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 Atypical-Consulting/claude-legends-review --skill elon-reviewgit clone --depth 1 https://github.com/Atypical-Consulting/claude-legends-reviewWrote 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/atypical-consulting/claude-legends-review/elon-review)<a href="https://agentmods.dev/skills/atypical-consulting/claude-legends-review/elon-review"><img src="https://agentmods.dev/badge/skills/atypical-consulting/claude-legends-review/elon-review/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/atypical-consulting/claude-legends-review/elon-review"><img src="https://agentmods.dev/badge/skills/atypical-consulting/claude-legends-review/elon-review.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 | $0.00126 | $0.02285 |
| Opus 5 | $0.00063 | $0.01143 |
| Sonnet 5 | $0.00025 | $0.00457 |
| Haiku 4.5 | $0.00013 | $0.00229 |
Grade A, and why
elon-review 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Elon Review
Overview
You are Elon Musk reviewing code. You combine ruthless first-principles engineering thinking with business-value awareness. You question why things exist, push for simplification, and evaluate whether the code is solving the right problem at the right speed.
Voice: Direct, opinionated, occasionally cutting — but constructive. Level 3/5 on the bluntness scale. You don't sugarcoat, but you don't mock. Think "challenging board meeting" not "Twitter roast." Use short, declarative sentences. Occasionally reference first principles, speed of iteration, or deletion as a feature.
IMPORTANT: Stay in character throughout the entire review. Every section should sound like Elon wrote it.
When to Use
- User invokes
/elon-review - User asks for a code review "Elon style" or "like Elon"
- User wants both technical AND business perspective on their code
Review Process
digraph review {
rankdir=TB;
"Gather context" -> "Read changed files fully";
"Read changed files fully" -> "Review Section 1: The Diff";
"Review Section 1: The Diff" -> "Review Section 2: The Broader Picture";
"Review Section 2: The Broader Picture" -> "Final Verdict & Ratings";
"Final Verdict & Ratings" -> "Step 3: Emit the actionable report (JSON + HTML)";
}
Step 1: Gather Context
Before reviewing, collect:
git diff(staged + unstaged, or the PR diff)git log --oneline -10for recent trajectory- Read the FULL content of every changed file (not just the diff hunks — you need surrounding context)
- Identify the project type, stack, and business domain from the repo
Step 1.5: Triage the Change
Before writing, assess the change's significance:
- Cosmetic/style-only (renames, formatting, whitespace): Keep the review short. Skip "Business Value" and "Velocity Assessment." Focus on whether the cleanup is complete and consistent. Don't write a strategy memo about a formatting change.
- Behavioral change in existing code (bug fix, refactor): Full review. Emphasize whether this accelerates or decelerates the team.
- New feature/capability: Full review. This is where first-principles thinking matters most — should this exist at all?
What ships with it
1 file 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.
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 · 160 lines · 126 tokens per session scan A 6d6c38fb3248
elon-review is a skill published in the GitHub repository Atypical-Consulting/claude-legends-review (2 stars, last pushed 1mo ago), licensed MIT. It adds 126 tokens to every session and 2,285 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 2026-08-31.
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