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 andycungkrinx91/konoha --skill analyzing-prefetch-files-for-execution-historygit clone --depth 1 https://github.com/andycungkrinx91/konohaWrote 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/andycungkrinx91/konoha/analyzing-prefetch-files-for-execution-history)<a href="https://agentmods.dev/skills/andycungkrinx91/konoha/analyzing-prefetch-files-for-execution-history"><img src="https://agentmods.dev/badge/skills/andycungkrinx91/konoha/analyzing-prefetch-files-for-execution-history/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/andycungkrinx91/konoha/analyzing-prefetch-files-for-execution-history"><img src="https://agentmods.dev/badge/skills/andycungkrinx91/konoha/analyzing-prefetch-files-for-execution-history.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 | $0.00034 | $0.03208 |
| Opus 5.5 | $0.00014 | $0.01283 |
| Sonnet 5.5 | $0.00007 | $0.00642 |
| Haiku 4.5 | $0.00003 | $0.00321 |
Grade A, and why
analyzing-prefetch-files-for-execution-history 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 today.
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
100% identical to analyzing-prefetch-files-for-execution-history — 0 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 — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyzing Prefetch Files for Execution History
When to Use
- When determining which programs were executed on a Windows system and when
- During malware investigations to confirm execution of suspicious binaries
- For establishing a timeline of application usage during an incident
- When correlating program execution with other forensic artifacts
- To identify anti-forensic tools or unauthorized software that was run
Prerequisites
- Access to Windows Prefetch directory (C:\Windows\Prefetch) from forensic image
- PECmd (Eric Zimmerman), WinPrefetchView, or python-prefetch parser
- Understanding of Prefetch file format (versions 17, 23, 26, 30)
- Windows system with Prefetch enabled (default on client OS, disabled on servers)
- Knowledge of Prefetch naming conventions (APPNAME-HASH.pf)
Workflow
Step 1: Extract Prefetch Files from Forensic Image
# Mount the forensic image
mount -o ro,loop,offset=$((2048*512)) /cases/case-2024-001/images/evidence.dd /mnt/evidence
# Copy all prefetch files
mkdir -p /cases/case-2024-001/prefetch/
cp /mnt/evidence/Windows/Prefetch/*.pf /cases/case-2024-001/prefetch/
# Count and list prefetch files
ls -la /cases/case-2024-001/prefetch/ | wc -l
ls -la /cases/case-2024-001/prefetch/ | head -30
# Hash all prefetch files for integrity
sha256sum /cases/case-2024-001/prefetch/*.pf > /cases/case-2024-001/prefetch/pf_hashes.txt
# Note: Prefetch filename format is EXECUTABLE_NAME-XXXXXXXX.pf
# The hash (XXXXXXXX) is based on the executable path
# Same executable from different paths creates different prefetch files
Step 2: Parse Prefetch Files with PECmd
# Using Eric Zimmerman's PECmd (Windows or via Mono/Wine on Linux)
# Download from https://ericzimmerman.github.io/
# Parse a single prefetch file
PECmd.exe -f "C:\cases\prefetch\POWERSHELL.EXE-A]B2C3D4.pf"
# Parse all prefetch files and output to CSV
PECmd.exe -d "C:\cases\prefetch\" --csv "C:\cases\analysis\" --csvf prefetch_results.csv
# Parse with JSON output
PECmd.exe -d "C:\cases\prefetch\" --json "C:\cases\analysis\" --jsonf prefetch_results.json
# Output includes for each file:
# - Executable name and path
# - Run count
# - Last run time (up to 8 timestamps in Windows 10)
# - Files and directories referenced during execution
# - Volume information (serial number, creation date)
# - Prefetch file creation time
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.
- today First seen · 329 lines · 34 tokens per session scan A 58849dbbb92c
analyzing-prefetch-files-for-execution-history is a skill published in the GitHub repository andycungkrinx91/konoha (12 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 3,208 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to analyzing-prefetch-files-for-execution-history, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
analyzing-prefetch-files-for-execution-history
Parse Windows Prefetch files to determine program execution history including run counts, timestamps, and referenced files for forensic investigation.
analyzing-prefetch-files-for-execution-history
Parse Windows Prefetch files to determine program execution history including run counts, timestamps, and referenced files for forensic investigation.
analyzing-prefetch-files-for-execution-history
A guide for reading Windows Prefetch files, which record information about programs that have run on a system. The records can include execution counts, times, and referenced files.
analyzing-prefetch-files-for-execution-history
Parse Windows Prefetch files to determine program execution history including run counts, timestamps, and referenced files for forensic investigation.
analyzing-prefetch-files-for-execution-history
Parse Windows Prefetch files to determine program execution history including run counts, timestamps, and referenced files for forensic investigation.
analyzing-prefetch-files-for-execution-history
Parse Windows Prefetch files (versions 17, 23, 26, 30) with tools like PECmd, WinPrefetchView, or python-prefetch to determine program execution history, including run counts, execution timestamps, and referenced files/DLLs. Use when building a timeline of program execution on a Windows system, confirming whether a…