Borrowing it
Nothing to install: this file belongs to SCStelz/security-investigator. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SCStelz/security-investigator/main/.github/skills/detection-authoring/SKILL.mdgit clone --depth 1 https://github.com/SCStelz/security-investigatorWrote 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/scstelz/security-investigator/detection-authoring)<a href="https://agentmods.dev/skills/scstelz/security-investigator/detection-authoring"><img src="https://agentmods.dev/badge/skills/scstelz/security-investigator/detection-authoring/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/scstelz/security-investigator/detection-authoring"><img src="https://agentmods.dev/badge/skills/scstelz/security-investigator/detection-authoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 Tool Misuse · line 192 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- high System Prompt Leakage · line 640 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 | $0.00085 | $0.16901 |
| Opus 5 | $0.00043 | $0.08450 |
| Sonnet 5 | $0.00017 | $0.03380 |
| Haiku 4.5 | $0.00009 | $0.01690 |
Grade A, and why
detection-authoring 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 11d 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 — 1,102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Custom Detection Authoring — Instructions
Purpose
This skill deploys custom detection rules to Microsoft Defender XDR via the Microsoft Graph API (/beta/security/rules/detectionRules). It handles:
- Query adaptation — Converting Sentinel KQL queries into custom detection format
- Single-rule deployment — Creating one rule via Graph API
- Batch deployment — Deploying multiple rules from a JSON manifest
- Lifecycle management — Listing, updating, enabling/disabling, and deleting rules
- Validation — Dry-run queries in Advanced Hunting before deployment
Entity Type: Custom detection rules (Defender XDR)
Writing new detection queries from scratch? This skill focuses on deploying and managing detection rules — not query creation. If you need to write detection KQL from scratch (schema validation, community examples, performance optimization), use the kql-query-authoring skill first with CD intent markers (say "create custom detection queries for [scenario]"). It will produce Sentinel-format queries with
cd-metadatablocks ready for this skill to adapt and deploy.
📑 TABLE OF CONTENTS
- Prerequisites — Auth, scopes, PowerShell modules
- Critical Rules — Mandatory constraints (includes query adaptation checklist)
- Naming Convention — Standardized
displayNameformat (no prefixes, no MITRE IDs, colon separators) - API Reference — Graph API schema and field values
- Frequency & Lookback — Schedule periods, lookback windows, NRT constraints
- Deployment Workflow — Step-by-step process
- Batch Deployment — Manifest-driven multi-rule deployment
- Lifecycle Management — CRUD operations
- Existing Rule Discovery — Search Analytic Rules & Custom Detections by table, EventID, or keyword
- Known Pitfalls — Lessons learned (19 pitfalls documented)
- CD Metadata Contract — Schema for query file ↔ detection skill coordination
What ships with it
2 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.
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.
- 11d ago First seen · 1,102 lines · 85 tokens per session scan A 7baed46042a9
detection-authoring is a skill published in the GitHub repository SCStelz/security-investigator (245 stars, last pushed 3d ago), licensed MIT. It adds 85 tokens to every session and 16,901 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…