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 vinayaklatthe/microsoft-security-skills --skill sentinel-detection-engineeringgit clone --depth 1 https://github.com/vinayaklatthe/microsoft-security-skillsWrote 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/vinayaklatthe/microsoft-security-skills/sentinel-detection-engineering)<a href="https://agentmods.dev/skills/vinayaklatthe/microsoft-security-skills/sentinel-detection-engineering"><img src="https://agentmods.dev/badge/skills/vinayaklatthe/microsoft-security-skills/sentinel-detection-engineering/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/vinayaklatthe/microsoft-security-skills/sentinel-detection-engineering"><img src="https://agentmods.dev/badge/skills/vinayaklatthe/microsoft-security-skills/sentinel-detection-engineering.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 | $0.00239 | $0.02266 |
| Opus 5 | $0.00120 | $0.01133 |
| Sonnet 5 | $0.00048 | $0.00453 |
| Haiku 4.5 | $0.00024 | $0.00227 |
Grade A, and why
sentinel-detection-engineering 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sentinel Detection Engineering
Sentinel detection engineering is the discipline of building high-fidelity, well-tuned, maintainable detections and response automation. This skill covers the lifecycle — content sourcing, authoring, validating, automating, and versioning detections — not the broader SIEM architecture.
When to use
Authoring or maturing analytics rules, hunting queries, automation rules, and playbooks in Microsoft Sentinel. Use for KQL detection patterns, MITRE alignment, content-hub vs custom choices, and detection-as-code rollout.
Do not use this skill for Sentinel onboarding/architecture (sentinel), Defender XDR
custom detections in isolation (defender-xdr), or generic KQL learning unrelated to
detection.
Sources of content (use in this order)
-
Content Hub solutions — Microsoft- and partner-published, versioned bundles of data connectors, analytics rules, hunting queries, workbooks, playbooks. Always start here. Install the solution; enable rules in Active.
-
Microsoft Sentinel GitHub — community-contributed queries that haven't (yet) made it into a solution. Vet, then promote into your repo.
-
Custom detections — domain-specific, authored against your own data sources or specific business logic.
Rule of thumb: If a Microsoft solution covers 80% of the use case, install the solution and override the 20% in your repo — don't fork from scratch.
Choose the analytics rule type
| Rule type | When to use | Latency |
|---|---|---|
| Scheduled | Most cases; KQL window-based | 5 min – 24 h |
| Near-real-time (NRT) | High-priority, single-event detections (e.g., privileged role assignment) | <1 min |
| Microsoft Security (legacy) | Forward Defender alerts as Sentinel incidents | Immediate |
| Fusion | Multi-stage attack correlation (built-in ML) | Variable |
| Anomalies | Behavior baselines (built-in ML) | Hourly |
| Threat Intelligence | TI-indicator → log match | Schedule |
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 · 163 lines · 239 tokens per session scan A 031d1af4b1cb
sentinel-detection-engineering is a skill published in the GitHub repository vinayaklatthe/microsoft-security-skills (173 stars, last pushed 2mo ago), licensed MIT. It adds 239 tokens to every session and 2,266 once invoked, about $0.0012 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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