Auvik Performance logo

Auvik Performance

Community
automateyournetwork
auvik-performance

Auvik time-series performance stats for devices, interfaces, services, and hardware components — plus SNMP poller history for custom OID values. Use when checking device CPU or memory utilization over time, reviewing interface throughput or packet loss, checking service (ping) latency, pulling component-level stats (fan temperature, PSU power), or querying custom SNMP poller values, from Auvik specifically. For the same kind of question against Zabbix-collected telemetry instead, use `zabbix-metrics-history`.

Overview

Publisherautomateyournetwork
Repositorynetclaw
Skill nameauvik-performance
Stars
680
Forks
189
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by automateyournetwork on GitHub. Read the source before you install it.

Installation

Install the Auvik Performance AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/auvik-performance
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/automateyournetwork/netclaw.git /tmp/netclaw
mkdir -p .claude/skills
cp -r /tmp/netclaw/workspace/skills/auvik-performance .claude/skills/auvik-performance
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Auvik Performance in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Auvik Performance on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Auvik Performance is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Auvik Performance

Query time-series performance statistics from the Auvik monitoring platform: device CPU, memory, bandwidth, and availability; interface throughput and error rates; service (ping) latency; hardware component metrics; and custom SNMP poller values. All data is read-only and sourced from Auvik's collected telemetry.

MCP Server

  • Server: auvik-mcp (NetClaw MCP, Feature 036)
  • Command: python3 mcp-servers/auvik-mcp/auvik_mcp_server.py (stdio transport)
  • Auth: Basic auth via AUVIK_USERNAME + AUVIK_API_KEY
  • Read-only: GET operations only — no write or configuration changes

Available Tools

ToolWhat It Does
auvik_get_device_statisticsTime-series device stats (CPU, memory, bandwidth, packet rates) or availability stats (uptime, outage); stat_id, from_time, interval required
auvik_get_interface_statisticsTime-series interface stats (bandwidth, utilization, packet loss, discards, multicast, unicast, broadcast); stat_id, from_time, interval required
auvik_get_service_statisticsTime-series service (ping) stats — pingTime (latency) or pingPacket (packet loss); stat_id, from_time, interval required
auvik_get_component_statisticsTime-series hardware component stats (temperature, power, utilization, capacity); component_type, stat_id, from_time, interval required
auvik_get_oid_statisticsPoint-in-time current OID values from /v1/stat/oid/deviceMonitor; no time window — returns the most recent polled value
auvik_list_snmp_poller_settingsList configured SNMP poller definitions; tenants required; with_devices=true lists devices assigned to a poller
auvik_get_snmp_poller_historyHistorical SNMP poller time-series; tenants and from_time required; value_type=int requires interval; value_type=string accepts compact

Key Concepts

Tenants = MSP clients. Performance tools accept an optional tenants parameter. Scope to a specific client to avoid cross-tenant data mixing.

Identifier resolution. device and parent_device parameters accept hostnames, IPs, or partial names — resolved automatically to Auvik IDs. The interface parameter on auvik_get_interface_statistics also resolves from name or parent device. Ambiguous matches return ResolutionCandidate[].

from_time and interval are required on all time-series tools. from_time accepts ISO-8601 datetimes or relative shorthand (e.g., -1h, -7d, -30d) which the server converts to ISO-8601. interval must be minute, hour, or day. thru_time is optional — defaults to now.

stat_id enums by tool. Each tool has a fixed set of valid stat_id values:

ToolValid stat_id values
auvik_get_device_statistics (standard)bandwidth, cpuUtilization, memoryUtilization, storageUtilization, packetUnicast, packetMulticast, packetBroadcast
auvik_get_device_statistics (availability; set availability=true)uptime, outage
auvik_get_interface_statisticsbandwidth, utilization, packetLoss, packetDiscard, packetMulticast, packetUnicast, packetBroadcast
auvik_get_service_statisticspingTime, pingPacket
auvik_get_component_statisticscapacity, counters, idle, latency, power, queueLatency, rate, readiness, ready, speed, swap, swapRate, temperature, totalLatency, utilization

component_type on auvik_get_component_statistics. Valid values: cpu, cpuCore, disk, fan, memory, powerSupply, systemBoard. Both component_type and stat_id are required.

SNMP poller flow. Custom SNMP polling is a two-step operation: (1) auvik_list_snmp_poller_settings to discover poller IDs and associated devices; (2) auvik_get_snmp_poller_history to pull time-series values for a specific poller. tenants is required on both calls. value_type=int returns numeric time-series (requires interval); value_type=string returns string-valued OID snapshots (use compact=true to reduce payload size).

auvik_get_oid_statistics vs. auvik_get_snmp_poller_history. auvik_get_oid_statistics returns the most recent polled value for any OID on a device — no time window, no interval. Use it for a quick "what is the current value?" check. Use auvik_get_snmp_poller_history for trend analysis over time.

Pagination. auvik_get_oid_statistics and auvik_list_snmp_poller_settings support cursor pagination. Time-series tools return data arrays directly. Use fetch_all=false + page_first for large poller inventories.

Workflow

Device Health Check (CPU and Memory Trend)

  1. Start GAIT branch: gait_branch with name like auvik-perf-check-<device>-2026-06-21
  2. CPU utilization: auvik_get_device_statistics with stat_id=cpuUtilization, device=<hostname>, from_time=-24h, interval=hour
  3. Memory utilization: re-run with stat_id=memoryUtilization, same device and window
  4. Bandwidth: re-run with stat_id=bandwidth to check overall traffic load
  5. Availability: auvik_get_device_statistics with availability=true, stat_id=uptime, same device and window — confirm no outage periods during the review window
  6. Record in GAIT: commit performance findings with peak values, average utilization, and any anomalies noted

Interface Throughput Review

  1. Identify interfaces: auvik-inventory (auvik_list_interfaces) with parent_device=<hostname> — enumerate interface names
  2. Bandwidth stats: auvik_get_interface_statistics with stat_id=bandwidth, parent_device=<hostname>, from_time=-7d, interval=hour
  3. Packet loss: re-run with stat_id=packetLoss — identify any interfaces with elevated loss
  4. Discards: re-run with stat_id=packetDiscard — input/output queue drops signal congestion
  5. Record in GAIT: commit interface performance summary with top-utilization interfaces and any loss/discard findings

Custom SNMP Poller Investigation

  1. List poller settings: auvik_list_snmp_poller_settings with tenants=<client> — discover available custom pollers and their IDs
  2. Find poller devices: re-run with poller_id=<id>, with_devices=true — confirm which devices report to this poller
  3. Pull numeric history: auvik_get_snmp_poller_history with tenants=<client>, value_type=int, snmp_poller_setting_id=<id>, from_time=-30d, interval=hour
  4. Pull string history (if applicable): re-run with value_type=string, compact=true
  5. Spot-check current value: auvik_get_oid_statistics with device=<hostname>, oid=<oid-string> for a point-in-time reading
  6. Record in GAIT: commit poller findings with OID, device, value trend, and any threshold concerns

Component Temperature / Power Audit

  1. Fan temperature: auvik_get_component_statistics with component_type=fan, stat_id=temperature, parent_device=<hostname>, from_time=-24h, interval=hour
  2. PSU power: re-run with component_type=powerSupply, stat_id=power
  3. Memory utilization (component-level): re-run with component_type=memory, stat_id=utilization
  4. Disk capacity: re-run with component_type=disk, stat_id=capacity
  5. Record in GAIT: commit component health summary with peak values

Integration with Other Skills

SkillHow They Work Together
gait-session-trackingMandatory — start a branch before querying, record every turn, close with gait_log
auvik-inventoryDiscover device and interface names to use as device and parent_device params here
auvik-network-alertsCorrelate performance anomalies with alerts that fired in the same time window
auvik-lifecycleHigh CPU/memory on aging devices combined with EoL status accelerates refresh priority

Environment Variables

VariableRequiredDescription
AUVIK_USERNAMEYesAuvik user email (Basic-auth username)
AUVIK_API_KEYYesAuvik API key (Basic-auth password)
AUVIK_BASE_URLNoRegional cluster URL; defaults to https://auvikapi.us1.my.auvik.com — swap us1 for your region
AUVIK_VERIFY_SSLNoSet false to skip TLS verification (not recommended)
AUVIK_TIMEOUTNoHTTP timeout in seconds (default: 30)
AUVIK_MAX_PAGESNoPagination safety cap for poller settings (default: 50)

Important Rules

  • Read-only — this skill queries Auvik-collected telemetry only. It cannot configure SNMP pollers, change polling intervals, or modify device settings.
  • stat_id, from_time, and interval are required on all time-series tools. Omitting any one returns a ValidationError.
  • component_type is also required on auvik_get_component_statistics — specify the hardware subsystem (e.g., fan, memory) before choosing the stat_id.
  • tenants is required on auvik_list_snmp_poller_settings and auvik_get_snmp_poller_history — the Auvik API enforces this for custom poller endpoints.
  • auvik_get_oid_statistics returns point-in-time data only — it does not accept from_time or interval. Use auvik_get_snmp_poller_history for trend analysis.
  • Refer to devices by name or IP, not by Auvik internal IDs. The resolver handles lookup; raw IDs in prompts are fragile and tenant-specific.
  • Record every session in GAIT — all performance queries, trend findings, and SNMP poller investigations must be committed to the audit trail.

Failure Behavior

  • If a tool call fails with an authentication or connection error, check that AUVIK_API_KEY, AUVIK_BASE_URL, AUVIK_USERNAME are set and valid before assuming a data or device problem.
  • On a tool error (timeout, unreachable host, malformed response), report the failure and its error message directly to the user rather than fabricating or guessing at results.
  • For a confirmed read-only call, check connectivity and retry once if appropriate. For any call that changes state or sends a message, a timeout does not prove the action failed: inspect current state or delivery status before retrying, preserve the required approval/change gates, and do not repeat an action whose outcome is unknown.

Frequently asked questions

What does the Auvik Performance AI skill do?

Auvik time-series performance stats for devices, interfaces, services, and hardware components — plus SNMP poller history for custom OID values. Use when checking device CPU or memory utilization over time, reviewing interface throughput or packet loss, checking service (ping) latency, pulling component-level stats (fan temperature, PSU power), or querying custom SNMP poller values, from Auvik specifically. For the same kind of question against Zabbix-collected telemetry instead, use `zabbix-metrics-history`.

Why use Auvik Performance on TypingMind?

Because you install it once and use it with any model. Auvik Performance is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Auvik Performance in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/auvik-performance. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Auvik Performance?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Auvik Performance?

As many as you like. As long as a model supports skills, you can use Auvik Performance with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Auvik Performance AI skill free?

Yes. It is published on GitHub by automateyournetwork under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇