Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add automateyournetwork/netclaw --skill fwrule-analyzergit 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/skills/automateyournetwork/netclaw/fwrule-analyzer)<a href="https://agentmods.dev/skills/automateyournetwork/netclaw/fwrule-analyzer"><img src="https://agentmods.dev/badge/skills/automateyournetwork/netclaw/fwrule-analyzer/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/skills/automateyournetwork/netclaw/fwrule-analyzer"><img src="https://agentmods.dev/badge/skills/automateyournetwork/netclaw/fwrule-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 44 YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
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 | $0.00090 | $0.01823 |
| Opus 5 | $0.00045 | $0.00911 |
| Sonnet 5 | $0.00018 | $0.00365 |
| Haiku 4.5 | $0.00009 | $0.00182 |
Grade A, and why
fwrule-analyzer 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.
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.
Firewall Rule Analyzer
MCP Server
- Repository: AutomateIP/fwrule-mcp
- Transport: stdio (Python via
uv run fwrule-mcp) - Install:
git clone+uv sync(orpip install -e .) - Requires: No environment variables — standalone analysis engine
- Dependencies:
fastmcp>=2.0,pydantic>=2.0, Python 3.11+
Available Tools (3)
| Tool | What It Does |
|---|---|
analyze_firewall_rule_overlap |
Compare a candidate rule against an existing ruleset using 6-dimensional set intersection (zones, addresses, ports, protocols, actions, applications). Detects overlaps, shadowing, conflicts, and duplicates. Supports two input modes: vendor-native config via built-in parsers, or pre-normalized JSON. |
parse_policy |
Convert vendor-native firewall configurations into a standardized JSON schema. Enables inspection of parser output — rule counts, object resolution, address expansion — before running overlap analysis. |
list_supported_vendors |
Enumerate all supported firewall vendors, their aliases, configuration formats, and explain how to use normalized JSON input to bypass vendor-specific parsers. |
Supported Vendors (10)
| Vendor | Config Format | Versions | Identifiers |
|---|---|---|---|
| Palo Alto PAN-OS | XML export | 9.x–11.x | panos, paloalto, panorama |
| Cisco ASA | show running-config | 9.x+ | asa, cisco-asa |
| Cisco FTD | FMC JSON | 6.x–7.x | ftd, firepower, fmc |
| Cisco IOS/IOS-XE | show running-config | 12.x–17.x | ios, iosxe, cisco-ios |
| Cisco IOS-XR | show running-config | 6.x+ | iosxr, ios-xr, xr |
| Check Point | JSON rulebase | R80.x–R82.x | checkpoint, cp, check-point |
| Juniper SRX | display set | 19.x+ | juniper, srx |
| Juniper Junos | display set | 18.x+ | junos, mx, ptx, qfx |
| Nokia SR OS | MD-CLI format | 20.x+ | sros, nokia, sr-os |
| Fortinet FortiOS | Full backup config | 5.x–7.x | fortios, fortigate, fortinet, forti, fgt, fmg |
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.
- 9d ago First seen · 120 lines · 90 tokens per session scan A 61db7901b65b
fwrule-analyzer is a skill published in the GitHub repository automateyournetwork/netclaw (657 stars, last pushed 6d ago), licensed Apache-2.0. It adds 90 tokens to every session and 1,823 once invoked, about $0.0005 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 2026-09-03.
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