Borrowing it
Nothing to install: this file belongs to automateyournetwork/netclaw. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/automateyournetwork/netclaw/main/AGENTS.mdgit clone --depth 1 https://github.com/automateyournetwork/netclawWrote 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.
[](https://agentmods.dev/instructions/automateyournetwork/netclaw/agents-md)<a href="https://agentmods.dev/instructions/automateyournetwork/netclaw/agents-md"><img src="https://agentmods.dev/badge/instructions/automateyournetwork/netclaw/agents-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.
<a href="https://agentmods.dev/instructions/automateyournetwork/netclaw/agents-md"><img src="https://agentmods.dev/badge/instructions/automateyournetwork/netclaw/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.11191 | $0.11191 |
| Opus 5.5 | $0.04476 | $0.04476 |
| Sonnet 5.5 | $0.02238 | $0.02238 |
| Haiku 4.5 | $0.01119 | $0.01119 |
Grade A, and why
netclaw AGENTS.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 today.
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.
How it starts
The opening of the file, as written. The whole thing — 653 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NetClaw Operating Instructions
Startup Protocol
- Read
SOUL.md— your identity, expertise, and rules - Read
USER.md— who your human is and what they expect - Read
TOOLS.md— local infrastructure details - Read daily memory files if they exist (
memory/YYYY-MM-DD.md) - Start a GAIT session branch before doing any work
Memory System
NetClaw uses a two-layer memory architecture: file-based daily logs for raw session history, and MemPalace for structured, searchable long-term memory.
Daily Logs (File-Based)
- Write session notes to
memory/YYYY-MM-DD.mdat the end of each session - Include: what was asked, what was found, what was changed, what tickets were created
- These are raw logs — write everything, curate later
Long-Term Memory (MemPalace)
- Use
mempalace_searchto recall past decisions, troubleshooting steps, and architecture choices - Use
mempalace_add_drawerto store important decisions with wing/room taxonomy - Use
mempalace_kg_addto record temporal network facts (e.g., device upgrades, peer changes) with validity windows - Use
mempalace_diary_writeat session end to journal observations in AAAK compressed format - Periodically distill important patterns from daily logs into MemPalace drawers
- Examples: "R1 crashes every Tuesday at 03:00 UTC — TAC case open", "ISP circuit to Site-B has 200ms latency spikes during business hours"
Learning
- When you learn something new about the network, update
TOOLS.mdand store it in MemPalace - When you make a mistake, document it so future sessions don't repeat it
- When a skill procedure doesn't match reality, note the discrepancy here
Safety Rules
These are non-negotiable:
- Never guess device state. Run a show command first. Always.
- Never apply config without a baseline. Capture pre-change state in GAIT.
- Never run destructive commands —
write erase,erase,reload,delete,formatare refused. - Never skip change control. Production requires an approved ServiceNow CR. The explicitly opted-in Terminal Intent Local/Lab workflow described below uses a scoped local change record instead.
- Never auto-quarantine an endpoint. ISE quarantine requires explicit human confirmation.
- NetBox is read-write. You have full API access to create and update devices, IPs, interfaces, VLANs, and cables in NetBox.
- Always verify after changes. If verification fails, do not close the CR.
- Always commit to GAIT. Every session ends with
gait_log. - Don't exfiltrate data. Private network configs, credentials, and topology stay local.
- Ask before sending external communications — emails, Slack messages to channels outside #netclaw-*, ServiceNow tickets.
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.
- today Changed · +75 lines · +1,087 tokens per session 81f7a7b15258
- yesterday Changed · +184 lines · +2,647 tokens per session 79d3d2dbabbd
- 2d ago Changed · +161 lines · +2,571 tokens per session 6d2b66b69ad1
- 3d ago Changed · +42 lines · +806 tokens per session a76b337eda32
- 4d ago Changed · +4 lines · +277 tokens per session 707f7805c74e
- 6d ago Changed · +4 lines · +199 tokens per session 985be4d1eabb
- 7d ago Changed · +8 lines · +255 tokens per session c4660fc19403
- 11d ago Changed · +4 lines · +227 tokens per session 2275293713e1
- 13d ago Changed · +3 lines · +458 tokens per session db5bf153b5df
- 21d ago First seen · 168 lines · 2,664 tokens per session scan A 825c9daf94a3
netclaw AGENTS.md is an instructions file published in the GitHub repository automateyournetwork/netclaw (715 stars, last pushed yesterday), licensed Apache-2.0. It adds 11,191 tokens to every session, about $0.0448 per session on Opus 5.5. 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.
netclaw AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| netclaw AGENTS.mdautomateyournetwork/netclaw | Instructions file | 715 | yesterday | Apache-2.0 | A | 11,191 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |