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jmercer187

sleeper-mcp

by jmercer187

get_draft_state

Fetch a normalized Sleeper draft board with league settings, team on the clock, recent picks, rosters, drafted players, and position counts for live draft assistance.

Instructions

Fetch the full normalized draft board for a Sleeper draft.

This is the primary tool for live-draft assistance. It combines the league settings (scoring, starting lineup), the draft metadata, the team on the clock, recent picks, every roster with slot assignments, all drafted player IDs and position counts into one compact payload.

Args: draft_id: The Sleeper draft ID (numeric string).

Input Schema

NameRequiredDescriptionDefault
draft_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the composition of the payload and that it is 'normalized' and 'compact', and 'Fetch' makes the read-only nature clear, but it says nothing about data freshness (critical for a live draft), whether calls are rate-limited, or any auth/prerequisite requirements.

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?

Front-loaded with the core purpose, followed by the payload breakdown and a short args block. Every sentence carries information; only the Args section partially restates the schema, but it adds the numeric-string format so it still 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?

An output schema exists, so return values needn't be re-explained, and the single required parameter is documented. The only gap is behavioral context an aggregating live tool should mention (freshness/latency), which keeps it from a 5.

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 0% (the single property has no description), so the description must compensate — and it does, specifying 'The Sleeper draft ID (numeric string)', which adds a format constraint the schema does not encode. That is the only parameter, and it is fully explained.

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?

States a specific verb and resource ('Fetch the full normalized draft board for a Sleeper draft') and immediately scopes it further as the primary live-draft tool. The aggregation sentence ('combines league settings, draft metadata, team on the clock, recent picks, every roster... into one compact payload') implicitly differentiates it from get_draft, get_draft_picks, get_rosters and get_league by showing it supersedes them.

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?

'This is the primary tool for live-draft assistance' gives an explicit use context that an agent can act on. It stops short of naming when to prefer the narrower siblings (e.g. get_draft_picks) instead, so it lacks explicit alternatives or exclusions.

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