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Get metric history

get_metrics
Read-onlyIdempotent

Retrieve health metric readings sorted newest first. Filter by metric name, date range, or user to analyze specific health data.

Instructions

Return raw metric readings, newest first, optionally filtered by metric/date.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userNowhich person; defaults to the primary user.
limitNomax rows (capped by server).
sinceNo
untilNo
metricNorestrict to one metric name; omit for all.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations provide readOnlyHint and idempotentHint, indicating safe, repeatable operation. The description adds behavioral details beyond annotations: it specifies the sorting order (newest first) and optional filtering by metric and date. This is helpful context. It does not contradict annotations, so no conflict. A 4 reflects the added value without being exhaustive (e.g., no mention of server-side caps or pagination).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence that is front-loaded with the main action and includes key modifiers. Every word is necessary. No redundancy or filler. Highly concise and well-structured.

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 that an output schema exists (per context signals), the description is not required to explain return values. It covers the tool's core behavior: returns raw readings ordered newest first, with optional metric and date filters. The default limit of 200 is in the schema. The description is adequate for a read-only, idempotent tool with moderate complexity. A 4 reflects that it covers essentials but could mention the user parameter's default behavior for completeness.

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 60% (3 of 5 parameters have descriptions). The description adds meaning for the date parameters (since, until) by stating 'filtered by...date', but does not explain date format or semantics. The metric and limit parameters are adequately described in the schema. The user parameter has schema description but the tool description doesn't highlight its role. Overall, the description provides some added context but does not fully compensate for the 2 undocumented parameters.

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 returns 'raw metric readings, newest first' with optional filtering by metric and date. This verb+resource combination distinguishes it from sibling tools like list_metrics (which lists available metric types) and log_metric (which adds data). The purpose is specific and unambiguous.

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 conveys when to use this tool: to retrieve raw metric readings with optional filters. It implies the context of fetching historical data. However, it does not explicitly mention when not to use it or suggest alternatives like analyze_metric for analysis. The guidance is clear but lacks exclusionary context.

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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