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 ancoleman/ai-design-components --skill siem-logginggit clone --depth 1 https://github.com/ancoleman/ai-design-componentsWrote 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/ancoleman/ai-design-components/siem-logging)<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/siem-logging"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/siem-logging/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/ancoleman/ai-design-components/siem-logging"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/siem-logging.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 | $0.00049 | $0.03344 |
| Opus 5.5 | $0.00020 | $0.01338 |
| Sonnet 5.5 | $0.00010 | $0.00669 |
| Haiku 4.5 | $0.00005 | $0.00334 |
Grade A, and why
siem-logging scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
process.args : ("Invoke-WebRequest", "iwr", "wget")] How it starts
The opening of the file, as written. The whole thing — 406 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SIEM Logging
Purpose
Configure comprehensive security logging infrastructure using SIEM platforms (Elastic SIEM, Microsoft Sentinel, Wazuh, Splunk) to detect threats, investigate incidents, and maintain compliance audit trails. This skill covers platform selection, log aggregation architecture, detection rule development (SIGMA format and platform-specific), alert tuning, and retention policies for regulatory compliance (GDPR, HIPAA, PCI DSS, SOC 2).
When to Use This Skill
Use this skill when:
- Implementing centralized security event monitoring across infrastructure
- Writing threat detection rules for authentication failures, privilege escalation, data exfiltration
- Designing log aggregation for multi-cloud environments (AWS, Azure, GCP, Kubernetes)
- Meeting compliance requirements for log retention and audit trails
- Tuning security alerts to reduce false positives and alert fatigue
- Calculating costs for high-volume security logging (TB/day scale)
- Integrating security logging with incident response workflows
SIEM Platform Selection
Quick Decision Framework
Choose SIEM platform based on:
Budget Considerations:
- Unlimited budget → Splunk Enterprise Security (enterprise features, proven scale)
- Moderate budget ($50k-$500k/year) → Microsoft Sentinel or Elastic SIEM (cloud-native, flexible)
- Tight budget (<$50k/year) → Wazuh (free, open-source XDR/SIEM)
Infrastructure Context:
- Heavy Azure investment → Microsoft Sentinel (native integration, built-in SOAR)
- Heavy AWS investment → AWS Security Lake + OpenSearch (AWS-native)
- Multi-cloud or on-premise → Elastic SIEM or Wazuh (platform-agnostic)
Data Volume:
- >1 TB/day → Splunk or Elastic Cloud (proven at scale)
- 100 GB - 1 TB/day → Microsoft Sentinel or Elastic SIEM
- <100 GB/day → Wazuh or Sentinel 50 GB tier
Team Expertise:
- Elasticsearch experience → Elastic SIEM (familiar tooling)
- Microsoft/Azure expertise → Microsoft Sentinel (Azure ecosystem)
- Generalists or limited resources → Wazuh (easiest learning curve)
What ships with it
17 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- examples/architectures/elk-stack-docker-compose.yml 7.1 KB
- examples/architectures/fluentd-kubernetes-daemonset.yaml 15 KB
- examples/architectures/wazuh-docker-compose.yml 2.5 KB
- examples/detection-rules/brute-force-detection.yaml 5.6 KB
- examples/detection-rules/privilege-escalation.yaml 11 KB
- examples/sigma-rules/brute-force-detection.yml 758 B
- examples/sigma-rules/data-exfiltration.yml 886 B
- examples/sigma-rules/lateral-movement.yml 849 B
- examples/sigma-rules/privilege-escalation.yml 817 B
- outputs.yaml 4.8 KB
- references/alert-tuning-strategies.md 1.9 KB
- references/cloud-native-logging.md 2.9 KB
- references/cost-optimization.md 1.5 KB
- references/detection-rules-guide.md 15 KB
- references/log-retention-policies.md 6.2 KB
- references/platform-comparison.md 16 KB
- scripts/cost-calculator.py 5.4 KB runs code
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.
- 1mo ago First seen · 406 lines · 49 tokens per session scan A 72f0a8e9daf6
siem-logging is a skill published in the GitHub repository ancoleman/ai-design-components (525 stars, last pushed 10mo ago), licensed MIT. It adds 49 tokens to every session and 3,344 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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