cfec11bb46
stop-slop, taste-skill, terrashark had embedded .git dirs causing Woodpecker clone to fail on submodule update.
1.5 KiB
References
Cited Studies
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EmotionPrompt (Microsoft Research) — Demonstrates that emotional and stakes-based prompt framing mathematically improves LLM reasoning quality and output length. Documents the +45% improvement from financial framing and +115% from combined stimuli.
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LazyBench — Proves that frontier models (Gemini 1.5 Pro, GPT-4o) actively select cognitive shortcuts and fail tasks they are capable of solving when the perceived effort exceeds internal thresholds.
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Compounding Error Avoidance — Research demonstrating that models truncate outputs as a risk mitigation strategy, preferring shorter responses to reduce the surface area for factual errors on long-form tasks.
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Seasonal Behavior Analysis (Winter Break Hypothesis) — Statistical analysis confirming that LLMs internalize seasonal work patterns from training data, producing measurably shorter outputs during periods corresponding to human holiday seasons.
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2025 Controlled Laziness Experiments — Three-part academic study (December 2025) confirming that output truncation is a behavioral artifact of alignment training, not a failure of context processing or model capability.
Further Reading
- Google Gemini API documentation on
thinking_levelparameter configuration - Anthropic MCP (Model Context Protocol) specification and integration guides
- OpenAI API reference for temperature and Top-p parameter tuning
- YAML front-matter specification for SKILL.md lazy-loading architecture