rapid-domain-mastery

Builds field maps from multi-source academic or technical corpora: expert mental models, debates, assumptions, prerequisites, oral-exam questions, and sprint study plans. Use for exam prep, research onboarding, or rapid topic mastery from multiple sources. Not for plain summaries or single short docs.

Ir para a instalação

Repositório: abe238/community-skills
Última atividade na origem: 29 de maio de 2026 às 03:30
Idioma detectado do SKILL.md: inglês
Estrelas: 1
Forks: 0

Opções de instalação

Por padrão, está selecionado o prompt que primeiro revisa a origem. Você pode mudar para um comando direto ou baixar uma cópia local.

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

Um comando direto ignora o prompt de revisão. Verifique a origem antes de executá-lo.

npx skills add https://github.com/abe238/community-skills --skill rapid-domain-mastery

O comando permanece em uma só linha. Role horizontalmente para revisá-lo antes de copiar.

Prefere uma cópia local? Baixe os arquivos disponíveis atualmente no SkillsMP.

Revise os arquivos de origem

Leia o SKILL.md e os arquivos complementares exibidos pelo SkillsMP antes de decidir se vai instalar.

Explorador de arquivos

25 arquivos

SKILL.md

Instruções da origem · Visualização somente leitura

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Rapid Domain Mastery

First pass

Read references/00-routing-and-boundaries.md.

Decide whether the corpus is strong enough for synthesis; if it is thin, label the weak spots with [Gap] and keep claims bounded.

Read references/10-input-contract.md and normalize subject, goal, level, time budget, source shape, and desired mode.

Core modules

Always load references/20-corpus-audit.md.

Load references/30-field-cartography.md and references/40-mental-model-extraction.md for field maps, conceptual compression, or expert-model extraction.

Load references/50-debate-cartography.md when the corpus contains competing schools, methods, interpretations, or tradeoff-heavy positions.

Load references/60-assumption-mining.md in every deep run; hidden assumptions are where fake understanding usually hides.

Load references/70-prerequisite-ladder.md when the user is missing foundations or the corpus assumes them.

Load references/80-diagnostic-question-design.md for exam prep, interviews, mastery checks, or concept stress tests.

Load references/90-tutor-loop.md when the user wants interactive drilling.

Load references/100-study-sprint-planner.md when the user gives a time budget.

Load references/110-application-and-transfer.md when the user wants design, implementation, policy, teaching, or project transfer.

Load references/120-domain-adapters.md when discipline-specific handling matters.

Load references/130-mcp-and-tooling.md only when tools or live retrieval materially change the workflow.

Load references/140-output-templates.md and files in templates/ when a structured deliverable will help.

Load references/150-quality-gates.md before finalizing any substantial answer.

Load references/160-failure-modes.md if the task risks summary drift, fake consensus, or thin-corpus overreach.

Epistemic labels

Use these when helpful: [Consensus], [Debate], [Open], [Prereq], [Inference], [Gap].

Default output

Return, in this order when appropriate: corpus audit, core mental models, major disagreements, open questions, hidden assumptions, prerequisite ladder, diagnostic questions, and either tutor start or sprint plan.