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ThoTischner

observability-mcp

query_metrics

Fetch raw time-series data and pre-computed summary statistics for one metric of a service to identify trends or exact values over a look-back window.

Instructions

Fetch the raw time-series for ONE metric of ONE service over a look-back window, returned together with pre-computed summary statistics. When to use: when you need the actual numeric values or the trend of a known metric. For a 'is this service OK?' verdict use get_service_health; to find which services are misbehaving use detect_anomalies. Prerequisites: get the exact service name from list_services and choose a metric from the list at the end of this description. Behavior: read-only, no side effects. Returns an ordered array of {timestamp, value} points plus a summary {current, average, min, max, trend}. With groupBy set, returns one labelled series per distinct label value under groups instead of a single aggregated series. Units depend on the metric (e.g. CPU as %, latency as ms, rates as per-second). An unknown service/metric or an unreachable backend yields a structured explanatory error, never an exception. Available metrics: No metrics sources configured.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
serviceYesRequired. Exact, case-sensitive service name exactly as returned by `list_services` (e.g. 'api-gateway', 'payment-service').
metricYesRequired. Exact metric name to query. One of: .
durationNoOptional. Look-back window ending at 'now', written as <number><unit> with unit s|m|h|d (e.g. '5m', '90m', '1h', '24h'). Default: '5m'.
sourceNoOptional. Restrict the query to a single backend by its source name (see `list_sources`). Default: query and merge all metrics backends.
groupByNoOptional. Metric label to break the result down by, e.g. 'instance', 'pod', 'node'. When set, the response contains one series per distinct label value under `groups`. Default: a single aggregated series.
Behavior4/5

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

No annotations provided, so description carries full burden. It states read-only, no side effects; explains groupBy behavior, units, and error handling. Missing explicit auth/rate limit info but otherwise thorough.

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?

Well-structured with clear sections. Slightly verbose but every sentence adds value. Could tighten slightly but overall efficient.

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 5 params, no output schema, no annotations, description covers return format, error handling, groupBy, units, prerequisites. Missing explicit default for 'source' but minor.

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

Parameters4/5

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

Schema coverage 100%, baseline 3. Description adds value: explains how to get service name, duration format, groupBy behavior. Improves usability beyond 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 it fetches raw time-series for one metric of one service, and distinguishes itself from sibling tools by naming alternatives (get_service_health, detect_anomalies).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to use (need numeric values/trend) and when not (use get_service_health or detect_anomalies). Provides prerequisites: get service name from list_services, choose metric from list.

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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