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HPE Networking Assistant

HPE Networking Assistant

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by hpe-networking-lab
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Python
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get_sle

Retrieve Service Level Expectations (SLE) per site to gauge user-experience quality. View Mist's scores for ap-health, coverage, capacity, successful-connects, and switch/gateway/wan health as percentages.

Instructions

Service Level Expectations (SLE) per site — Mist's user-experience scores as percentages (e.g. ap-health, coverage, capacity, successful-connects, switch/gateway/wan health). Use to gauge experience quality by site.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_sle"
  }
}

Input Schema

NameRequiredDescriptionDefault
org_idNoMist organization id (optional).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.14.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It explains the output type (percentages, example categories) but does not mention whether the data is live, historical, requires specific permissions, or how results are structured. Some context is added, but significant gaps remain.

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?

The description is concise: two sentences with no fluff. The first sentence defines the tool with acronym expansion and examples; the second provides a clear usage directive. Every word earns its place.

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 the tool's simplicity (one optional parameter, no output schema), the description explains the return value well (SLE percentages with examples) and the usage context. It does not specify the exact output structure (e.g., per-site object list), but for this low-complexity tool, the description is sufficiently complete.

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 100% for the single optional parameter org_id, so the baseline is 3. The description does not add any parameter-level detail beyond the schema, which is acceptable given the high schema coverage, but it also does not explain behavior when org_id is omitted (e.g., using active org).

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 that the tool returns Service Level Expectations (SLE) per site as user-experience scores in percentages, with specific examples. It distinguishes itself from sibling tools by focusing on SLE specifically, making its purpose 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 gives explicit context for when to use it: 'Use to gauge experience quality by site.' It does not explicitly mention alternatives or when not to use it, but the context is clear enough given the specialized nature of SLE.

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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