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Python
Remote

get_resource_metrics

Read-onlyIdempotent

Fetch time-series metric statistics for a VMware Aria resource by UUID. Returns raw data points or per-metric summaries, and flags requested keys with no data instead of reporting zero.

Instructions

[READ] Fetch time-series metric statistics for a resource.

Returns mode ("raw" or "summary"), then metrics (raw: metric key -> list of {timestamp_ms, value} points, only keys with points) or summary (summary=True: per key n, min, max, avg, latest, first/latest timestamps, change_count and change_points — {timestamp_ms, from, to} where the value changed, at most 50, most recent kept), and missing (one entry per requested key with no points: not_collected_for_resource with similar_keys to try, no_data_in_window, resource_reports_no_stat_keys, or undetermined). Never report a missing key as zero. Prefer summary=True for windows over a few hours. Over days or weeks, set interval_type="DAYS" (or "HOURS"): the default is one point per 5 minutes, about 8,600 per key for a month. Each point is rollup_type over its span, so with AVG the summary max is the highest daily average, not the peak: use rollup_type="MAX" for peaks. interval in the result gives the resolution requested and, in applied, the one Aria reports it used. For a single current score use get_resource_health instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hoursNoNumber of hours of history to retrieve. Default 1.
targetNoAria target name from config; default when omitted.
summaryNoReturn per-metric summaries instead of every point. Default False.
metric_keysYesMetric keys to fetch, e.g. ["cpu|usage_average", "mem|usage_average", "disk|usage_average", "net|usage_average"].
resource_idYesThe resource UUID.
rollup_typeNoAggregation type: AVG, MAX, MIN, SUM, COUNT, LATEST. Default AVG.AVG
interval_typeNoSpan each point covers: MINUTES, HOURS, DAYS, WEEKS or MONTHS. Default MINUTES. Each point is rollup_type over the span, so DAYS with AVG gives daily averages.MINUTES
interval_quantityNoNumber of interval_type units per point, at least 1. Default 5 (with MINUTES: Aria's 5-minute collection).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.2.0
    • addedInput schema / properties / interval_quantity
      Added value: +{
+  "default": 5,
+  "description": "Number of interval_type units per point, at least 1. Default 5 (with MINUTES: Aria's 5-minute collection).",
+  "title": "Interval Quantity",
+  "type": "integer"
+}
    • addedInput schema / properties / interval_type
      Added value: +{
+  "default": "MINUTES",
+  "description": "Span each point covers: MINUTES, HOURS, DAYS, WEEKS or MONTHS. Default MINUTES. Each point is rollup_type over the span, so DAYS with AVG gives daily averages.",
+  "title": "Interval Type",
+  "type": "string"
+}
  2. Changed1 schema field changedv1.15.0
    • addedInput schema / properties / summary
      Added value: +{
+  "default": false,
+  "description": "Return per-metric summaries instead of every point. Default False.",
+  "title": "Summary",
+  "type": "boolean"
+}
  3. Changed6 schema fields changedv1.10.0
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / hours / description
      Added value: +"Number of hours of history to retrieve. Default 1."
    • addedInput schema / properties / metric_keys / description
      Added value: +"Metric keys to fetch, e.g. [\"cpu|usage_average\", \"mem|usage_average\", \"disk|usage_average\", \"net|usage_average\"]."
    • addedInput schema / properties / resource_id / description
      Added value: +"The resource UUID."
    • addedInput schema / properties / rollup_type / description
      Added value: +"Aggregation type: AVG, MAX, MIN, SUM, COUNT, LATEST. Default AVG."
    • addedInput schema / properties / target / description
      Added value: +"Aria target name from config; default when omitted."
  4. Addedv1.5.29
  5. Removedv1.5.28
  6. First observedv1.3.2

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only cover the safety profile (readOnly, idempotent, non-destructive); the description goes well beyond them. It discloses missing-key semantics and warns 'Never report a missing key as zero', caps change_points at 50 most-recent, quantifies volume (~8,600 points per key per month), and warns that AVG summary max is the highest daily average, not the true peak.

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?

Front-loads the return shape before the tuning advice, and every sentence carries information. It is dense and parenthetical-heavy, requiring careful reading, but there is little outright waste.

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?

There is no output schema, so the description carries the full return-value burden and does so: it documents mode, the raw and summary shapes, and the missing-entry variants. Combined with its usage guidance, an agent has everything needed to call and interpret this tool.

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 is 100%, so the baseline would be 3, but the description adds real meaning: the interaction between rollup_type and interval_type, what 'interval applied' in the result means, and the practical default resolution. Some of this (DAYS+AVG = daily averages) duplicates the schema, keeping it below 5.

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?

Opens with a specific verb+resource ('Fetch time-series metric statistics for a resource') and explicitly distinguishes itself from the sibling get_resource_health ('For a single current score use get_resource_health instead'). An agent can route correctly without opening either schema.

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?

Gives explicit when-to-use guidance: prefer summary=True for windows over a few hours, set interval_type='DAYS'/'HOURS' for day/week windows, use rollup_type='MAX' for peaks. It also names the alternative tool and the condition that selects it.

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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