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amanharshx
by amanharshx

deployment_metrics

Read-only

Fetch error rate, average latency, and request totals for any deployment, with configurable time ranges and an optional compact sparkline summary.

Instructions

Read metrics for one deployment by owner/deployment or a bare slug (owner defaults to the account owner). The response is one of two shapes selected by sparkline: the default shape carries timeRange (a {start, end} object)/summary/timeSeries, sparkline=true carries requests24h (an array of per-hour points, not a total)/totalRequests/errorRate/avgLatencyMs. The two are never merged; which shape came back is returned as-is. range (e.g. 1h, 24h, 7d; default 24h) is passed through to the server unvalidated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rangeNoTime range, passed through unvalidated (e.g. 1h, 24h, 7d; default 24h).
sparklineNoWhen true, selects the compact sparkline shape (requests24h, totalRequests, errorRate, avgLatencyMs) instead of the detailed shape.
deploymentYesDeployment ref by owner/deployment or a bare slug.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.13
    • changedInput schema / properties / range / description
      Previous value: -"Time range, passed through unvalidated (one of 1h, 6h, 24h, 7d, 30d; default 24h)."New value: +"Time range, passed through unvalidated (e.g. 1h, 24h, 7d; default 24h)."
  2. Addedv0.1.12

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint and destructiveHint annotations, the description discloses the two mutually exclusive response shapes, the exact fields returned for each, and that 'range' is passed through unvalidated. This is significant behavioral context that helps the agent interpret results and anticipate server behavior without contradiction.

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 dense and informative, front-loaded with the core purpose, then detailing response shapes and parameter behavior. While it is a longer paragraph, every sentence adds value and there is no redundancy, so it remains concise relative to the complexity it conveys.

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?

Given the two response shapes and the absence of an output schema, the description fully covers what an agent needs to know: the fields in each shape, the parameter that selects them, and the behavior of range. No critical information is missing for a read-only metrics tool.

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?

With 100% schema coverage, the baseline is 3, but the description adds substantial meaning: it explains the deployment parameter's format (owner/deployment or bare slug), clarifies that sparkline toggles the response shape, and specifies the default and unvalidated nature of range. This goes well beyond the schema descriptions.

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 action ('Read metrics') and the resource ('one deployment'), with specific identifiers ('by owner/deployment or a bare slug'). It distinguishes itself from siblings like deployment_health and deployment_logs by focusing on metrics, and the sibling list confirms it's a distinct read operation.

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 clarifies what the tool does and the default owner behavior, but does not explicitly say when to prefer this over alternatives like deployment_health or deployment_logs. The context is clear enough for an agent to infer its use, but it lacks explicit exclusions or alternative routing.

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