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SkillsMP has collected 579 skills from curiositech/windags-skills. Open a skill to review its source and details.
curiositech/windags-skillsShowing 19 of 579 collected skills.
Designs ethical engagement systems for wellness apps — onboarding, habit loops, streaks, re-engagement, and push strategy that serve user health over retention metrics. Grounded in BJ Fogg's Behavior Model, Self-Determination Theory, and the Hook Model…
Expert in Windows 3.1 era sound vocabulary for modern web/mobile apps. Creates satisfying retro UI sounds using CC-licensed 8-bit audio, Web Audio API, and haptic coordination. Activate on 'win31 sounds', 'retro audio', '90s sound effects', 'chimes', 'tada',…
Expert in Windows 3.1 era pixel art and graphics. Creates icons, banners, splash screens, and UI assets with authentic 16/256-color palettes, dithering patterns, and Program Manager styling. Activate on 'win31 icons', 'pixel art 90s', 'retro icons',…
Build WinDAGs — the orchestration platform where AI agents accumulate genuine expertise through DAGs of skillful agents. Covers DAG design, execution engines, meta-DAG architecture, skill selection, dynamic mutation, visualization, and deployment. Activate on…
Post-execution skill crystallization and learning engine updates for WinDAGs. Runs after successful execution to update Thompson sampling parameters, track method quality, detect monster-barring, log near-miss events, and signal Kuhnian crises. Activate on…
Two-stage review engine with four-layer quality model for the WinDAGs meta-DAG. Receives completed node outputs and produces ReviewResult containing QualityVector. Stage 1 (Haiku) checks Floor + Wall on every node. Stage 2 (Sonnet) runs Ceiling evaluation…
Maintain consistency across all winDAGs documentation surfaces — corpus documents, marketing copy, README files, site content, skill files, API docs, and derivative documents. Enforces the canonical terminology table, voice guidelines, architectural accuracy,…
Polya's four questions after every WinDAGs execution. Q1 (contract satisfied?) and Q2 (unstated assumptions?) are mandatory on every DAG. Q3 (generalizable?) and Q4 (broader connections?) are conditional on quality and cost thresholds, run asynchronously, and…
Failure diagnosis, DAG mutation, and escalation engine for the WinDAGs meta-DAG. Receives failure information and quality vectors from the Evaluator. Classifies failures on four dimensions. Follows a five-level escalation ladder. Applies seven mutation types…
This skill should be used when a SKILL.md file needs compression, deduplication, or token reduction. It provides an embedding-based compression pipeline that detects and removes redundant chunks within SKILL.md files using local embeddings (all-MiniLM-L6-v2).…
Expert in authentic Windows 3.1 aesthetic for modern web applications. Creates pixel-perfect retro UI with beveled borders, system gray palettes, and program manager styling. Activate on 'windows 3.1', 'retro ui', 'beveled borders', 'win31', 'program…
Modern web applications with authentic Windows 95 aesthetic. Gradient title bars, Start menu paradigm, taskbar patterns, 3D beveled chrome. Extrapolates Win95 to AI chatbots, mobile UIs, responsive layouts. Activate on 'windows 95', 'win95', 'start menu',…
Longitudinal memory tracking, philosophy teaching, and personal accountability with compassion. Expert in pattern recognition, Stoicism/Buddhism, and growth guidance. Activate on 'accountability', 'philosophy', 'Stoicism', 'Buddhism', 'personal growth',…
Comprehensive introduction to multi-agent systems covering coordination, communication, and distributed AI theory
Framework for building multi-agent conversation systems with customizable LLM-powered agents
Comprehensive survey of LLM-based task planning methods including decomposition, search, and execution strategies
Prompting paradigm combining reasoning traces with actions for LLM agents to interact with external tools
Framework for deliberate problem-solving with LLMs through exploration of branching reasoning paths
Formal verification approach to LLM evaluation ensuring correctness and consistency in automated judging