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Glama

get_client_dpi

Retrieve Deep Packet Inspection statistics for a client by MAC address to identify top applications and network usage.

Instructions

Get Deep Packet Inspection (DPI) statistics for a specific client

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
macYesMAC address of the client
limitNoNumber of top applications to return (default: 10)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals that this is a read operation but adds nothing beyond that — no mention of return format, pagination behavior, whether the client must be online, data freshness, or how results are aggregated. The description essentially restates the tool's name with minimal added context.

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?

A single, front-loaded sentence that names the verb and resource immediately. There is no wasted text, and the expansion 'DPI' is a useful clarification. It could earn a 5 by also naming the differing sibling in the same breath, but as written it is efficiently minimal.

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 simple 2-parameter read tool with no output schema, the description is minimally viable — an agent knows what to call and roughly what to pass. But it lacks any return-value expectations, default behavior for 'limit', or guidance distinguishing it from get_dpi_stats and get_bandwidth_stats, which leaves meaningful gaps for a correct call.

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 100% (both 'mac' and 'limit' have descriptions), so the schema does the heavy lifting. The description's phrase 'for a specific client' reinforces the mac parameter's role and implies per-client scoping, but it does not add meaning beyond what the schema already documents. Baseline 3 is appropriate.

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?

The description states a specific verb ('Get'), a clear resource ('Deep Packet Inspection (DPI) statistics'), and a scope ('for a specific client'). This differentiates it from the sibling get_dpi_stats, which presumably covers network-wide DPI data. However, it does not explicitly name the sibling or the selection criterion, so the differentiation is implicit 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?

No guidance is given on when to use this tool versus alternatives. With 50+ siblings including get_dpi_stats, get_bandwidth_stats, and get_client_details, an agent is left to infer the use case from the name alone. There are no exclusions, prerequisites, or 'use X instead' statements.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.