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vs_analytics

Read-onlyIdempotent

Retrieve L4 and L7 performance metrics for a virtual service over the past hour to diagnose throughput or latency issues.

Instructions

[READ] Show performance metrics for one Virtual Service over the last hour.

Queries the AVI analytics collection API with a fixed window: 12 samples at 5-minute granularity. Returns L4 metrics (avg bandwidth, completed and new connections) and L7 metrics (avg client transaction latency, % response errors, total responses). Empty output means the VS had no traffic in the window or analytics collection is disabled — not an error. Use when investigating throughput or latency issues after vs_status shows degraded health; use vs_error_logs for per-request error detail with a configurable time window.

Args: vs_name: Exact Virtual Service name, case-sensitive, as shown by vs_list. Fails with a 'not found' message if no VS matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vs_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds substantial behavioral details: fixed time window (12 samples at 5-min granularity), specific L4/L7 metrics returned, explanation of empty output (no traffic or disabled analytics), and that a non-matching VS name produces a 'not found' error. No contradictions with annotations.

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 well-structured with a [READ] tag, purpose, technical details, usage guidance, and parameter documentation. It is concise but could be slightly more terse; however, every sentence adds value and no extraneous content exists.

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 output schema exists, the description appropriately does not detail return structure but explains what metrics are returned and what empty output means. It also covers the fixed time window and parameter behavior. For a single-parameter read-only tool with rich annotations, the description is fully complete.

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?

Schema coverage is 0%, so the description must fully explain the parameter. It does so thoroughly: vs_name is exact, case-sensitive, as shown by vs_list, and failure behavior ('Fails with a not found message'). This provides complete semantic meaning beyond the 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 the tool shows performance metrics for a single Virtual Service over the last hour, specifying the resource, action, and time window. It also distinguishes from sibling tools like vs_error_logs by contrasting purpose and configurability.

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?

The description explicitly advises when to use this tool ('when investigating throughput or latency issues after vs_status shows degraded health') and when to use an alternative ('use vs_error_logs for per-request error detail with a configurable time window'). This provides clear decision guidance.

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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