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brunosemfio

app-store-connect-mcp

by brunosemfio

list_report_instances

Read-onlyIdempotent

List report instances by granularity and processing date to identify available data versions for a given report.

Instructions

List the instances of a report: one per granularity and processing date.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoInstances per page (1-200).
cursorNoPagination cursor returned by a previous call.
report_idYesID from list_reports.
granularityNoOptional "DAILY", "WEEKLY" or "MONTHLY".
processing_dateNoOptional "YYYY-MM-DD" date the instance was processed.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already cover the safety profile (read-only, idempotent, non-destructive). The description adds the useful invariant that results are defined per granularity and processing date, but it doesn't disclose pagination or any other runtime behavior. This is appropriate but modest given the annotation coverage.

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?

A single sentence with no filler; the most important scoping concept is front-loaded. It is efficiently structured and easy to scan.

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?

With a fully self-describing schema, safety annotations, an output schema, and pagination parameters documented, the description does not need to repeat lower-level details. The only missing conceptual piece, the uniqueness of instances, is present in the opening sentence.

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%, and each parameter has a meaningful description (defaults, allowed formats, source of report_id). The tool description adds the 'one per granularity and processing date' context but no per-parameter semantics beyond the schema. This meets the baseline for well-covered parameters.

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 states a clear action ('List') and resource ('instances of a report'), and it clarifies the entity by adding 'one per granularity and processing date.' It is distinguishable from sibling list tools, but it doesn't explicitly name alternatives, so it falls just short of full differentiation.

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

Usage Guidelines3/5

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

The description provides a concise definition but no explicit when-to-use versus alternatives like list_reports or download_report_instance. The intended context can be inferred from 'instances of a report,' but the agent is not told when not to use this tool. That yields implied, rather than explicit, usage guidance.

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