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 dandye/ai-runbooks --skill respond-compromised-accountgit clone --depth 1 https://github.com/dandye/ai-runbooksWrote 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/dandye/ai-runbooks/respond-compromised-account)<a href="https://agentmods.dev/skills/dandye/ai-runbooks/respond-compromised-account"><img src="https://agentmods.dev/badge/skills/dandye/ai-runbooks/respond-compromised-account/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/dandye/ai-runbooks/respond-compromised-account"><img src="https://agentmods.dev/badge/skills/dandye/ai-runbooks/respond-compromised-account.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 277 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00047 | $0.01806 |
| Opus 5 | $0.00023 | $0.00903 |
| Sonnet 5 | $0.00009 | $0.00361 |
| Haiku 4.5 | $0.00005 | $0.00181 |
Grade A, and why
respond-compromised-account 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 12d 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 — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compromised User Account Response Skill
Structured workflow for responding to potentially compromised user accounts using the PICERL model.
Inputs
USER_ID- Username or email of the potentially compromised userCASE_ID- SOAR case ID for documentationALERT_GROUP_IDENTIFIERS- Alert group identifiers from SOAR- (Optional)
INITIAL_ALERT_DETAILS- Summary of triggering alert
Required Outputs
After completing each phase, you MUST report these outputs:
Identification Phase
| Output | Description |
|---|---|
AFFECTED_ACCOUNTS |
User accounts confirmed or suspected compromised |
SUSPICIOUS_ACTIVITY |
Summary of anomalous activity detected |
ACCESS_SCOPE |
Systems/data the account had access to |
COMPROMISE_LIKELIHOOD |
Assessment level: Low, Medium, High, Confirmed |
Containment Phase
| Output | Description |
|---|---|
DISABLED_ACCOUNTS |
Accounts that were disabled |
RESET_PASSWORDS |
Accounts with passwords reset |
REVOKED_SESSIONS |
Sessions terminated |
Eradication Phase
| Output | Description |
|---|---|
REMOVED_PERSISTENCE |
Persistence mechanisms removed (forwarding rules, OAuth apps, etc.) |
CLEANED_ENDPOINTS |
Associated endpoints verified clean |
Recovery Phase
| Output | Description |
|---|---|
RESTORED_ACCOUNTS |
Accounts re-enabled with new security controls |
USER_NOTIFICATIONS |
Users notified of incident and required actions |
PICERL Phases
Phase 2: Identification
Step 2.1: Get Context
secops-soar.get_case_full_details(case_id=CASE_ID)
Use /check-duplicates.
Step 2.2: Gather Initial Context
SIEM entity lookup:
secops-mcp.lookup_entity(entity_value=USER_ID)
(If IDP tools available):
- Account status
- Recent logins
- MFA configuration
- Password last changed
Step 2.3: Analyze User Activity
Search SIEM for last 96 hours:
secops-mcp.search_security_events(
text="All activity for USER_ID",
hours_back=96
)
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.
- 12d ago First seen · 300 lines · 47 tokens per session scan A dcef87855463
respond-compromised-account is a skill published in the GitHub repository dandye/ai-runbooks (126 stars, last pushed 28d ago), licensed Apache-2.0. It adds 47 tokens to every session and 1,806 once invoked, about $0.0002 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.
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