Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
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Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
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Explains ML predictions on omics data with SHAP, LIME, and permutation importance, handling the correlated-feature trap, the conditional-vs-interventional Shapley choice, and the attribution-is-not-causation boundary. Use when interpreting an omics classifier, debugging shortcut/batch learning, or deciding whether an attribution ranking can be trusted as biology. For validated feature selection see machine-learning/biomarker-discovery; explanations are not a selection method.
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Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
中文简介正在准备中。当前显示原文说明。
Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
中文简介正在准备中。当前显示原文说明。
Use this skill to evaluate whether to switch from annual MVR pulls to continuous monitoring. Covers cost-benefit, intervention timing, and major providers.
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Use this skill when the user asks about FMCSA Compliance Safety Accountability (CSA) program scoring — the seven BASIC categories, BASIC Severity Indicator (BSI), peer percentiles, intervention thresholds, how violations age out, SMS Methodology, ISS (Inspection Selection System), what "alert" status means, Safety Measurement System mechanics, or DataQ disputes. Cite SMS Methodology v3.20.
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Handle mental health crisis situations in AI coaching safely. Use when implementing crisis detection, safety protocols, emergency escalation, or suicide prevention features. Activates for crisis keywords, safety planning, hotline integration, and risk assessment.
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Expert in cluttering -- the lesser-known fluency disorder characterized by rapid/irregular speech rate, excessive disfluencies, and frequent ADHD comorbidity. Covers differential diagnosis from stuttering, assessment protocols, therapy approaches (rate control, self-monitoring, pragmatic awareness), technology-assisted intervention, and AI tools for people who clutter. Activate on 'cluttering', 'rapid speech disorder', 'speech rate too fast', 'speech disfluency not stuttering', 'disorganized speech', 'ADHD speech problems', 'cluttering vs stuttering', 'speech intelligibility', 'mazed speech', 'telescoping words'. NOT for stuttering-only treatment (overlap is common but they are distinct), hearing disorders, or voice disorders (pitch, resonance).
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This skill should be used when the user asks to "これらのIssueを全部実装して", "implement these issues autonomously", "Issue一覧を自動で片付けて", "これらのタスクを順番に実装してPRにして", or provides a list of GitHub Issue numbers/URLs for autonomous batch implementation. Fetches all specified Issues, resolves dependency order, then iterates through each — creating a worktree, implementing, and opening a PR — without user intervention.
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Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
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Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.
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