Skip to main content
Glama
laughnan

arcade-matter-mcp

by laughnan

SummarizeReadingTime

Matter_SummarizeReadingTime
Read-onlyIdempotent

Summarize reading time over a date range: total and average minutes, days read, longest streak, busiest day, and current streak; use it to answer how much you read this month.

Instructions

Summarize how much the user read over a period: total and average minutes, days read, the longest streak, the busiest day, and the current streak when the period reaches yesterday or today. Use this to answer "how much have I read this month?" or "how much did I read in September?". Makes up to 10 requests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNoStart of the period, as an ISO date (YYYY-MM-DD). Defaults to 30 days ago.
untilNoEnd of the period (inclusive), as an ISO date. Defaults to today.
timezone_nameNoIANA time zone used to assign sessions to days, e.g. 'America/Los_Angeles'. Defaults to UTC.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, open-world, non-destructive, so the safety profile is covered. The description adds real behavioral context beyond them: a cost signal ('Makes up to 10 requests') and the conditional rule that the current streak is only reported when the period reaches yesterday or today.

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 purpose, then the output inventory, then usage examples and the request-cost note. The output enumeration is somewhat long, and since an output schema exists it partly duplicates structured data, but it remains readable and every clause is informative.

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?

For a read-only aggregation tool with a full output schema, the description covers purpose, trigger questions, cost, and the streak-reporting condition. The only minor gap is no explicit routing against ListReadingSessions, but nothing essential to calling it correctly is missing.

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 description coverage is 100%, so the schema already documents since/until/timezone_name with defaults and formats. The description adds no parameter syntax or defaults beyond what the schema provides, aside from the implicit linkage of 'until' to the streak behavior. Baseline 3 applies.

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?

Specific verb (summarize) plus resource (reading time over a period), and it enumerates exactly what the summary contains: totals, averages, days read, longest streak, busiest day, current streak. This clearly separates it from Matter_ListReadingSessions, which returns raw sessions rather than aggregates.

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?

Gives concrete user-question triggers ('how much have I read this month?', 'how much did I read in September?'), which tells the agent when to reach for this tool. It stops short of explicitly naming the raw-session alternative (ListReadingSessions) and when to prefer that instead.

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