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Network Lab MCP

Network Lab MCP

Official
by CiscoDevNet
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Python
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get_execution_instructions

Retrieve active scenario, operating principles, and reference knowledge for the current task; list stored definitions to discover reusable content and optionally inspect full read-only definitions.

Instructions

Return the operating principles, the active scenario, and the active reference knowledge for the current task: how to behave, what to accomplish, and what reusable knowledge is available. Also returns metadata-only catalogs (name + description) of every stored scenario and reference, so existing knowledge can be discovered and reused. Optional inspect_scenarios / inspect_references (lists of stored definition names from those catalogs) additionally return the full content of those definitions, read-only: inspecting never activates or changes anything, and unknown names fail the call. Definition changes are not made through MCP; propose them and a human reviews and commits them in the CLI. Reloaded from disk on every call.

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_execution_instructions"
  }
}

Input Schema

NameRequiredDescriptionDefault
inspect_scenariosNo
inspect_referencesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it declares read-only behavior ('inspecting never activates or changes anything'), the failure mode for unknown names, disk-reload freshness on every call, and that catalogs are metadata-only. These are exactly the behavioral traits an agent needs before calling.

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 primary return is front-loaded and every sentence carries information, but the opening sentence is dense and the parenthetical gloss ('how to behave, what to accomplish...') adds length without new information. Slightly tighter phrasing would earn a 5.

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 and no annotations, so the description must cover the return contract — and it does, distinguishing the default catalogs from the full-content inspection mode, noting read-only semantics and failure behavior. Nothing essential for a correct call is missing.

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 description coverage is 0%, so the description must supply parameter meaning, and it does: both inspect params are lists of stored definition names drawn from the returned catalogs, and bad names fail the call. It stops short of specifying name formatting or duplicate handling, keeping it at a 4.

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 names a concrete verb and resource — returning operating principles, the active scenario, active reference knowledge, and metadata catalogs — and its scope is clearly distinct from the terminal/topology siblings. An agent can tell exactly what comes back without opening the schema.

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?

It explains the optional inspect parameters' effect and explicitly routes definition changes away from MCP ('propose them and a human reviews and commits them in the CLI'), which acts as a when-not signal. It does not name alternatives for retrieving active state, so it falls short of a full 5.

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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