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 ise-incident-responsegit 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/ise-incident-response)<a href="https://agentmods.dev/skills/automateyournetwork/netclaw/ise-incident-response"><img src="https://agentmods.dev/badge/skills/automateyournetwork/netclaw/ise-incident-response/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/ise-incident-response"><img src="https://agentmods.dev/badge/skills/automateyournetwork/netclaw/ise-incident-response.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00074 | $0.02940 |
| Opus 5 | $0.00037 | $0.01470 |
| Sonnet 5 | $0.00015 | $0.00588 |
| Haiku 4.5 | $0.00007 | $0.00294 |
Grade A, and why
ise-incident-response 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 — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ISE Incident Response
Safety -- Non-Negotiable Rules
NEVER auto-quarantine an endpoint. Endpoint group changes require explicit human confirmation. The agent MUST present its findings, state its recommendation, and then STOP and WAIT for the human to type an affirmative response before proceeding with any ISE endpoint group modification.
NEVER skip the investigation steps. Even if the human says "just quarantine MAC XX:XX:XX:XX:XX:XX", the agent MUST first collect endpoint data, auth history, and posture state so the quarantine action has full context for the ServiceNow ticket and GAIT audit trail.
NEVER modify ISE authorization policies during incident response. This workflow changes endpoint group membership only. Policy changes require a separate Change Request via servicenow-change-workflow.
When to Use
- Suspected compromised endpoint (SOC alert, SIEM correlation)
- Unauthorized device detected on the network
- Endpoint exhibiting anomalous behavior (port scanning, lateral movement)
- Failed posture compliance requiring immediate isolation
- Rogue access point or hub detected on a switchport
How to Call the ISE MCP Tools
All ISE tools are called via mcp-call with the ISE MCP server command:
python3 $MCP_CALL "ISE_BASE=$ISE_BASE USERNAME=$ISE_USERNAME PASSWORD=$ISE_PASSWORD python3 -u $ISE_MCP_SCRIPT" TOOL_NAME '{"param":"value"}'
ServiceNow tools are called via:
python3 $MCP_CALL "$SERVICENOW_MCP_SCRIPT" TOOL_NAME '{"param":"value"}'
Incident Response Procedure
Phase 1: Endpoint Identification
Locate the suspect endpoint by MAC address, IP address, or username. Start with the endpoints list and active sessions.
Look up all endpoints:
python3 $MCP_CALL "ISE_BASE=$ISE_BASE USERNAME=$ISE_USERNAME PASSWORD=$ISE_PASSWORD python3 -u $ISE_MCP_SCRIPT" endpoints '{}'
Check active sessions for the suspect:
python3 $MCP_CALL "ISE_BASE=$ISE_BASE USERNAME=$ISE_USERNAME PASSWORD=$ISE_PASSWORD python3 -u $ISE_MCP_SCRIPT" active_sessions '{}'
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 · 266 lines · 74 tokens per session scan A 66ae625371c8
ise-incident-response is a skill published in the GitHub repository automateyournetwork/netclaw (657 stars, last pushed 6d ago), licensed Apache-2.0. It adds 74 tokens to every session and 2,940 once invoked, about $0.0004 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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