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 olafkfreund/nixos_config --skill 1passwordgit clone --depth 1 https://github.com/olafkfreund/nixos_configWrote 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/olafkfreund/nixos_config/1password)<a href="https://agentmods.dev/skills/olafkfreund/nixos_config/1password"><img src="https://agentmods.dev/badge/skills/olafkfreund/nixos_config/1password/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/olafkfreund/nixos_config/1password"><img src="https://agentmods.dev/badge/skills/olafkfreund/nixos_config/1password.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 | $0.00121 | $0.01727 |
| Opus 5 | $0.00060 | $0.00864 |
| Sonnet 5 | $0.00024 | $0.00345 |
| Haiku 4.5 | $0.00012 | $0.00173 |
Grade A, and why
1password 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 6d 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.
The source is not reproduced here
Licensed GPL-3.0
The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- 6d ago First seen · 194 lines · 121 tokens per session scan A 6a5135398ba0
1password is a skill published in the GitHub repository olafkfreund/nixos_config (23 stars, last pushed today), licensed GPL-3.0. It adds 121 tokens to every session and 1,727 once invoked, about $0.0006 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 2026-09-03.
Other skills, from other repositories
1password
Manage secrets via 1Password CLI (op). Read, create, and inject secrets. Provides whitelisted access for other skills (ask-curl, GitHub, etc.) via op:// secret references and 1Password Environments.
ship-safe
Run a full security audit on this project — 16 agents scan for secrets, injections, auth bypass, SSRF, supply chain, Supabase RLS, MCP security, agentic AI, RAG poisoning, PII compliance, and more. Use when the user wants a security audit, vulnerability scan, or asks if their code is safe to ship.
ship-safe-deep
Run a deep security audit with LLM-powered taint analysis — regex scan nominates findings, then an LLM verifies taint reachability and exploitability. Use when the user wants thorough, high-confidence results with fewer false positives.
ship-safe-fix
Auto-fix security issues — remediate hardcoded secrets and common vulnerabilities (TLS bypass, debug mode, XSS, shell injection, Docker :latest). Use when the user wants to automatically fix security findings.
ship-safe-red-team
Run a multi-agent red team scan — 29 specialized security agents scan for 80+ attack classes including injection, auth bypass, SSRF, supply chain, Supabase RLS, MCP security, agentic AI, RAG poisoning, PII compliance, and more. Use when the user wants a deep security analysis beyond just secrets.
ship-safe-scan
Quick scan for leaked secrets — API keys, passwords, tokens, database URLs. Use when the user wants to check for hardcoded secrets or exposed credentials.