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 marysatasselshaped667/skills-collection-1 --skill analyzing-windows-shellbag-artifactsgit clone --depth 1 https://github.com/marysatasselshaped667/skills-collection-1Wrote 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/marysatasselshaped667/skills-collection-1/analyzing-windows-shellbag-artifacts)<a href="https://agentmods.dev/skills/marysatasselshaped667/skills-collection-1/analyzing-windows-shellbag-artifacts"><img src="https://agentmods.dev/badge/skills/marysatasselshaped667/skills-collection-1/analyzing-windows-shellbag-artifacts/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/marysatasselshaped667/skills-collection-1/analyzing-windows-shellbag-artifacts"><img src="https://agentmods.dev/badge/skills/marysatasselshaped667/skills-collection-1/analyzing-windows-shellbag-artifacts.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 | $0.00050 | $0.02257 |
| Opus 5 | $0.00025 | $0.01128 |
| Sonnet 5 | $0.00010 | $0.00451 |
| Haiku 4.5 | $0.00005 | $0.00226 |
Grade A, and why
analyzing-windows-shellbag-artifacts 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.
This is a copy
89% identical to analyzing-windows-shellbag-artifacts — 29 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyzing Windows Shellbag Artifacts
Overview
Shellbags are Windows registry artifacts that track how users interact with folders through Windows Explorer, storing view settings such as icon size, window position, sort order, and view mode. From a forensic perspective, Shellbags provide definitive evidence of folder access -- even folders that no longer exist on the system. When a user browses to a folder via Windows Explorer, the Open/Save dialog, or the Control Panel, a Shellbag entry is created or updated in the user's registry hive. These entries persist after folder deletion, drive disconnection, and even across user profile resets, making them invaluable for proving that a user navigated to specific directories on local drives, USB devices, network shares, or zip archives.
When to Use
- When investigating security incidents that require analyzing windows shellbag artifacts
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
Prerequisites
- Familiarity with digital forensics concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
Registry Locations
Windows 7/8/10/11
| Hive | Key Path | Stores |
|---|---|---|
| NTUSER.DAT | Software\Microsoft\Windows\Shell\BagMRU | Folder hierarchy tree |
| NTUSER.DAT | Software\Microsoft\Windows\Shell\Bags | View settings per folder |
| UsrClass.dat | Local Settings\Software\Microsoft\Windows\Shell\BagMRU | Desktop/Explorer shell |
| UsrClass.dat | Local Settings\Software\Microsoft\Windows\Shell\Bags | Additional view settings |
BagMRU Structure
The BagMRU key contains a hierarchical tree of numbered subkeys representing the directory structure. Each subkey value contains a Shell Item (SHITEMID) binary blob encoding the folder identity:
What ships with it
7 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.
- 8d ago First seen · 201 lines · 50 tokens per session scan A 4204c97ac819
analyzing-windows-shellbag-artifacts is a skill published in the GitHub repository marysatasselshaped667/skills-collection-1 (1 stars, last pushed yesterday), licensed MIT. It adds 50 tokens to every session and 2,257 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to analyzing-windows-shellbag-artifacts, differing in 29 lines, and is treated as a copy.
Other skills, from other repositories
analyzing-windows-shellbag-artifacts
Analyze Windows Shellbag registry artifacts to reconstruct folder browsing activity, detect access to removable media and network shares, and establish user interaction with directories even after deletion using SBECmd and ShellBags Explorer.
analyzing-windows-shellbag-artifacts
Analyze Windows Shellbag registry artifacts to reconstruct folder browsing activity, detect access to removable media and network shares, and establish user interaction with directories even after deletion using SBECmd and ShellBags Explorer.
analyzing-windows-shellbag-artifacts
Analyze Windows Shellbag registry artifacts to reconstruct folder browsing activity, detect access to removable media and network shares, and establish user interaction with directories even after deletion using SBECmd and ShellBags Explorer.
analyzing-windows-shellbag-artifacts
Analyze Windows Shellbag registry artifacts to reconstruct folder browsing activity, detect access to removable media and network shares, and establish user interaction with directories even after deletion using SBECmd and ShellBags Explorer.
analyzing-windows-shellbag-artifacts
Analyze Windows Shellbag (BagMRU) registry artifacts with SBECmd and Shellbags Explorer to reconstruct folder browsing activity and prove user interaction with directories, including removable media and network shares, even after the folders are deleted. Use when reconstructing a user's folder access history or…
analyzing-windows-shellbag-artifacts
Analyze Windows Shellbag registry artifacts to reconstruct folder browsing activity, detect access to removable media and network shares, and establish user interaction with directories even after deletion using SBECmd and ShellBags Explorer.