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 building-super-timelines-with-plasogit 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/building-super-timelines-with-plaso)<a href="https://agentmods.dev/skills/andycungkrinx91/konoha/building-super-timelines-with-plaso"><img src="https://agentmods.dev/badge/skills/andycungkrinx91/konoha/building-super-timelines-with-plaso/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/building-super-timelines-with-plaso"><img src="https://agentmods.dev/badge/skills/andycungkrinx91/konoha/building-super-timelines-with-plaso.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 | $0.00029 | $0.01908 |
| Opus 5.5 | $0.00012 | $0.00763 |
| Sonnet 5.5 | $0.00006 | $0.00382 |
| Haiku 4.5 | $0.00003 | $0.00191 |
Grade B, and why
building-super-timelines-with-plaso scanned grade B with 1 finding 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo add-apt-repository ppa:gift/stable This is a copy
100% identical to building-super-timelines-with-plaso — 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Building Super Timelines with Plaso
Authorized Use Only: Build timelines only from evidence you are authorized to analyze. Work from forensic images/copies and preserve chain of custody.
Overview
Plaso (Plaso Langar Að Safna Öllu) is the open-source engine behind log2timeline, the standard for building forensic super timelines — a single chronological, normalized view fusing hundreds of artifact types (file-system MACB times, registry, EVTX, browser history, prefetch, LNK, $UsnJrnl, syslog, and more) into one timeline. Plaso has three core CLI tools:
- log2timeline.py — extracts events from a source (disk image, mount point, directory, or device) into a
.plasostorage file using its large parser/plugin set. - pinfo.py — reports on the contents and processing metadata of a
.plasofile. - psort.py — post-processes, filters, deduplicates, time-zones, and exports the storage file to an output format (CSV, JSON-line, Elasticsearch, Timesketch, etc.).
- psteal.py — convenience wrapper that runs extraction + export in one step.
The resulting timeline is enormous, so analysts triage it in Timesketch — a collaborative, web-based timeline analysis platform that ingests .plaso files (or CSV/JSONL) and supports filtering, tagging, starring, saved searches, and automated analyzers.
When to Use
- Reconstructing the full sequence of events on a compromised host during incident response.
- Correlating activity across many artifact sources on a single normalized timeline.
- Investigating anti-forensic behavior such as timestomping or log clearing (which stands out against MACB and journal evidence).
- Feeding a curated timeline into Timesketch for team triage.
Prerequisites
- Install Plaso (Docker is the supported, reproducible method):
Alternatively on Ubuntu via the GIFT PPA:docker pull log2timeline/plaso # Run a tool, mounting your evidence/output directory docker run -v /cases:/data log2timeline/plaso log2timeline.py --versionsudo add-apt-repository ppa:gift/stable sudo apt-get update && sudo apt-get install -y plaso-tools - A Timesketch instance (docker-compose deployment from https://github.com/google/timesketch) for triage.
- A forensic image (E01/raw) or mounted file system.
What ships with it
3 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 · 166 lines · 29 tokens per session scan B 3e60d8e1501f
building-super-timelines-with-plaso is a skill published in the GitHub repository andycungkrinx91/konoha (12 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 1,908 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). It is 100% identical to building-super-timelines-with-plaso, differing in 0 lines, and is treated as a copy.
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