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mrh-is

partiful-mcp

by mrh-is

get_users_party_stats

Read-onlyIdempotent

Fetch events attended and hosted counts for multiple Partiful user IDs in one call, returning stats keyed by each user ID.

Instructions

Get just the party stats (events attended count, events hosted count) for a batch of Partiful user IDs — lighter weight than get_users, which returns full profile info (name, username, profile image) with party stats always baked in as well. Returns statsByUserId, an object of stats keyed by user ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoDot-path field names to include in the response. Omit to return all fields. Available fields: statsByUserId
user_idsYesArray of Partiful user IDs to look up

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statsByUserIdNo
Behavior4/5

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

Annotations already declare read-only and idempotent behavior, so the bar is lower. The description adds context by specifying the return shape ('statsByUserId') and noting what it does not return (full profile info), which informs expected behavior without contradicting annotations.

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 sentences, front-loaded with the tool's core purpose, then a useful contrast, then the return shape. Every sentence earns its place with no redundancy.

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?

Given the simple batch lookup, the presence of an output schema, and strong annotations, the description is complete enough for the agent to select and invoke the tool correctly. It covers purpose, when to use, and return shape.

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% with descriptions for both parameters. The description adds minimal extra meaning beyond noting 'batch' and the return key, so the baseline of 3 is appropriate as schema carries the heavy lifting.

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 clearly states it 'Get just the party stats' for 'a batch of Partiful user IDs', using a specific verb and resource. It explicitly contrasts with the sibling get_users, distinguishing itself by what it returns and omits.

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 clearly indicates when to use this tool by noting it is 'lighter weight than get_users' and explaining what get_users returns instead. This implies use this for stats-only needs, though it doesn't explicitly state exclusions or alternative scenarios.

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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