agentmods.dev

multivendor-ai-network-lab: Instructions file for Claude Code

CLAUDE.md

multivendor-ai-network-lab CLAUDE.md is an instructions file for Claude Code from gesh75/multivendor-ai-network-lab. It costs 1,901 tokens per session, scanned A, original, MIT.

Project instructions for a lab that simulates data-center networks from several vendors and includes an AI tool for collecting and analysing network state.

In plain words
What is it for?
They help with the Containerlab EVPN-VXLAN fabric, the Docker Compose multi-region backbone, vendor drivers, telemetry, dashboards, and the operations portal.
Why use it?
They give coding agents the project’s structure, terminology, technologies, and operating rules so changes fit the existing labs and tools.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions CLAUDE.md.

This is gesh75/multivendor-ai-network-lab's own configuration. It tells Claude Code how to work on multivendor-ai-network-lab itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything multivendor-ai-network-lab configures →

not rated 11repo 2d ago A scan 1,901 tokens original MIT
View source ↗ gesh75/multivendor-ai-network-lab gesh75.github.io
Reuse

Borrowing it

Nothing to install: this file belongs to gesh75/multivendor-ai-network-lab. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/gesh75/multivendor-ai-network-lab/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/gesh75/multivendor-ai-network-lab

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for multivendor-ai-network-lab CLAUDE.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/gesh75/multivendor-ai-network-lab/claude-md/github.svg)](https://agentmods.dev/instructions/gesh75/multivendor-ai-network-lab/claude-md)
Your own site
<a href="https://agentmods.dev/instructions/gesh75/multivendor-ai-network-lab/claude-md"><img src="https://agentmods.dev/badge/instructions/gesh75/multivendor-ai-network-lab/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for multivendor-ai-network-lab CLAUDE.md

Your own site · 80×15
<a href="https://agentmods.dev/instructions/gesh75/multivendor-ai-network-lab/claude-md"><img src="https://agentmods.dev/badge/instructions/gesh75/multivendor-ai-network-lab/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 1,901 This file is loaded in full into every session.
When invoked 1,901 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.01901 $0.01901
Opus 5 $0.00950 $0.00950
Sonnet 5 $0.00380 $0.00380
Haiku 4.5 $0.00190 $0.00190

Measured 9d ago against content hash 1f3c054634f6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

multivendor-ai-network-lab CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

CLAUDE.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Multivendor AI Network Lab — Project Context

Repo: multivendor-ai-network-lab (github.com/gesh75/multivendor-ai-network-lab, remote mv) Purpose: Multi-vendor data-center network labs + an AI Network Tool that collects state across vendors via a driver abstraction layer and analyzes it. Stack: containerlab + docker-compose, Nokia SRL / Arista cEOS / FRR, Python (drivers, telemetry), InfluxDB + Grafana, static HTML ops portal.

Naming: this is the AI Network Tool. "DCN Network Tool" was the earlier Acronis-era tool — the directory name DCN_Network_Tool is legacy and kept only for path stability.

Two Labs

CLOS EVPN-VXLAN Fabric (containerlab)

  • Topology: containerlab-multivendor/topologies/clos-evpn.clab.yml
  • 3 spines + 6 leafs + 6 hosts. Vendors: spine1/leaf2/leaf5 = Nokia SRL, spine2/leaf1/leaf4 = Arista cEOS, spine3/leaf3/leaf6 = FRR.
  • eBGP underlay (per-leaf AS 65001–65006, spines AS 65100) + eBGP EVPN overlay (multihop loopback peering, spines as route-reflector-clients/transit).
  • ESI-LAG dual-homed hosts (anycast MAC 00:00:5E:00:53:01), symmetric IRB anycast gateway (L3 VNI 50001, TENANT-A VRF), IPv6 dual-stack (fd00:dc1::/48).
  • Configs: containerlab-multivendor/configs/{spine,leaf}/. SRL nodes need a post-deploy push: containerlab-multivendor/scripts/post-deploy-srl.sh [wait-seconds].
  • Bring-up: containerlab-multivendor/scripts/{setup,deploy,destroy}.sh. Linux uses native containerlab (sudo-aware). macOS Docker Desktop uses ghcr.io/srl-labs/clab with --pid host (scripts/clab-common.sh).
  • cEOS eAPI is baked into leaf1 / leaf4 / spine2 startup-configs for NAPALM (management api http-commands, HTTPS:443). Do not docker restart a node to enable it — redeploy with --reconfigure.

DCN Multi-Region Backbone (docker-compose)

  • Compose: network-lab/docker-compose.yml. 10 FRR routers (5 core + edge/dist), multi-region eBGP, mgmt 10.200.0.0/24. Real device names (de-fra-core-01, uk-lon-core-01, nl-ams-core-01, us-nyc-core-01, …) — NOT clab-prefixed.
  • Configs: network-lab/configs/<device>/frr.conf.

Read the full file on GitHub · 120 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 120 lines · 1,901 tokens per session scan A 1f3c054634f6

Subscribe to this mod's changes

multivendor-ai-network-lab CLAUDE.md is an instructions file published in the GitHub repository gesh75/multivendor-ai-network-lab (11 stars, last pushed 2d ago), licensed MIT. It adds 1,901 tokens to every session, about $0.0095 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

ai-agentsaiopsaristaauto-remediationcontainerlabfrr
Related

Other instructions, from other repositories

next.js AGENTS.md

AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,153 tokens

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

langchain AGENTS.md

AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,469 tokens

deepseek-harness AGENTS.md

AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.

deepseek-ai/deepseek-harness · 3,735 tokens