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Vetroscope MCP

by rankin-works

Get time report

get_report

Aggregate time report for any period: total active seconds, top apps, and top projects with nested sub-projects. Filter by hours, weekdays, or device.

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. Totals therefore match Charts/Dashboard totals for the same range.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNotoday | yesterday | week | month | year | a single date YYYY-MM-DD | an inclusive date range YYYY-MM-DD..YYYY-MM-DDtoday
top_appsNoMax apps returned (default 50, 0 to omit)
top_projectsNoMax projects returned (default 50, 0 to omit)
top_sub_projectsNoMax sub-projects per project (default 25, 0 to omit)
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.
hour_endNoExclusive end hour 0-24 in local time. Combine with hour_start.
weekdaysNoRestrict to specific weekdays. 0=Sunday, 1=Monday, …, 6=Saturday. Omit or pass [0,1,2,3,4,5,6] for no weekday filter.
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.
Behavior4/5

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

No annotations are provided, so the description carries full burden. It explains that the report applies SQLite settings (ignored apps, projects) and additional filters, and that totals match dashboard. It does not detail side effects or performance, but for a read-only aggregation tool these are not critical.

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 a single paragraph of moderate length, front-loaded with the main purpose and followed by details. It is informative without being verbose, though a slightly more structured format (e.g., bullet points) could improve scannability.

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?

Given no output schema and no annotations, the description covers what the tool returns (fields like total seconds, apps, projects), how it filters data, and alignment with dashboard totals. It lacks explicit mention of pagination or output format details but is sufficient for a basic understanding.

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?

Input schema has 100% description coverage, so baseline is 3. The description adds context like 'filters layered on top' and nested sub-projects, but does not deepen understanding of individual parameters beyond their schema 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 tool produces an aggregate time report for a period, listing total active seconds, top apps, and top projects with nested sub-projects. While the purpose is specific and includes examples, it does not explicitly distinguish this tool from siblings like get_app_breakdown or get_category_breakdown.

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 implies usage for obtaining totals matching Charts/Dashboard, and mentions filters, but it does not explicitly state when to use this tool versus other breakdown tools or provide conditions for usage.

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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