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/data-security-analysis/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/data-security-analysis)<a href="https://agentmods.dev/skills/scstelz/security-investigator/data-security-analysis"><img src="https://agentmods.dev/badge/skills/scstelz/security-investigator/data-security-analysis.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 System Prompt Leakage · line 1038 Skill contains patterns that could indirectly extract system prompts through rephrasing, translation, summarization, or side-channel techniques.Fix: Guard against indirect extraction by refusing to summarize, translate, or rephrase system instructions. Add explicit anti-extraction clauses.
- medium Agent Snooping · line 1432 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00179 | $0.21445 |
| Opus 5 | $0.00089 | $0.10722 |
| Sonnet 5 | $0.00036 | $0.04289 |
| Haiku 4.5 | $0.00018 | $0.02144 |
Grade A, and why
data-security-analysis 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 8d 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 — 1,437 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Security Events Analysis — Instructions
Purpose
This skill analyzes DataSecurityEvents (Microsoft Purview Insider Risk Management / DLP telemetry) to answer questions about who accessed documents containing sensitive information types (SITs) and/or sensitivity labels — including EDM (Exact Data Match), built-in SITs (credit cards, SSNs, etc.), trainable classifiers, and Microsoft Purview sensitivity labels (Confidential, Highly Confidential, custom labels, etc.).
Primary Table: DataSecurityEvents (Defender XDR Advanced Hunting)
| Use Case | Example Question |
|---|---|
| SIT access audit | "Who accessed files with credit card numbers in the last 30 days?" |
| EDM monitoring | "Show me all access to documents matching our EDM SIT" |
| DLP event analysis | "What DLP policy matches occurred this week?" |
| Insider risk triage | "Which users have the most sensitive data interactions?" |
| SIT landscape overview | "What sensitive information types exist in our environment?" |
| Sensitivity label audit | "Who accessed Highly Confidential labeled documents?" |
| Label change tracking | "Show me all label downgrades in the last 30 days" |
| Copilot label exposure | "What labeled documents did Copilot access in risky interactions?" |
📑 TABLE OF CONTENTS
- Critical Workflow Rules - Start here!
- SIT GUID Mapping Strategy - How SIT GUIDs are resolved to names
- Label GUID Mapping Strategy - How sensitivity label GUIDs are resolved to names
- Output Modes - Inline chat vs. Markdown file
- Quick Start - 8-step execution pattern
- Execution Workflow - 6-phase analysis process
- Sample KQL Queries - Validated query patterns (Queries 1-16d)
- Report Template - Rendering rules (15 rules) + output format specification
- Known Pitfalls - Table quirks and edge cases (27 entries)
- Error Handling - Troubleshooting guide
- SVG Dashboard Generation - Visual dashboard from report data
What ships with it
1 file 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.
- 8d ago First seen · 1,437 lines · 179 tokens per session scan A a8cce9c2a058
data-security-analysis is a skill published in the GitHub repository SCStelz/security-investigator (244 stars, last pushed 2d ago), licensed MIT. It adds 179 tokens to every session and 21,445 once invoked, about $0.0009 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…
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…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…