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stuart-russell

stuart-russell is a skill for Claude Code, Codex from K-Dense-AI/mimeographs. It costs 125 tokens per session (1,180 once invoked), scanned A, a copy of stuart-russell, MIT.

An AI safety and governance guide based on Stuart Russell’s work on human values, uncertainty about goals, autonomous weapons, and regulation.

In plain words
What is it for?
Use it to evaluate AI systems, value alignment, control problems, safety requirements, autonomous weapons, or AI regulation.
Why use it?
It helps identify the risks of building AI that follows a fixed objective without reliably understanding what people want.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 123repo +2 24d ago A scan 125 tokens copy · 100% MIT

Good fit Use it to evaluate AI systems, value alignment, control problems, safety requirements, autonomous weapons, or AI regulation.

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Install with agentmods
npx agentmods add skills/k-dense-ai/mimeographs/stuart-russell
View source ↗ K-Dense-AI/mimeographs k-dense.ai
Install

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.

Any agent
npx skills add K-Dense-AI/mimeographs --skill stuart-russell
Clone the repo
git clone --depth 1 https://github.com/K-Dense-AI/mimeographs

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for stuart-russell

README.md
[![agentmods](https://agentmods.dev/badge/skills/k-dense-ai/mimeographs/stuart-russell/github.svg)](https://agentmods.dev/skills/k-dense-ai/mimeographs/stuart-russell)
Your own site
<a href="https://agentmods.dev/skills/k-dense-ai/mimeographs/stuart-russell"><img src="https://agentmods.dev/badge/skills/k-dense-ai/mimeographs/stuart-russell/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.

agentmods 80×15 button for stuart-russell

Your own site · 80×15
<a href="https://agentmods.dev/skills/k-dense-ai/mimeographs/stuart-russell"><img src="https://agentmods.dev/badge/skills/k-dense-ai/mimeographs/stuart-russell.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 125 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,180 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00125 $0.01180
Opus 5 $0.00063 $0.00590
Sonnet 5 $0.00025 $0.00236
Haiku 4.5 $0.00013 $0.00118

Measured 8d ago against content hash 01231e5c2b5e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

stuart-russell 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 8d 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.

Origin

This is a copy

100% identical to stuart-russell — 2 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.

mimeographs/stuart-russell/SKILL.md · 65 lines

How it starts

The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Thinking like Stuart Russell

Stuart Russell is a foundational figure in artificial intelligence whose work fundamentally challenges the "Standard Model" of AI. His signature cognitive move is shifting the focus from creating systems that perfectly optimize a fixed objective to creating systems that are provably beneficial because they are explicitly uncertain about what humans want.

Reach for this skill whenever you're analyzing AI safety, the control problem, value alignment, autonomous weapons, or the regulatory frameworks needed to govern high-stakes technologies.

Core principles

  • Uncertainty in Objectives: AI systems must be designed with explicit uncertainty about their objectives; treating an objective as absolute truth leads to relentless, catastrophic optimization.
  • Safety by Design (Not Post-Hoc): Safety must be built into the core mathematical foundation of AI from the start, rather than patched onto unprincipled "black boxes" after the fact.
  • Burden of Proof on Developers: The onus of proving safety must be on AI developers, enforced by strict regulatory red lines, just as it is in aviation or nuclear power.
  • Realization of Human Preferences: The sole purpose of an AI system should be the realization of human preferences, which it must learn dynamically by observing human behavior.

For detailed rationale and quotes, see references/principles.md.

How Stuart Russell reasons

Russell reasons by drawing parallels between AI and other high-stakes, mature engineering disciplines (like aviation and nuclear energy). He rejects the trial-and-error "bird breeding" approach of modern deep learning in favor of rigorous, mathematical guarantees. When evaluating an AI system, he first asks: What is its objective, and how certain is it of that objective? He dismisses post-hoc safety measures like RLHF as fundamentally flawed because they do not alter the underlying optimization drive.

He frequently relies on the King Midas Problem to illustrate the danger of fixed objectives, and The Gorilla Problem to frame the existential risk of creating entities smarter than ourselves. For more on these, see references/mental-models.md.

Read the full file on GitHub · 65 lines

Files

What ships with it

60 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.

Changes

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.

  1. 8d ago First seen · 65 lines · 125 tokens per session scan A 01231e5c2b5e

Subscribe to this mod's changes

stuart-russell is a skill published in the GitHub repository K-Dense-AI/mimeographs (123 stars, last pushed 24d ago), licensed MIT. It adds 125 tokens to every session and 1,180 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to stuart-russell, differing in 2 lines, and is treated as a copy.

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