「big bang」の検索結果

Expert-level cosmology covering the Big Bang, cosmic expansion, dark matter, dark energy, CMB, large-scale structure, and observational cosmology.

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Guided journey from a large aged codebase everyone fears to touch to one that is safe to change, legible, bounded, and resilient - paid down in place without a rewrite. Orchestrates eight skills phase by phase - working-with-legacy-code, refactoring-patterns, clean-code, software-design-philosophy, clean-architecture, pragmatic-programmer, release-it, domain-driven-design - asking the user questions at every decision point and recording results in the project docs/ folder (TESTING.md, TECH-DEBT.md, REMOVE-TECHNICAL-DEBT-PLAN.md) so the journey resumes across sessions. Use when the user wants to tame a legacy codebase, pay down technical debt safely, avoid a big-bang rewrite, or says 'we are afraid to touch this code'. For a fresh vibe-coded prototype, improve-code-quality; for greenfield structure, design-code-architecture; for a product-and-UX pass, improve-app; to optimize a working codebase for speed, architecture-optimization. For one framework in isolation, invoke that skill directly.

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Moves data from one system to another without losing it or corrupting it — profiling the source before mapping, deciding between big-bang and parallel-run cutover, reconciling counts and values rather than assuming, handling the records that will not map cleanly, and planning a rollback that is actually executable. Use this to plan or run a migration, assess a migration plan someone else wrote, work out why a completed migration is producing wrong numbers, or size how long one will really take.

日本語の概要は準備中です。原文の説明を表示しています。

Observational cosmology from Hubble's law to the CMB. Covers redshift, Hubble expansion, the cosmological parameters, the cosmic microwave background, large-scale structure, galaxy rotation curves and dark matter, Type Ia SNe and dark energy, and the current state of Lambda-CDM. Use when reasoning about the large-scale universe, interpreting cosmological surveys, or teaching the Big Bang evidence chain.

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Execute structural metamorphosis using strangler fig migration, chrysalis phases, and interface preservation. Covers transformation planning, parallel running, progressive cutover, rollback design, and post-metamorphosis stabilization for system architecture evolution. Use when assess-form has classified the system as READY for transformation, when migrating from monolith to microservices, when replacing a core subsystem while dependents continue operating, or when any architectural change must be gradual rather than big-bang.

日本語の概要は準備中です。原文の説明を表示しています。

Use when a task needs the judgment of a Computer Systems Analyst — running requirements elicitation and gap analysis against a target system, writing a feasibility study for a build-vs-buy-vs-customize decision, designing a system integration approach (point-to-point vs middleware vs API-led), scoping data-migration risk before a cutover, or choosing between phased and big-bang implementation strategies.

日本語の概要は準備中です。原文の説明を表示しています。

Use when work is ambiguous or has multiple viable paths; compares options, assumptions, evidence, tradeoffs, and the best next action.

日本語の概要は準備中です。原文の説明を表示しています。