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Found 45 Skills
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
A decision-support framework that evaluates systems, architectures, and strategies through the entropy (decay) vs negentropy (growth) lens, while surfacing tacit knowledge gaps. Use this skill whenever the user is making architecture decisions, evaluating system designs, reviewing technical approaches, choosing between options, auditing existing systems, or planning strategies. Also trigger when the user explicitly asks to "apply the negentropy lens", mentions "entropy", "negentropy", "tacit knowledge", "knowledge engine", or "flip the switch". Nudge activation when you detect the user is at a decision point — even if they haven't asked for this lens — by briefly noting the entropic/negentropic dimension before proceeding.
dontbesilent Slow is Fast. It helps entrepreneurs find methods that seem slower but deliver faster results in the long run, and build assets through friction. Trigger methods: /dbs-slowisfast, /slow-is-fast, "Is there a slower way", "Am I going too fast" Slow-is-fast diagnosis. Help entrepreneurs find seemingly slower methods that build assets through friction. Trigger: /dbs-slowisfast, "is there a slower way", "am I going too fast"
Evaluates market bubble risk through quantitative data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when user asks about bubble risk, valuation concerns, or profit-taking timing.
What-if scenario analyzer for sports. Play-calling recommendations, clock management, substitution patterns, risk/reward calculations.
Daily Review Assistant - An AI-assisted decision-making tool for cleaning up knowledge inboxes. The Agent provides "Keep/Delete" suggestions with reasons, and users manually execute after confirmation. Following the principle of "Collect without judging, make decisions during daily review", complete daily knowledge organization in 5-10 minutes. Triggers: /daily-review, /日清, /review
Priority Judgment Assistant - Help users determine priorities from chaotic to-do items and figure out what to do right now. Triggered when users say "I have a lot of things to do", "Help me sort this out", "Set priorities", "What should I do today".
Restaurant recommendations / What to eat / Where to eat / Coffee, bars, desserts, late-night snacks. For users asking questions like "What's good to eat nearby? / Restaurant recommendations / What's the average cost per person? / What time do you close? / Do I need a reservation? / Suitable for families or treating guests?" etc. By default, provide a "query time snapshot" (local time) and source links; do not fabricate restaurant names, addresses, business hours, average cost per person, or ratings; if information is insufficient, first ask 2-3 key questions.
Guide PMs through evaluating feature investments using revenue impact, cost structure, ROI, and strategic value. Delivers build/don't build recommendations.
Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.
Clinical Decision Support System (CDSS) development patterns. Drug interaction checking, dose validation, clinical scoring (NEWS2, qSOFA), alert severity classification, and integration into EMR workflows.
Query schelling.sh for recurring, decision-shaped problems. Retrieve defaults and risks from prior cases, then attach durable follow-up learning. Works for Markdown deliverables when memory should steer decisions. Needs network.