picks over a date range, applying optional rating, market, edge, or league filters to calculate win rate, ROI, and average edge for data-driven strategy decisions.

Instructions

Run a backtest over settled picks for a date range with optional rating/market/edge/league filters. Returns total picks, wins, losses, win rate, ROI, avg edge, and breakdowns. Requires Pro token. Range max 365 days.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateToYesEnd date YYYY-MM-DD (must be after dateFrom)
marketNoFilter by market enum name (e.g. OU25, H2H3Way, BTTS)
ratingNoFilter by rating
minEdgeNoMinimum edge threshold
dateFromYesStart date YYYY-MM-DD (inclusive)
leagueIdNoFilter by league ID

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.2

TDQS

A3.7/5.0
Behavior3/5

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

Annotations mark readOnlyHint as false, indicating this is not a pure read operation, and the description does not clarify side effects, execution model, or whether running a backtest consumes credits beyond the Pro token requirement. It does add useful constraints like 'Range max 365 days' and the Pro-token prerequisite, but does not fully compensate for the lack of side-effect disclosure.

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?

Three sentences with no filler: purpose, output summary, and key constraints. The most important operational details (Pro token, 365-day max) are included without bloating the description.

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?

For a 6-parameter tool with no output schema, the description covers the essential inputs and return metrics well. The only notable gap is that 'breakdowns' is vague, and it does not say whether the backtest runs synchronously or returns immediately, but overall an agent can reasonably select and invoke this tool.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds the valuable constraint that the date range is capped at 365 days, which is not present in the schema, and it summarizes the optional filter groups (rating, market, edge, league) in a way that helps an agent understand the parameters at a glance.

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 action ('Run a backtest') and resource ('settled picks') with a clear scope: date range and filters. It is clear on its own, but it does not explicitly differentiate itself from the closely related sibling flab_track_record, which could serve a similar historical-results purpose.

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

Usage Guidelines3/5

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

It gives useful context: backtests are over settled picks, require a Pro token, and are limited to 365 days. However, it does not state when to prefer this tool over alternatives like flab_track_record or flab_picks_history, nor does it mention any exclusions.

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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