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 The-Artificer-of-Ciphers-LLC/skills-from-the-artificer --skill linuss-lawgit clone --depth 1 https://github.com/The-Artificer-of-Ciphers-LLC/skills-from-the-artificerWrote 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/the-artificer-of-ciphers-llc/skills-from-the-artificer/linuss-law)<a href="https://agentmods.dev/skills/the-artificer-of-ciphers-llc/skills-from-the-artificer/linuss-law"><img src="https://agentmods.dev/badge/skills/the-artificer-of-ciphers-llc/skills-from-the-artificer/linuss-law/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/the-artificer-of-ciphers-llc/skills-from-the-artificer/linuss-law"><img src="https://agentmods.dev/badge/skills/the-artificer-of-ciphers-llc/skills-from-the-artificer/linuss-law.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 | $0.00099 | $0.00792 |
| Opus 5 | $0.00049 | $0.00396 |
| Sonnet 5 | $0.00020 | $0.00158 |
| Haiku 4.5 | $0.00010 | $0.00079 |
Grade A, and why
linuss-law 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Linus's Law
"Given enough eyeballs, all bugs are shallow." — Attributed to Linus Torvalds; popularized by Eric Raymond in The Cathedral and the Bazaar, 1999
The core idea
When enough people examine a codebase, bugs that might seem deeply hidden to any individual reviewer will be found. What's opaque to one person is obvious to another. Different reviewers bring different mental models, experiences, and areas of focus.
This is the argument for both code review and open source development as quality mechanisms.
Why more eyeballs help
Cognitive diversity. Different reviewers think differently. One person might miss an off-by-one error; another will spot it immediately. One reviewer notices the security implication that the author never considered.
Assumption blindness. Authors are blind to their own assumptions. You can't see what you took for granted. A reviewer who doesn't share those assumptions sees the gap.
Familiarity blindness. After staring at code, you read what you meant to write, not what you wrote. Fresh eyes catch typos in variable names, wrong constants, and logic inversions that authors routinely miss.
Specialization. A security engineer reviewing code finds different bugs than a performance engineer or a domain expert. Broader review coverage is richer review.
Practical implications for teams
Make code review a non-negotiable practice. The research on code review is clear: it is one of the highest-ROI quality practices in software engineering. Even one additional reviewer catches a significant fraction of defects before they reach production.
Vary your reviewers. Don't always have the same person review the same person's code. Cross-domain reviews — someone less familiar with the code — catch different bugs than deep-expert reviews.
Make it easy to review. Small PRs, clear descriptions, linked context. Long PRs get shallow reviews. The review process should reduce friction for reviewers, not just for authors.
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.
- 12d ago First seen · 60 lines · 99 tokens per session scan A 9231d7b182b2
linuss-law is a skill published in the GitHub repository The-Artificer-of-Ciphers-LLC/skills-from-the-artificer (4 stars, last pushed 10d ago), licensed MIT. It adds 99 tokens to every session and 792 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
best-practices
Apply modern web development best practices for security, compatibility, and code quality. Use when asked to "apply best practices", "security audit", "modernize code", "code quality review", or "check for vulnerabilities".
resolve-pr-comments
Evaluate, fix, answer, and reply to GitHub pull request review comments and conversation comments. Handles both change requests (fix or skip) and reviewer questions (explain using reasoning recalled from past Claude Code transcripts). Use when the user asks to "resolve PR comments", "fix review comments", "address PR…
review-code
Review code for bugs, security vulnerabilities, API misuse, consistency issues, simplicity problems, or test coverage gaps by running internal reviews and a peer review in parallel and returning combined findings. Single-concern with a type argument, or full review with no argument. Use when the user asks to "review…
assess-technical-debt
Assess project-wide structural technical debt: complexity hotspots, deprecated API usage, duplication clusters, and architecture rot. Ranks findings by impact and refactor effort into a report at .turbo/technical-debt.md. Use when the user asks to "assess technical debt", "find technical debt", "review technical…
map-codebase
Deep architecture report that fans out parallel inspections across different aspects of the codebase (structure, tech stack, APIs, patterns, data flow, dependencies, testing) and synthesizes findings into a comprehensive document at .turbo/codebase-map.md and .turbo/codebase-map.html. Use when the user asks to "map…
peer-review
Run an independent peer review via Codex. Use when the user asks to "peer review", "peer review my code", "peer review my plan", "get a second opinion", or "independent review".