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Vetroscope MCP

by rankin-works

Get activity sessions

get_sessions

Retrieve continuous activity sessions grouped by app, project, and sub_project within 90-second gaps. Filter by period, app, project, tag, hour, weekday, device, and min duration.

Instructions

Continuous activity blocks reconstructed from the raw 30s entries — the natural grain for 'what did I work on this morning?'. Two consecutive entries are one session when they share the same (app, project, sub_project) and are within 90s of each other. Each session reports start/end/duration and tag/app metadata.

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
appNoRestrict to a single app (canonical name)
projectNoRestrict to a single project (exact match)
tagNoRestrict to entries carrying a tag with this exact name
min_secondsNoDrop sessions shorter than this (default 0 — keep all)
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.
limitNoMax sessions returned (default 200)
Behavior4/5

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

No annotations exist, so the description carries full burden. It explains session definition and metadata returned, but lacks details on edge cases or limitations.

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?

Description is efficient and front-loaded with the core purpose, though the second sentence could be slightly more concise.

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 a tool with 10 parameters and no output schema, the description adequately explains what sessions are and what metadata is returned, making it complete.

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%, so the baseline is 3. Description adds context about session granularity but does not significantly enhance parameter meaning beyond the schema.

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?

The description clearly states the tool reconstructs continuous activity blocks from raw entries, which is specific and distinct from sibling tools like get_app_breakdown or query_entries.

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?

Implies usage for answering 'what did I work on this morning?' but does not explicitly contrast with alternatives or state when not to use.

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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