Generates complete reference-grounded single-drug adverse-effect network-pharmacology research designs from a user-provided drug, adverse event, and desired evidence depth. Always use this skill when a user wants to design, plan, or upgrade a conventional network-pharmacology study centered on one fixed drug and one fixed adverse-effect endpoint, using drug-target prediction, adverse-event target collection, overlap analysis, PPI hub prioritization, enrichment interpretation, molecular docking, and optional orthogonal transcriptomic or literature validation. Covers five study patterns (canonical hub-first, cardiotoxicity or electrophysiology-oriented, immune-inflammatory adverse effect, organ-toxicity pathway context, translational validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, dependency/evidence map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, verified-reference pack, and self-critical risk review.
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。
aipoch/medical-research-skills☆ 1,9602026年9月17日 更新
Generates complete conventional oncology bulk-transcriptome biomarker and hub-gene research designs from a user-provided cancer type and study direction. Always use this skill whenever a user wants to design, plan, or build a tumor bioinformatics study centered on differential expression, prognostic filtering or risk modeling, PPI-based hub-gene prioritization, diagnostic/prognostic evaluation, clinical association, immune infiltration context, methylation context, and optional tissue or cell validation. Covers five study patterns (signature-first prognostic workflow, hub-gene-first biomarker workflow, hybrid signature-to-hub workflow, immune-context biomarker workflow, translational validation workflow) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path...
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。
aipoch/medical-research-skills☆ 1,9602026年9月17日 更新
Designs QTL colocalization studies that connect eQTL, pQTL, sQTL, or related molecular QTL signals with GWAS loci. Always use this skill whenever a user wants to plan, scope, or structure a locus-level study asking whether a GWAS association and a molecular QTL association may reflect the same underlying causal signal. Covers locus definition, QTL/GWAS source architecture, ancestry and LD alignment, single-locus vs multi-locus strategy, candidate-gene prioritization, optional fine-mapping, linked MR/SMR follow-up, and functional annotation. Always output four workload configurations (Lite / Standard / Advanced / Publication+) with a recommended primary plan, stepwise workflow, method rationale, evidence hierarchy, figure plan, minimal executable version, and strictly verified literature guidance with no fabricated references. Never equate colocalization with causality proof, mediation proof, or automatic target validation. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets, repositories, consortia, or public resources.
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。
aipoch/medical-research-skills☆ 1,9602026年9月17日 更新
Designs internal, external, temporal, and functional validation strategies at the protocol stage for medical research studies.
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。
aipoch/medical-research-skills☆ 1,9602026年9月17日 更新
Generates complete Mendelian Randomization + single-cell transcriptomics (scRNA-seq) research designs from a user-provided direction. Always use this skill whenever a user wants to design, plan, or build a study combining MR and single-cell data — even if phrased as "help me write a paper on X", "design a bioinformatics study for Y", or "I want to study Z using MR and scRNA". Covers five study patterns (mechanism gene-set, key-cell, candidate-gene reverse validation, exposure-disease-cell triangulation, translational biomarker) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, and a strictly verified reference literature retrieval layer with real references only.
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。
aipoch/medical-research-skills☆ 1,9602026年9月17日 更新
Generates complete NHANES-style cross-sectional epidemiology + retrospective clinical validation research designs from a user-provided disease and biomarker direction. Always use this skill whenever a user wants to design, plan, or build a population-level biomarker association study using NHANES or similar survey datasets, especially when the article logic includes disease definition, biomarker formula derivation, multivariable logistic regression, restricted cubic spline analysis, subgroup stability testing, and a secondary hospital-based retrospective validation cohort. Covers five study patterns (cross-sectional association, dose-response / RCS, subgroup-stability, NHANES + retrospective validation, preliminary screening-performance) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path...
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。
aipoch/medical-research-skills☆ 1,9602026年9月17日 更新
Designs discovery, modeling, and validation workflows for prognostic biomarkers in biomedical and clinical research. Always use this skill when the user needs a prognostic biomarker study blueprint rather than a diagnostic test protocol, predictive biomarker design, treatment recommendation, or a completed manuscript. Focus on endpoint family, follow-up horizon, time scale, candidate marker strategy, model-building logic, risk stratification framework, and internal/external validation requirements. Do not invent cohort size, event rate, assay readiness, literature support, or validation access.
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。
aipoch/medical-research-skills☆ 1,9602026年9月17日 更新
Explains why studies on the same biomedical topic reach different or opposing conclusions by auditing differences in population, endpoint definition, sample source, assay or platform, study design, statistical model, adjustment strategy, validation chain, and bias control. It separates true contradiction from apparent contradiction caused by framing or methods. Never fabricate references, PMIDs, DOIs, trial identifiers, dataset details, platform details, study features, or conflict explanations that are not supported by the input.
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。
aipoch/medical-research-skills☆ 1,9602026年9月17日 更新
Designs cell-based and animal-based validation plans that translate computational, omics, biomarker, genetic, or clinical findings into experimentally testable validation routes. Always use this skill whenever a user wants to move from an in silico, statistical, or clinical association finding toward wet-lab validation using cell systems, organoid-like systems, xenograft or genetically relevant animal models. It should define the exact claim to test, separate mechanism-testing from association-support and translational-support goals, choose the best-fit model family, specify perturbation strategy, readouts, controls, sequencing of experiments, and four workload configurations (Lite / Standard / Advanced / Publication+) with one recommended primary plan. Never fabricate model availability, reagent availability, species relevance, assay feasibility, phenotype penetrance, expected effect sizes, validation success, or literature references.
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。
aipoch/medical-research-skills☆ 1,9602026年9月17日 更新
Collects candidate biomedical literature across multiple databases, adapts search logic by database, preserves source metadata, and organizes results into a structured, screening-ready candidate pool. Always use this skill when a user wants cross-database literature collection, search strategy construction, candidate paper aggregation, or first-pass evidence organization before deduplication, screening, layered reading, or review planning. Requires real and verifiable literature records only. Every formal literature item must include a real link and DOI when available; never fabricate citations, titles, authors, years, journals, abstracts, PMIDs, or DOIs. If a DOI is unavailable or cannot be verified, state that explicitly rather than inventing one.
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。
aipoch/medical-research-skills☆ 1,9602026年9月17日 更新
Generates complete bidirectional multi-phenotype Mendelian randomization research designs from a user-provided exposure family and outcome family. Always use this skill whenever a user wants to design, plan, or build a genome-wide causal-inference study based on publicly available GWAS summary statistics, especially when the article logic includes multiple exposures, multiple outcomes or subtypes, bidirectional MR, IV filtering, IVW as the main estimator, weighted median / MR-Egger / MR-PRESSO sensitivity analyses, leave-one-out testing, heterogeneity / pleiotropy checks, and multiple-testing control with FDR. Covers five study patterns (single-family bidirectional MR, multi-phenotype screening MR, subtype-resolved MR, phenome-style bidirectional causal map, mechanism-prioritized MR follow-up) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version...
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。
aipoch/medical-research-skills☆ 1,9602026年9月17日 更新
Builds prioritized manuscript revision plans for major or minor revisions by separating comments that require experiments, analyses, clarification, restructuring, or wording changes.
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。
aipoch/medical-research-skills☆ 1,9602026年9月17日 更新
Optimize UI performance against Core Web Vitals — LCP, INP, CLS — with loading/code-split strategy, layout-shift prevention, and animation performance rules. Use when the user wants to improve speed, fix jank or layout shift, hit Web Vitals budgets, or make a UI feel fast on low-end devices.
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。
plugin87/ux-ui-agent-skills☆ 1,9542026年10月11日 更新
Use this skill for planning, testing, and safely executing PostgreSQL schema migrations — especially when working with production data or shared databases. **Trigger when user asks to:** - Test a schema migration before applying it to production - Add, remove, or rename columns safely on a live table - Change a column's data type without downtime - Add or drop indexes, constraints, or foreign keys on large tables - Understand which ALTER TABLE operations lock the table - Roll back a failed migration - Plan a zero-downtime migration strategy - Fork a database to test a migration safely **Keywords:** migration, schema change, ALTER TABLE, add column, drop column, rename column, change type, zero downtime, lock, AccessExclusiveLock, concurrent index, forking, rollback, backfill, deploy Covers: lock-level reference for every common DDL operation, safe migration patterns, fork-based testing, zero-downtime column changes, index creation, constraint addition, backfill strategies, pre/post-migration validation, and rollback planning.
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。
timescale/pg-aiguide☆ 1,8692026年10月15日 更新
Document chunking with multiple strategies including semantic, recursive, and fixed-size chunking
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。
a5c-ai/babysitter☆ 1,8472026年9月17日 更新
Design technical architecture, select technology stack, and define implementation strategy from specifications and constitution constraints.
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。
a5c-ai/babysitter☆ 1,8472026年9月17日 更新
Transform research findings into actionable implementation plans with stakes-based rigor, test-first strategy, and granular task decomposition.
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。
a5c-ai/babysitter☆ 1,8472026年9月17日 更新
Generate comprehensive investor-ready business case document with market, solution, financials, and strategy
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。
rmyndharis/antigravity-skills☆ 1,7752026年10月15日 更新
Expert startup business analyst specializing in market sizing, financial modeling, competitive analysis, and strategic planning for early-stage companies. Use PROACTIVELY when the user asks about market opportunity, TAM/SAM/SOM, financial projections, unit economics, competitive landscape, team planning, startup metrics, or business strategy for pre-seed through Series A startups.
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。
rmyndharis/antigravity-skills☆ 1,7752026年10月15日 更新
Creates comprehensive content outlines and topic clusters for SEO. Plans content calendars and identifies topic gaps. Use PROACTIVELY for content strategy and planning.
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。
rmyndharis/antigravity-skills☆ 1,7752026年10月15日 更新
Expert hybrid cloud architect specializing in complex multi-cloud solutions across AWS/Azure/GCP and private clouds (OpenStack/VMware). Masters hybrid connectivity, workload placement optimization, edge computing, and cross-cloud automation. Handles compliance, cost optimization, disaster recovery, and migration strategies. Use PROACTIVELY for hybrid architecture, multi-cloud strategy, or complex infrastructure integration.
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。
rmyndharis/antigravity-skills☆ 1,7752026年10月15日 更新
This skill should be used when the user asks to "analyze competitors", "assess competitive landscape", "identify differentiation", "evaluate market positioning", "apply Porter's Five Forces", or requests competitive strategy 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。
rmyndharis/antigravity-skills☆ 1,7752026年10月15日 更新
Use before writing any type of tests. Distills 14 industry sources into deterministic decision gates, schemas, and worked test examples.
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。
NeoLabHQ/context-engineering-kit☆ 1,7752026年8月27日 更新
The screenwriting business and career (编剧行业与生意经) — merged from Diamond & Weissman's Bulletproof (buyer's-eye workflow, three Cs, one-page nine-step, set pieces, submission, notes, resilience), Eric Bork's The Idea (PROBLEM seven-element idea test, 60/30/10, television differences), Neill Hicks (market four entities, six criteria, WGA, agents, option, credit arbitration, gross vs net, step deals), Richard Walter (query letter, agents, package, option, spec, release, copyright, guild, gatekeepers, professionalism, 66 principles), Wendy Henson (breaking in), Blake Snyder (logline pitch, genre, agents), Julian Hoxter (industry terms), Mei Feng's Oscar analyses, and the Hollywood masterclass (pitching, notes, credits, TV vs film). Use when evaluating whether an idea is sellable, writing a logline/query/pitch, preparing a submission, handling notes and rewrites, understanding options/credits/WGA/agents/net profit, choosing between film and TV, or building a career strategy.
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。
jtydhr88/screenwriting-skills☆ 1,6792026年10月3日 更新