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half-life

Model decay processes by the time required for half of a quantity to degrade, enabling exponential decay predictions

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Repository
lev-os/agents
Letzte Quellaktivität
7. März 2026 um 00:14
Erkannte Sprache von SKILL.md
Englisch
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22
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2

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
half-life
description
Model decay processes by the time required for half of a quantity to degrade, enabling exponential decay predictions
# Half-Life **What**: The time required for half of a quantity to decay or lose half its value—applies to radioactive decay, drug metabolism, information relevance, and any exponential decay process. **When to use**: Modeling decay of knowledge, skill retention, technical debt accumulation, or any process where value/quantity declines exponentially over time. **Introduced by**: Ernest Rutherford (1907) for radioactive decay; widely applied concept ## Core Mechanism **Exponential decay formula**: N(t) = N₀ × (1/2)^(t/t₁/₂) Where: - N(t) = remaining quantity at time t - N₀ = initial quantity - t₁/₂ = half-life period **Key insight**: After one half-life, 50% remains. After two half-lives, 25% remains. Decay is exponential, not linear. ## Execution Steps ### 1. Identify Decaying Quantity What degrades over time? Knowledge, skills, relationships, documentation accuracy? ### 2. Measure Half-Life How long until half the value is lost? Historical data or estimation. ### 3. Model Future Decay Use half-life formula to predict future state. ### 4. Determine Refresh Cycle How often must you refresh to maintain minimum threshold? ### 5. Design Decay Mitigation Build reinforcement loops to counteract natural decay. ## Real-World Applications **Documentation**: Half-life ~6-12 months in fast-moving projects. After 2 years, <25% still accurate. **Skills**: Programming language knowledge half-life depends on ecosystem velocity (JavaScript ~2 years, SQL ~10 years) **Relationships**: Professional network half-life ~2-3 years without maintenance **Cache**: Data freshness half-life determines cache TTL ## Scoring Criteria **Practitioner Weight**: 9/10 — Rutherford's work empirically validated; widely used in physics, medicine, chemistry **Clarity & Executability**: 9/10 — Clear quantitative model; directly actionable **Proven ROI**: 8/10 — Enables nuclear medicine, carbon dating, cache strategies, learning models **Novelty**: 7/10 — Intuitive for physical decay; insightful when applied to information/skills **Cross-Domain Applicability**: 9/10 — Physics, medicine, software caching, knowledge management, skill development **Total Score**: 42/50 (Tier 1: Canonical)
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