Borrowing it
Nothing to install: this file belongs to wezendy/elon-musk-algorithm-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/wezendy/elon-musk-algorithm-skills/main/GEMINI.mdgit clone --depth 1 https://github.com/wezendy/elon-musk-algorithm-skillsWrote 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/instructions/wezendy/elon-musk-algorithm-skills/gemini-md)<a href="https://agentmods.dev/instructions/wezendy/elon-musk-algorithm-skills/gemini-md"><img src="https://agentmods.dev/badge/instructions/wezendy/elon-musk-algorithm-skills/gemini-md/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/instructions/wezendy/elon-musk-algorithm-skills/gemini-md"><img src="https://agentmods.dev/badge/instructions/wezendy/elon-musk-algorithm-skills/gemini-md.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 | $0.01077 | $0.01077 |
| Opus 5 | $0.00539 | $0.00539 |
| Sonnet 5 | $0.00215 | $0.00215 |
| Haiku 4.5 | $0.00108 | $0.00108 |
Grade A, and why
elon-musk-algorithm-skills GEMINI.md 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 9d 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.
This is a copy
94% identical to elon-musk-algorithm-skills AGENTS.md — 4 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Engineering decision framework derived from Elon Musk's 5-step algorithm, as articulated during the 2021 Starbase tour with Tim Dodd and curated in The Book of Elon by Eric Jorgenson (Simon & Schuster, 2026). This file is the canonical source of truth for any AI coding agent operating in this repository (Claude Code, Codex, Cursor, Copilot, Gemini CLI, Devin, Aider, Amp, and others).
Apply the steps in strict order. Optimizing or automating something that should not exist is the most common engineering failure.
Scope: Primarily for reviewing and cleaning up existing systems (brownfield work). For greenfield application building, apply with translation (see overview skill). For function-level coding behavior (variable naming, error handling style, refactoring patterns), pair with andrej-karpathy-skills. The two frameworks operate at different granularities and do not conflict.
Tradeoff: Biases toward deletion over preservation, and toward order over speed. For trivial tasks, use judgment.
The framework
This guideline is decomposed into six skills under skills/. Skill files follow the SKILL.md open standard and are portable across agents that support it. Load the overview first, then follow the wiki links through the steps in order. Each step skill enforces a Gate that verifies prior steps are complete before proceeding.
- [[musk-algorithm]] - Overview and entry point
- [[musk-step-1-question-requirements]] - Every requirement needs a named human. Then challenge it.
- [[musk-step-2-delete-parts]] - Cut first. The 10% add-back rule calibrates the cut.
- [[musk-step-3-simplify-optimize]] - Only after 1 and 2. The most common smart-engineer failure.
- [[musk-step-4-accelerate-cycle-time]] - Only after 3. Never speed up a process that should be deleted.
- [[musk-step-5-automate]] - Last. The Fremont rule.
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.
- 9d ago First seen · 70 lines · 1,077 tokens per session scan A 3b170d29d04e
elon-musk-algorithm-skills GEMINI.md is an instructions file published in the GitHub repository wezendy/elon-musk-algorithm-skills (9 stars, last pushed 3mo ago), licensed MIT. It adds 1,077 tokens to every session, about $0.0054 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to elon-musk-algorithm-skills AGENTS.md, differing in 4 lines, and is treated as a copy.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.