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get_history

Read-onlyIdempotent

Retrieve historical PC activity samples for a day or time range to explain slowdowns using CPU, memory, disk, network, GPU, and process data.

Instructions

What happened at a time: the history's samples for a day (or part of one), each with CPU, memory, commit, disk and network totals, the GPU, the processes that led, and the processes that started, exited or hung. Answers "why was the PC slow at 14:32".

Input Schema

NameRequiredDescriptionDefault
toNoLocal time of day to end at, HH:MM (default the day's end).
topNoProcesses listed per sample (default 3, at most 10).
dateNoThe day, YYYY-MM-DD (default today); list_history_days lists them.
fromNoLocal time of day to start at, HH:MM (default the day's start).
limitNoAt most this many samples, the latest kept (default 120, at most 2000).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

The annotations already declare this to be a safe read (readOnly, idempotent, non-destructive), so the description's job is to describe substance. It does that by enumerating the metrics and the process categories per sample, which is real added context beyond the annotations. Pagination/truncation semantics live only in the schema's 'limit' description, so the description is not fully self-contained.

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 content is front-loaded: what is returned comes before the sample contents and the motivating question. The first sentence is very dense with a long comma-separated inventory, but every element describes the payload, so little is wasted.

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?

There is no output schema, so the description must convey the return shape, and it does so in reasonable detail, which is the right call for a five-parameter read tool with sensible defaults. What is missing is guidance on volume (samples per request, default 120/max 2000), which matters for how an agent scopes a query.

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%, with date, from/to, top and limit all documented in the schema itself, so the baseline is 3. The description's phrase 'a day (or part of one)' loosely mirrors the date and from/to parameters but adds no format, default or range detail beyond that.

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 states a concrete verb and resource: it returns the history's samples for a day or part of a day, and spells out what each sample contains (CPU, memory, commit, disk, network, GPU, top/started/exited/hung processes). That is far more specific than the bare name 'get_history'. It never names a sibling (e.g. list_history_days for picking a date), so there is no explicit sibling differentiation, keeping it at 4.

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 closing line 'Answers "why was the PC slow at 14:32"' gives a clear, concrete situation in which to reach for this tool, and 'the history's samples' positions it as the historical companion to the live-status tools. It does not say when NOT to use it or point at alternatives, which is the one gap.

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