sleeper-mcp

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trade_targets

Identify mispriced fantasy football players by comparing rival lineups to your rankings, flagging buy-low bench assets and sell-high starters.

Instructions

Mispriced players on RIVAL rosters, using revealed preference.

This works with ANY signal source, including a plain ranking.

The insight: a rival's LINEUP is his own valuation of his players, stated every week for free. Setting that against a source he does not have gives two archetypes —

BUY LOW he BENCHED someone your signal rates highly. He is not using the asset, so it is cheap to ask about. SELL HIGH he is STARTING someone your signal rates poorly. His price is at its peak precisely because he believes in him.

An INJURED player benched is listed separately and is NOT evidence of mispricing: the bench is explained by the injury. Buying an injured asset can still be right, but it is a bet on the injury rather than on the owner being wrong, and conflating the two dresses up the most obvious fact in the league as an edge.

Early-season caution: a week-1 bench reflects draft-day opinion, not anything observed. This gets meaningful once managers have seen their teams play.

Args: min_evidence: Ignore thin entries. Default 1. limit: Rows per category. Default 12.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`league_id_`	No
`roster_id_`	No
`min_evidence`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 12, 2026

TDQS

A3.6/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the methodology, output categories, and important caveats about injury and early-season data. It does not cover auth needs or rate limits, but adds substantial behavioral context beyond the schema.

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 long but front-loaded and cleanly structured with headers, bullet-like explanations, and a caveat section. Every part supports correct interpretation, though it is more verbose than typical tool descriptions.

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

Completeness3/5

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

The conceptual explanation is strong and an output schema exists so return format is covered. However, with 4 parameters at 0% schema coverage, the description should explain league_id_ and roster_id_ to be complete for a complex, multi-league 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?

Schema description coverage is 0%, so the description must compensate. It explains min_evidence and limit, including defaults, but completely omits league_id_ and roster_id_, leaving half the parameters undocumented anywhere.

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 clearly states the tool finds mispriced players on rival rosters using revealed preference, and explains the BUY LOW/SELL HIGH archetypes. It does not explicitly name sibling alternatives like trade_block or waiver_targets, but the purpose is specific enough for an agent to distinguish it from generic player tools.

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 explains when the signal is meaningful, gives early-season caution, and states that an injured benched player is not evidence of mispricing. This provides clear usage context, though it stops short of naming explicit alternative tools for related tasks.

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