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Vetroscope MCP

by rankin-works

Query raw entries

query_entries

Retrieve filtered raw tracking entries by project, tag, app, search, or time period to analyze specific activity details.

Instructions

Filtered list of raw tracking entries. Useful for digging into specific projects, tags, or finding what window titles appeared. When a period is set, respects the same dashboard exclusions stored in SQLite (ignored apps/projects/breakdown patterns, days_filter) plus optional hour/device filters so aggregates stay consistent with Charts; omit period to bypass those scope rules while still filtering by tag/app/search/etc. Defaults to active foreground entries only — pass mode='passive' or 'all' to include away-listening (background music while idle). Returns at most 5000 rows; default 200.

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-DD
appNoRestrict to a single app name (canonical name, not display_name)
projectNoRestrict to a single project (exact match)
tagNoRestrict to entries carrying a tag with this exact name
searchNoSubstring match against window title, project, or sub-project
modeNoactive = foreground only (default), passive = away-listening only, all = both
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.
limitNo
Behavior4/5

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

With no annotations, the description must cover behavioral traits. It discloses default mode ('active'), row limits (5000 max, 200 default), period-dependent exclusions, and optional filters. It does not explicitly state if the operation is read-only, but that is implied.

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 that efficiently conveys key details. However, it mentions the default limit twice ('default 200' appears at both the start and end), which slightly reduces conciseness.

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 11 optional parameters and no output schema, the description covers all necessary behavioral aspects: filtering semantics, period behavior, mode, limits, and special parameter values. An agent can confidently select and invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers 91% of parameters with descriptions. The description adds significant value beyond schema: it explains period exclusions, default mode, how hour_start/hour_end combine, and special device values like 'current'. This additional context is highly informative.

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 'Filtered list of raw tracking entries,' identifying the specific verb and resource. It further explains use cases like digging into projects and tags, distinguishing it from sibling tools that provide aggregate breakdowns.

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 explains when to use the tool (for specific searches) and contrasts behavior with/without a period filter. However, it does not explicitly state when not to use it or name alternative tools for other purposes.

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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