2,934 件 ・ 関連度順
概要と使いどころ
Integrate multiple scRNA-seq samples/batches using Harmony, scVI, Seurat anchors, and fastMNN. Remove technical variation while preserving biological differences. Use when integrating multiple scRNA-seq batches or datasets.
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。
Call accessible chromatin regions from ATAC-seq BAM files using MACS3, MACS2, Genrich, or HMMRATAC. Use when identifying open chromatin from aligned ATAC-seq, choosing between point-source vs HMM peak callers, applying ENCODE-style pseudoreplicate IDR, removing blacklist regions, or fixing 501bp consensus peaks for downstream differential 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。
Remove batch effects from RNA-seq data using ComBat, ComBat-Seq, limma removeBatchEffect, and SVA for unknown batch variables. Use when correcting batch effects in expression data.
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。
ChIP-seq peak calling and downstream interpretation with MACS3, signal track export, annotation, motif analysis, and differential binding 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。
ATAC-seq processing with assay QC, MACS3 peak calling, consensus peak matrices, differential accessibility, and motif or footprint follow-up.
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。
Workflow for small RNA and miRNA preprocessing, quantification, differential analysis, and target-oriented interpretation.
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。
Workflow for amplicon microbiome analysis including denoising, taxonomy assignment, diversity analysis, and differential abundance.
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。
Guidance for cell-free protein synthesis (CFPS) optimization. Use when: (1) Planning CFPS experiments, (2) Troubleshooting low yield or aggregation, (3) Optimizing DNA template design for CFPS, (4) Expressing difficult proteins (disulfide-rich, toxic, membrane).
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。
Binder design ranking using ipSAE (interprotein Score from Aligned Errors). Use this skill when: (1) Ranking binder designs for experimental testing, (2) Filtering BindCraft or RFdiffusion outputs, (3) Comparing AF2/AF3/Boltz predictions, (4) Predicting binding success rates, (5) Need better ranking than ipTM or iPAE. For structure prediction, use chai or alphafold. For QC thresholds, use protein-qc.
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。
Cell-free protein synthesis (CFPS) planning and optimization guidance. Use when: (1) Planning CFPS experiments, (2) Troubleshooting low yield or aggregation, (3) Optimizing DNA template design for CFPS, (4) Expressing difficult proteins (disulfide-rich, toxic, membrane).
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。
Workflow for RNA modification analysis such as m6A peak calling, differential modification, and transcript-level visualization.
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。
Workflow for Hi-C and related 3D genomics analyses including compartments, loops, TADs, differential contacts, and visualization.
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。
Generate data-backed content briefs by analyzing Google SERP results, competitor content, keyword intent, and audience questions. Produces writer-ready briefs with target queries, required subtopics, recommended format, word count, and competitive differentiation angles.
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 SEO-driven pages at scale using templates and data. Also use when the user mentions "programmatic SEO," "template pages," "pages at scale," "directory pages," "location pages," "[keyword] + [city] pages," "comparison pages," "integration pages," "building many pages for SEO," "pSEO," "generate 100 pages," "data-driven pages," or "templated landing pages." Use this whenever someone wants to create many similar pages targeting different keywords or locations. For auditing existing SEO issues, use an available SEO audit capability. For content strategy planning, use an available content strategy capability.
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。
Analyze competitor content coverage and uncover differentiated content opportunities using web search, page extraction, and DataForSEO content analysis. Use when asked for competitor content research, editorial gap analysis, content brief inputs, or topic whitespace.
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。
Guidance for using Generator.Equals — a C# source generator for auto-generating Equals, GetHashCode, operators, and Diff/Inequalities methods via attributes.
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 Java code for bugs, duplicate code, correctness risks, maintainability improvements, and missing tests. By default review files modified in git; when the user explicitly names files, classes, packages, or a diff, review that scope instead. Generate a detailed review.md report with actionable comments and fixes.
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。
Test application performance with k6 load/stress/soak/spike scripts and k6 scenarios, Lighthouse CI for Web Vitals, and performance budgets as CI gates. Covers load profiles, custom metrics, bottleneck identification, and Core Web Vitals (LCP, INP, CLS). Use when: "performance test," "load test," "stress test," "soak test," "spike test," "k6," "k6 scenarios," "Lighthouse," "Web Vitals," "Core Web Vitals," "performance budget." Not for: scheduled production probes — use synthetic-monitoring; pixel-diff regressions — use visual-testing; designing tests from prod telemetry — use observability-driven-testing. Related: ci-cd-integration, qa-metrics, release-readiness.
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。
Test for WCAG 2.2 AA compliance with axe-core + Playwright, keyboard navigation audits, screen reader testing, ARIA pattern validation, and legal compliance mapping (ADA, EAA, Section 508). Automated tools catch 30-40% of issues — this skill covers automated and manual testing together. Use when: "accessibility," "a11y," "WCAG," "screen reader," "axe," "keyboard navigation," "ARIA," "ADA compliance." Not for: cookie-consent/GDPR compliance — use compliance-testing; pixel-diff visual regression — use visual-testing. Related: playwright-automation, compliance-testing, visual-testing, ci-cd-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。
Measure and improve test coverage meaningfully. Covers Istanbul/V8/coverage.py configuration, coverage gap analysis by risk, coverage-as-ratchet in CI (never let it decrease), PR coverage diff checks, mutation testing for assertion quality, and distinguishing meaningful from vanity coverage. Use when: "code coverage," "coverage gap," "Istanbul," "coverage threshold," "coverage report," "branch coverage." Not for: writing the tests that raise coverage — use unit-testing; coverage as a tracked KPI trend over time — use qa-metrics. Related: unit-testing, ci-cd-integration, qa-metrics, ai-qa-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。
Use AI to write NEW test code from specs, PRDs, user stories, code diffs, bug reports, or OpenAPI specs. Staged pipeline: requirements extraction → risk analysis → coverage matrix → scenario generation → oracle design → test code → human review, with guardrails against hallucinated APIs and weak assertions. Use when: "generate tests from spec," "tests from PRD," "tests from user story," "auto-generate test cases," "AI write tests for me." Not for: testing AI/LLM features in your product — use ai-system-testing. Not for: auditing a pre-existing test suite you did not just generate — use ai-qa-review (Step 7 here only reviews tests THIS pipeline produced). Related: playwright-automation, unit-testing, api-testing, qa-project-context.
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。
Test native, React Native, hybrid, and Flutter mobile apps with Appium 3.x, Detox, Maestro, and Patrol. Covers device farm setup (BrowserStack, Sauce Labs), gesture simulation, deep link and cold-start testing, push notifications, biometric (Face ID) auth, offline/poor-network simulation, and iOS/Android permission dialog handling. Use when: "mobile test," "Appium," "Detox," "Maestro," "Patrol," "Flutter test," "iOS test," "Android test," "device farm," "deep link," "biometric," "Face ID," "permission dialog," "React Native test." Not for: device/browser matrix strategy in the abstract — use cross-browser-testing; app startup/memory/battery profiling depth — use performance-testing; mobile screenshot diffing — use visual-testing. Related: ci-cd-integration, cross-browser-testing, performance-testing, test-data-management, test-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。
Bulk-regenerate broken test selectors after a UI refactor or redesign. Detects drift between old and new DOM with an aria-snapshot diff, maps old locators to new equivalents using role-first + region scoping, validates against the new build, and produces a single PR with grouped per-file selector updates and per-change evidence. Assumes Playwright >= 1.50 (trace viewer DOM-snapshot panel, getByRole filtering, ariaSnapshot). Use when: "UI refactor broke tests," "redesign broke tests," "bulk update selectors," "regenerate selectors after refactor," "selector drift," "fix N broken tests after redesign." Not for: healing one flaky test at runtime — use test-reliability. Not for: writing a new test suite from scratch — use playwright-automation. Not for: re-recording tests after a framework switch (Selenium to Playwright) — use test-migration. Related: test-reliability, playwright-automation, test-migration, ci-cd-integration, visual-testing.
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 and upgrade MetaX model support against a target vLLM revision and installed MACA components, recursively including model-dependent attention and kernels. Establish quantization and cache differences, preserve upstream structure, and distinguish shared upstream bugs from adaptation defects. Use for model support work, not standalone monkey-patch or registry audits.
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。