28 eval-informed mental models and critical-thinking skills for Claude Code, GitHub Copilot, Codex, Cursor, and other Agent Skills-compatible tools
165 evidence-grounded AI skills for teachers, school leaders and EdTech builders—pedagogy, learning science, curriculum, assessment and regeneration. Claude, Codex and Hermes.
FPF (First Principles Framework) Library: a library of methods and pattern languages for engineering, research, management and human development, used by people and AI agents. Includes FPF Core, domain frameworks (DPFs) and Suites.
systems is a set of tools for describing, running and visualizing systems diagrams.
Structured reasoning methodologies from history's most rigorous thinkers, packaged as Claude Code skills.
Headless product design for AI coding agents, backed by a transactional product graph | Design how it works, verify what you ship.
An AI skill pack distilling Selected Works of Mao Zedong into reusable cognition, strategy, organization, and execution modules.
把《认知红利》中的思维升级方法论蒸馏成 15 个可执行的 AI skill 工具包
A reasoning skill for AI agents to improve complex judgment, premise auditing, counterargument pressure, and verifiable conclusions.
500+ transferable reasoning primitives extracted from 32 domains. Mental models that survive beyond domain specifics. Bayesian statistics, system dynamics, mechanism design, military strategy, and 28 others. Each tool: what it is, the key move, where it transfers, how it fails. For critical thinking and decision-making.
A work of meta-recursive experiential fiction exploring the boundaries between truth, perception, consciousness, and reality.
AI agent skills for thinking clearly, making better decisions, and getting things done. Strategy, research, decision-making, planning, risk management, negotiation, execution, strategic thinking, BMAD-METHOD elicitation, reasoning, business strategy, market research, competitive intelligence, forecasting, scenario planning, problem solving, priorit
A systems-thinking essay that explains why failure rarely happens suddenly. It shows how slow drift, accumulating pressure, and weakening buffers push systems toward collapse long before outcomes change, and why prediction-focused analytics miss the most important phase of failure.
Clarify definitions, identify key assumptions, and rethink complex problems from first principles. 用第一性原理澄清定义、识别关键假设并重新审视复杂问题。
[ARCHIVED → CodeAlive-AI/ai-driven-development] FPF (First Principles Framework) skill consolidated into the ai-driven-development umbrella collection.
A long-form article and practical framework for designing machine learning systems that warn instead of decide. Covers regimes vs decimals, levers over labels, reversible alerts, anti-coercion UI patterns, auditability, and the “Warning Card” template, so ML preserves human agency while staying useful under uncertainty.
An explanation-first HR analytics system that reconstructs why employee exit becomes rational. Instead of predicting attrition, it generates human-readable exit narratives by decomposing pressure and retention forces, adding peer context and counterfactual interventions to reveal how stability erodes over time.
An early-warning system that models disasters as instability transitions rather than isolated events. It combines force-based instability modeling with an interpretable ML escalation-risk layer to detect when hazards become disasters due to exposure growth, response delays, and buffer collapse.
An interpretable early-warning engine that detects academic instability before grades collapse. Instead of predicting performance, it models pressure accumulation, buffer strength, and transition risk using attendance, engagement, and study load to explain fragility and identify high-leverage interventions.
An interpretable battery health engine that detects hidden points of no return instead of just predicting health %. It models stress, buffer, and degradation intensity, discovers Stable/Drifting/Irreversible regimes via GMM, and learns simple Decision Tree thresholds, with a Streamlit app for diagnostics and what-if scenarios.
To associate your repository with the systems-thinking topic, visit your repo's landing page and select "manage topics."