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 wezendy/elon-musk-algorithm-skills --skill musk-step-5-automategit 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/skills/wezendy/elon-musk-algorithm-skills/musk-step-5-automate)<a href="https://agentmods.dev/skills/wezendy/elon-musk-algorithm-skills/musk-step-5-automate"><img src="https://agentmods.dev/badge/skills/wezendy/elon-musk-algorithm-skills/musk-step-5-automate/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/wezendy/elon-musk-algorithm-skills/musk-step-5-automate"><img src="https://agentmods.dev/badge/skills/wezendy/elon-musk-algorithm-skills/musk-step-5-automate.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 | $0.00185 | $0.01526 |
| Opus 5 | $0.00093 | $0.00763 |
| Sonnet 5 | $0.00037 | $0.00305 |
| Haiku 4.5 | $0.00018 | $0.00153 |
Grade A, and why
musk-step-5-automate 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Step 5: Automate
Last. The Fremont rule.
Part of the [[musk-algorithm]]. Fifth and final in the strict order.
Gate
Before this step, verify in the conversation or diff:
- [[musk-step-1-question-requirements]] has produced a list of named, surviving requirements.
- [[musk-step-2-delete-parts]] has produced an explicit deletion list and predicted add-back.
- [[musk-step-3-simplify-optimize]] has produced a complexity delta.
- [[musk-step-4-accelerate-cycle-time]] has produced manual cycle-time measurements.
If any is absent, stop. Run the missing step first. The Fremont rule says automating before this is complete is the costliest engineering mistake.
Why this step exists, and the Fremont rule
The Tesla "alien dreadnought" production line at Fremont was Musk's most public lesson. He attempted to automate the assembly line first. The automation encoded assumptions that turned out to be wrong. Tesla had to rip out the automation, run the line manually long enough to learn the edge cases, simplify the process, and then re-automate only what had proven its shape.
The Fremont rule, stated as a principle: automate only what has been run manually long enough to surface every edge case the automation must handle. Otherwise the automation encodes wrong assumptions, becomes expensive to remove, and creates false confidence that the system "works" when it has only deferred its failures.
Protocol
- Confirm the step you are about to automate survived steps 1 through 4. If it was deleted, do not automate. If it was not simplified, return to step 3. If it was not accelerated manually first, return to step 4.
- Confirm the step has been run manually long enough to expose edge cases. Ask: what edge cases were discovered during manual execution? If the answer is "we have not run it manually", do not automate. Run it manually first.
- State what is being automated, precisely. Inputs, outputs, success criteria, failure modes, edge cases handled, edge cases explicitly out of scope.
- State what is deliberately not automated, and why. Every automation has parts that should stay manual. Name them.
- Plan reversibility from day one. How does the automation get ripped out if it was a mistake? What is the manual fallback?
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 · 119 lines · 185 tokens per session scan A 892c88477709
musk-step-5-automate is a skill published in the GitHub repository wezendy/elon-musk-algorithm-skills (9 stars, last pushed 3mo ago), licensed MIT. It adds 185 tokens to every session and 1,526 once invoked, about $0.0009 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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