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get_network_state

Collect network state information by running standard show commands and returning a plain-text summary of areas, devices, interfaces, and topology.

Instructions

Run the standard set of show commands and return aggregated results.

This is the lightweight alternative to `get_ai_context`. It produces a
plain-text summary of the current network state (areas, devices,
interfaces, L1/L2/L3 topology, attributes) by invoking the show
commands listed in mcp_config.json -> ai_context_show_commands.

Args:
    master: Master filename inside the working directory
            (e.g. '[MASTER]office.xlsx'), or an absolute path inside
            the working directory.

Returns:
    Concatenated stdout from each show command, grouped by command name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
masterYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

It discloses that show commands are run and results are concatenated stdout. It references a config file for command list. No annotations exist, so the description adequately covers behavior, though more detail on read-only nature could help.

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 yet comprehensive, structured with a summary, details, and formal Args/Returns sections. Every sentence adds value.

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 single parameter and no annotations, the description covers purpose, usage, parameter, and output format completely. It references an output schema which reduces need for return value details.

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?

The description provides a detailed explanation of the 'master' parameter including format and example, far beyond the schema's minimal title. Schema coverage is 0%, but the description fully compensates.

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 'Run the standard set of show commands and return aggregated results' and positions itself as 'the lightweight alternative to get_ai_context', distinguishing it from a sibling tool.

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 explicitly contrasts with get_ai_context, implying this tool is for lighter queries. It lacks explicit when-not-to-use guidance but provides clear context.

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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