elon-musk

@rules/execution.md @rules/idea-generation.md @rules/report-synthesis.md @rules/validation.md @references/frameworks.md @references/flow-schema.md

Elon Musk

Rebuild decisions from fundamentals, not from copied industry defaults. This skill applies public Musk-style thinking frameworks; it must not impersonate Elon Musk or treat him as an authority.

• Separate real constraints from conventions, defaults, and untested beliefs.
• Generate weird-but-plausible options by applying first-principles operators.
• Turn the analysis into a sharp, reusable decision report with phase tracking.

<when_to_use>

Use this skill when:

• the available options all look like slight variations of the same default
• cost, go-to-market, product, operations, or strategy feels trapped by habit
• the user asks for first-principles analysis, Musk-style frameworks, assumption teardown, or a breakthrough report
• a problem needs a hard reset from fundamentals before normal planning

Do not use this skill when:

• the job is mostly factual research with no redesign or decision pressure
• the request is standard implementation planning or debugging
• the user needs startup readiness scoring rather than assumption teardown
• the user wants broad brainstorming without constraint analysis

Boundary routing:

• Use startup-validator when the main job is startup scoring, evidence grading, or readiness assessment.
• Use genius-thinking when the main job is open-ended idea generation without a concrete problem to deconstruct.
• Use research when the main job is source-backed fact-finding or trend comparison.

Positive examples:

/elon-musk 우리 SaaS 가격 전략이 경쟁사 복붙처럼 보여. 완전히 다시 생각해줘
/elon-musk first principles로 제조 원가를 뜯어보고 10배 낮출 방법을 찾아줘
/elon-musk 뻔하지 않은 시장 진입 리포트를 만들어줘. 기존 GTM 관행부터 의심해줘

Negative examples:

/research 이 뉴스 사실관계만 요약해줘
React hook 버그를 고쳐줘

Boundary example:

스타트업 점수 매겨줘
# Route to startup-validator unless the user explicitly asks to deconstruct assumptions first.

</when_to_use>

<input_check>

If the problem is missing, ask exactly one question:

Which problem should we deconstruct from first principles?

If the desired outcome is unclear but the problem is clear, proceed with a reasonable default: produce a decision report that identifies the best next experiment.

</input_check>

<core_guardrail>

This is a framework skill, not an impersonation skill.

• Say “applying Musk-style first-principles frameworks” rather than pretending to speak as Elon Musk.
• Challenge premises firmly but respectfully.
• Do not hero-worship, copy long external material, or treat any public figure’s view as proof.
• Speed and urgency must include human, legal, safety, trust, and quality guardrails.

</core_guardrail>

<owned_job>

For each run:

1. Restate the real decision, not just the surface request.
2. Gather only the facts needed to reason correctly; cite current facts when they matter.
3. Classify assumptions with the A/B/C model in references/frameworks.md.
4. Apply The Algorithm gate: question requirements, delete, simplify, accelerate, then automate.
5. Use breakthrough operators from rules/idea-generation.md to create non-obvious options.
6. Synthesize the result with the Mars-shot brief from rules/report-synthesis.md.
7. Stress-test the preferred path with inversion, pre-mortem, and a 24-hour reality test.
8. Run validation from rules/validation.md before finishing.

</owned_job>

<document_shape>

Output Structure

.hypercore/elon-musk/[topic-slug]/
├── flow.json           # phase tracking and validation state
├── research.md         # conventions, facts, source ledger, innovation cases
├── assumptions.md      # A/B/C matrix and Socratic premise attack
├── redesign.md         # Mars-shot brief, option portfolio, scoring
└── execution.md        # Algorithm gate, inversion, pre-mortem, 24h test

• Use ASCII kebab-case for [topic-slug].
• If the folder exists, read existing files and resume from the last incomplete phase.
• Keep the four output files for compatibility; put the sharper brief inside redesign.md rather than adding a new top-level output file.

</document_shape>

<flow_tracking>

Write flow.json at the start and update it as each phase completes. See references/flow-schema.md.

Phase	Output file	Completion signal
research	research.md	copied conventions and required facts are separated
deconstruct	assumptions.md	A/B/C matrix includes evidence questions for unknowns
redesign	redesign.md	Mars-shot brief plus 3-5 scored options exists
execute	execution.md	preferred path has Algorithm gate, risks, and 24h test

</flow_tracking>

Phase	Task	Output file
1	Clarify the real decision and gather only necessary evidence	research.md
2	Attack premises and classify constraints, conventions, unknowns	assumptions.md
3	Generate weird-but-plausible options from surviving fundamentals	redesign.md
4	Pick the bottleneck, stress-test the path, and define next experiments	execution.md

Research rule:

• If the problem depends on current facts, gather and cite them.
• If the problem is conceptual, do not force web, MCP, or team workflows.
• Unknowns should become either evidence questions or concrete experiments.

<output_contract>

Each output file must include:

• research.md: problem restatement, convention map, source ledger for current facts, and at least one innovation case when useful
• assumptions.md: A/B/C matrix, Socratic premise attack, deleted or defended conventions, and unknowns converted into questions/tests
• redesign.md: Mars-shot brief, magic-wand target, 3-5 alternatives, at least one non-obvious option, feasibility/impact/learning-speed scores
• execution.md: Algorithm order gate, bottleneck, inversion scenarios, pre-mortem, safety guardrails, and a 24-hour reality test or explicit reason it cannot be run

</output_contract>

Before finishing, verify:

• at least one convention was deleted or explicitly defended
• at least one hard constraint remains visible
• at least one unknown became a research question or experiment
• the preferred option does not optimize or automate something that should be deleted
• the report has a thesis, metric, bottleneck, next experiment, and safety caveat
• all current factual claims are cited or marked as assumptions
• all output files are saved and flow.json is set to completed