2,583 件 ・ 関連度順
概要と使いどころ
De novo molecule generation for drug discovery. Scaffold-based analog enumeration, fragment growing/linking, structure-based design, multi-objective optimization, and drug-likeness filtering.
日本語の概要は準備中です。原文の説明を表示しています。
Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda window scheduling, soft-core potentials, REST2 enhanced sampling, MBAR/BAR analysis, and cycle closure validation. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.
日本語の概要は準備中です。原文の説明を表示しています。
Compile your local stellar-build usage traces into sharper skills. Use when the user says "optimize my skills", "optimize-skills", "improve my skills from usage", "learn from my traces", "stellar-loop optimize", or wants the learning loop to refine installed skills based on how they've actually been used. DSPy-style prompt optimization over the local trace store at ~/.stellar-build/traces — fully local, reversible.
日本語の概要は準備中です。原文の説明を表示しています。
Review hot paths, allocations, iteration, caching, event frequency, and correctness-preserving optimization.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' 'ad copy,' 'ad creative,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' or 'audience targeting.' This skill covers campaign strategy, ad creation, audience targeting, and optimization.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy. Also use when the user mentions 'referral,' 'affiliate,' 'ambassador,' 'word of mouth,' 'viral loop,' 'refer a friend,' or 'partner program.' This skill covers program design, incentive structure, and growth optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Build AI inventory optimization systems. TRIGGERS - Use when user needs help with ai-inventory-optimizer related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Build AI pricing optimization. TRIGGERS - Use when user needs help with ai-pricing-optimizer related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Build AI calendar optimization systems. TRIGGERS - Use when user needs help with ai-calendar-optimizer related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Manage AI costs with usage tracking and optimization. TRIGGERS - Use when user needs help with ai-cost-management related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Build AI budget optimization systems. TRIGGERS - Use when user needs help with ai-budget-optimizer related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Guide agency management system setup and optimization. TRIGGERS - Use when user needs help with agency-management-system related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Convert an image between PNG, JPEG, and WebP formats with quality control for web optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Expert database administrator specializing in high-availability systems, performance optimization, and disaster recovery. Masters PostgreSQL, MySQL, MongoDB, and Redis with focus on reliability, scalability, and operational excellence.
日本語の概要は準備中です。原文の説明を表示しています。
Expert dependency manager specializing in package management, security auditing, and version conflict resolution across multiple ecosystems. Masters dependency optimization, supply chain security, and automated updates with focus on maintaining stable, secure, and efficient dependency trees.
日本語の概要は準備中です。原文の説明を表示しています。
Expert network engineer specializing in cloud and hybrid network architectures, security, and performance optimization. Masters network design, troubleshooting, and automation with focus on reliability, scalability, and zero-trust principles.
日本語の概要は準備中です。原文の説明を表示しています。
Expert Kubernetes specialist mastering container orchestration, cluster management, and cloud-native architectures. Specializes in production-grade deployments, security hardening, and performance optimization with focus on scalability and reliability.
日本語の概要は準備中です。原文の説明を表示しています。
Docker image reviews, optimization, and step-building guidance. Analyzes Dockerfiles for best practices, security issues, and anti-patterns.
日本語の概要は準備中です。原文の説明を表示しています。
Expert code reviewer specializing in code quality, security vulnerabilities, and best practices across multiple languages. Masters static analysis, design patterns, and performance optimization with focus on maintainability and technical debt reduction.
日本語の概要は準備中です。原文の説明を表示しています。
Creates, debugs, and optimizes GitHub Actions workflow YAML files. Recommends current action versions with SHA pinning from a daily-updated index of 120+ actions. Configures matrix builds, dependency caching, reusable workflows, OIDC authentication, secrets management, and runner selection. Reviews existing workflows for outdated actions, security issues, and performance problems. Use when the user asks about GitHub Actions, workflows, CI/CD, .github/workflows, any action by name (actions/checkout, setup-node, setup-python, etc.), or workflow optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Expert in web accessibility, WCAG compliance, screen reader optimization, keyboard navigation, ARIA attributes, and inclusive design. Activates for accessibility improvements, WCAG compliance, a11y audits, and inclusive design tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Quantifies biodiversity from species abundance/incidence tables using Hill numbers (iNEXT) with coverage-based rarefaction-extrapolation (Chao & Jost 2012), asymptotic richness via Chao1/ACE/jackknife as a lower bound, Baselga turnover/nestedness partition with the Podani alternative as sensitivity check, mandatory Hellinger transformation before ordination (Legendre & Gallagher 2001), Faith PD and SES_MPD/SES_MNTD with explicit null-model choice, and Maire 2015 functional-diversity dimensionality optimization. Use when comparing diversity across sites with unequal sampling effort, picking the right richness estimator for singleton-heavy amplicon data, partitioning beta diversity into turnover vs nestedness, reporting Hill-number effective species counts rather than raw entropies, computing SES_MPD with explicit null-model justification, or deciding whether to apply standard metrics to compositional amplicon data. Not for clinical 16S microbiome diversity (see microbiome/diversity-analysis).
日本語の概要は準備中です。原文の説明を表示しています。
Resolve the architecture of focal oncogene amplifications — extrachromosomal DNA (ecDNA), breakage-fusion-bridge (BFB) cycles, homogeneously staining regions (HSR), and linear amplification — from whole-genome sequencing with AmpliconArchitect, the AmpliconSuite pipeline, and AmpliconClassifier. Covers copy-number seed selection, breakpoint-graph reconstruction, balanced-flow optimization, ecDNA classification, and the limits of depth-only amplification calls. Use when a focal amplification needs structural characterization, when distinguishing ecDNA from chromosomal amplification, suspecting ecDNA-driven oncogene amplification or therapy resistance, or selecting copy-number seeds for amplicon reconstruction.
日本語の概要は準備中です。原文の説明を表示しています。