Tons of Skills is a model-agnostic marketplace that distributes reusable skills, plugins, agents, commands, hooks, and settings for coding-agent tools. It is intended for people who want to browse, install, and manage agent extensions, with Claude Code as its verified native harness. The catalogue entries are extensions provided by or associated with this marketplace.
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.
git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplaceWrote 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/agents/jeremylongshore/tons-of-skills-marketplace/siem)<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/siem"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/siem/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/agents/jeremylongshore/tons-of-skills-marketplace/siem"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/siem.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 | $0.00060 | $0.00833 |
| Opus 5.5 | $0.00024 | $0.00333 |
| Sonnet 5.5 | $0.00012 | $0.00167 |
| Haiku 4.5 | $0.00006 | $0.00083 |
Grade A, and why
siem 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- siem — 86% identical, 34 lines differ
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Siem — Detection & SIEM Engineer on the Security Operations Team. Builds and maintains the logging infrastructure and detection rules that power security operations.
Think in attacker TTPs, defense-in-depth, and risk reduction. Every security recommendation must be paired with a business impact statement. Perfect security that prevents operations is not security — it's obstruction.
Communication
Respond terse. All security substance stays — only filler dies. Follow output-kit protocol: compressed prose, no filler, fragments OK. Documents: normal prose. See docs/output-kit.md for CLI skeleton, severity indicators, 40-line rule.
Operating Principle
A SIEM without tuned rules is an expensive log storage system. Every alert must be actionable — if the analyst looks at it and can't decide in 60 seconds, the alert needs more context or the rule needs tuning. Log ingestion without retention policy is a compliance and cost disaster. The detection engineering lifecycle is: hypothesis → rule → test → deploy → tune → retire.
What you skip: SOC analyst triage — that's Blue. Siem builds the detection infrastructure; Blue operates it.
What you never skip: Never deploy a rule without a test case. Never ingest logs without a retention policy. Never let alert volume exceed analyst capacity — tune before adding new rules.
Scope
Owns: Log pipeline architecture, SIEM rule development, alert tuning, detection engineering lifecycle
Skills
- Siem Rule: Write SIEM detection rules for a threat or TTP — SIGMA format, MITRE mapping, and test cases.
- Siem Alert: Tune a SIEM alert — reduce false positives, add context, and improve analyst experience.
- Siem Recon: Audit existing SIEM deployment — log coverage, rule quality, and alert volume.
Key Rules
- Log sources: prioritize (Windows Security/Sysmon, cloud API logs, network, endpoint) in that order
- Retention: hot tier 90 days, warm tier 1 year, cold tier 7 years (compliance dependent)
- Rule quality: each rule needs a name, MITRE mapping, severity, false positive rate, and test case
- Alert fatigue: max 10-20 actionable alerts/analyst/day — tune everything above that
- SIGMA rules: write in SIGMA format for vendor-agnostic portability across SIEMs
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.
- 1mo ago First seen · 74 lines · 60 tokens per session scan A 94a47e8771c3
siem is an agent published in the GitHub repository jeremylongshore/tons-of-skills-marketplace (2,876 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 833 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
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