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damassi

Artsy Analytics MCP Server

by damassi

get_partner_inquiries_stats

get_partner_inquiries_stats

Retrieve partner inquiry analytics, including inquiry count and response times, for specified time periods. Use to analyze and optimize partner performance on Artsy.

Instructions

Get partner inquiry analytics including inquiry count and response times

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
partnerIdYesPartner ID to get inquiry analytics for
periodNoTime period for inquiry dataFOUR_WEEKS
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves analytics (implying a read-only operation) but doesn't cover important aspects like authentication requirements, rate limits, data freshness, or error conditions. For a stats tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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 a single, efficient sentence that front-loads the core purpose without unnecessary words. Every element ('Get partner inquiry analytics including inquiry count and response times') serves a clear purpose, making it easy to parse while maintaining completeness for its length.

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?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers what the tool does but lacks context about when to use it, behavioral details, and output format. Without annotations or output schema, the agent must rely heavily on the description, which doesn't fully compensate for these gaps.

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?

The description doesn't add any parameter information beyond what's already in the schema (which has 100% coverage). It mentions 'partner inquiry analytics' which aligns with the 'partnerId' parameter, and 'analytics' implies some time period, matching the 'period' parameter. However, it provides no additional context about parameter usage, constraints, or relationships beyond the schema's descriptions.

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 verb 'Get' and the resource 'partner inquiry analytics', specifying the metrics included (inquiry count and response times). It distinguishes this tool from siblings like 'get_partner_sales_stats' or 'get_partner_audience_stats' by focusing on inquiry analytics, though it doesn't explicitly contrast with 'get_partner_inquiry_time_series' which might offer similar data in a different format.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_partner_inquiry_time_series' (which might provide time-series data) or 'get_partner_complete_analytics' (which might include broader metrics), leaving the agent to infer usage context from tool names alone.

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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