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tweiss777

sleeper-mcp

by tweiss777

get_user

Read-onlyIdempotent

Resolve a Sleeper username or user ID to a public profile, returning user_id, username, display name, and avatar for use in league and draft queries.

Instructions

Resolve a Sleeper username or user ID to its public user profile.

Returns the user's user_id, username, display name, and avatar identifier. Use this first when only a username is known, then pass the returned user_id to get_user_leagues or get_user_drafts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
username_or_user_idYesA Sleeper username or numeric user_id. Usernames are the usual starting point; returned user_id values are stable IDs used by league and draft tools.
Behavior4/5

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

Annotations already cover safety (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the description builds on that by disclosing the return payload (user_id, username, display name, avatar) and adding the context that user_id is a stable identifier for downstream tools. This adds meaningful behavioral context beyond the annotations, though it does not mention error cases or pagination (not needed for a single-profile lookup).

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?

The description is two short paragraphs: the first states purpose, the second lists returns and gives usage guidance. Every sentence earns its place, and critical information (purpose and usage) is front-loaded. No fluff.

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

Completeness5/5

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

For a simple one-parameter lookup with no output schema, the description covers everything an agent needs: what it does, what it returns, how to use it, and how it fits into the toolchain. Annotations already handle safety, and the description fills the remaining gaps (return fields, stable ID intent). Complete for this tool's complexity.

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 coverage is 100% — the parameter description already explains that username_or_user_id accepts a username or numeric ID and that user_id values are stable. The tool description reiterates this but does not add new meaning beyond what the schema provides. Baseline of 3 is appropriate since the schema is the primary source of parameter semantics.

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 verb ('Resolve') and resource ('Sleeper username or user ID to its public user profile'). It clearly names the output fields (user_id, username, display name, avatar identifier) and differentiates from siblings by explaining its role as the entry point before calling get_user_leagues or get_user_drafts. This is unambiguous and distinguishes it from other user/league tools.

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

Usage Guidelines5/5

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

Usage guidance is explicit: 'Use this first when only a username is known, then pass the returned user_id to get_user_leagues or get_user_drafts.' This tells the agent when to invoke this tool and what to do next, naming the alternatives directly. No inference needed.

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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