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Vetroscope MCP

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Get time report

get_report

Get a time report for a period: total active seconds, top apps, and top projects with sub-projects. Filter by device, hour, or weekday.

Instructions

Aggregate Vetroscope time report for a period: total active seconds, top apps, and top projects (with sub-projects nested when present — e.g. individual YouTube videos, SoundCloud songs, Netflix episodes). Apps include the user's custom display_name when set. Applies the same SQLite settings as the desktop dashboard — ignored apps, ignored projects/breakdown patterns, and days_filter — plus optional hour-of-day/weekday/device filters layered on top. totalSeconds is wall-clock (each 30s bucket counted once even if two apps or two devices overlap). Per-app seconds are per-app buckets, so summing apps can exceed totalSeconds on overlap days. Do not sum the app rows and expect them to equal the header.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deviceNoRestrict to a single device. Pass 'current' (or 'this') for the local machine, a device UUID from get_device_breakdown, or a platform name like 'darwin', 'win32', 'browser-extension'. Omit or pass 'all' for no device filter.
periodNotoday | yesterday | week | month | year | a single date YYYY-MM-DD | an inclusive date range YYYY-MM-DD..YYYY-MM-DDtoday
hour_endNoExclusive end hour 0-24 in local time. Combine with hour_start.
top_appsNoMax apps returned (default 50, 0 to omit)
weekdaysNoRestrict to specific weekdays. 0=Sunday, 1=Monday, …, 6=Saturday. Omit or pass [0,1,2,3,4,5,6] for no weekday filter.
hour_startNoInclusive start hour 0-24 in local time. Combine with hour_end (e.g. 9 and 17 = 9am to 4:59pm). Omit both for no hour filter.
top_projectsNoMax projects returned (default 50, 0 to omit)
top_sub_projectsNoMax sub-projects per project (default 25, 0 to omit)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

A4.1/5.0
Behavior5/5

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

With no annotations provided, the description carries full behavioral burden and does so excellently. It reveals non-obvious overlap semantics (30s buckets counted once for totalSeconds, per-app buckets may exceed totalSeconds), warns against summing app rows to equal the header, discloses inherited SQLite settings, and mentions display_name behavior.

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?

The description is moderately long but information-dense, with the core purpose front-loaded in the first sentence. The subsequent caveats about overlap and summing prevent misuse rather than padding, making the length justifiable.

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 an 8-parameter tool with no output schema and no annotations, the description covers output categories, filter behavior, inherited settings, nested sub-projects, and a critical data-integrity warning. An agent has enough context to invoke the tool correctly and interpret its results safely.

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 input schema covers 100% of the 8 parameters with detailed descriptions, so the baseline is 3. The tool description adds useful global context about filter layering and dashboard settings, but it does not add per-parameter semantics beyond what the schema already provides.

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 opens with 'Aggregate Vetroscope time report' and enumerates the returned aggregates (total active seconds, top apps, top projects), making the action and resource clear. It does not explicitly contrast with siblings like get_app_breakdown or get_app_stats, so it stops 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 Guidelines4/5

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

The description makes the intended use context clear: a period-level aggregate report with optional hour-of-day, weekday, and device filters layered over standard dashboard settings. It does not name alternatives or state when not to use it, but the usage context is strong.

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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