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network-aiops

network-aiops

by AIops-tools
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Python
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get_lldp_neighbors_detail

Read-only

Retrieve detailed LLDP neighbor data for a network device, including chassis ID, system name, description, and capabilities to map topology and verify links.

Instructions

[READ] Detailed LLDP neighbors: chassis id, system name/description, capabilities.

Args: target: Device name from config.

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_lldp_neighbors_detail"
  }
}

Input Schema

NameRequiredDescriptionDefault
targetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and the '[READ]' tag reinforces it. The description adds value beyond annotations by disclosing the returned field set (chassis id, system name/description, capabilities), but omits behavior around the optional target (what happens when omitted) and error/empty-result handling.

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?

Compact and front-loaded: the purpose sentence comes first, followed by a terse args note. No filler, though the args block is boilerplate-thin.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-optional-param read tool with no output schema, the description is mostly adequate: annotations cover safety and the return fields are listed. It falls short by not explaining behavior when target is omitted (default null), which an agent needs to invoke it correctly.

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 description coverage is 0% (the only param 'target' has no schema description), so the description must compensate; it does minimally by explaining target is a 'Device name from config.' That meaningfully identifies the expected value, though it doesn't clarify the nullable default or omission behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (detailed LLDP neighbors) and enumerates the extra fields it returns (chassis id, system name/description, capabilities), which implicitly distinguishes it from the bare get_lldp_neighbors sibling. It never names that sibling explicitly, so the differentiation is inferable rather than stated.

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

Usage Guidelines2/5

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

There is no when-to-use guidance and no mention of get_lldp_neighbors as the alternative. The word 'Detailed' hints at a use case but the agent is left to infer when this is preferable over the basic variant.

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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