1,138 件 ・ 関連度順
概要と使いどころ
Differential abundance testing for microbiome data using compositionally-aware methods like ALDEx2, ANCOM-BC2, and MaAsLin2. Use when identifying taxa that differ between experimental groups while accounting for the compositional nature of microbiome 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。
Differentially methylated region (DMR) detection using methylKit tiles, bsseq BSmooth, and DMRcate. Use when identifying contiguous genomic regions with methylation differences between experimental conditions or cell types.
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。
Design pegRNAs for prime editing using PrimeDesign algorithms. Generate spacer, PBS, and RT template sequences for precise genomic modifications without double-strand breaks. Use when designing prime editing experiments for precise insertions, deletions, or point mutations.
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。
JACKS (Joint Analysis of CRISPR/Cas9 Knockout Screens) for modeling sgRNA efficacy and gene essentiality. Use when analyzing multiple CRISPR screens simultaneously or when accounting for variable sgRNA efficiency across experiments.
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。
CRISPResso2 for analyzing CRISPR gene editing outcomes. Quantifies indels, HDR efficiency, and generates comprehensive editing reports. Use when analyzing amplicon sequencing data from CRISPR editing experiments to assess editing efficiency.
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。
Design guides for cytosine and adenine base editing using editing window optimization and BE-Hive outcome prediction. Select optimal positions for C-to-T or A-to-G conversions without double-strand breaks. Use when designing base editor experiments for precise nucleotide 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。
Find differentially accessible chromatin regions between conditions using DiffBind or DESeq2. Use when comparing chromatin accessibility between treatment groups, cell types, or developmental stages in ATAC-seq experiments.
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。
This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.
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 quality control metrics including FRiP (Fraction of Reads in Peaks), cross-correlation analysis (NSC/RSC), library complexity, and IDR (Irreproducibility Discovery Rate) for replicate concordance. Use to assess experiment quality before downstream analysis. Use when assessing ChIP-seq data quality metrics.
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。
End-to-end binder design using BindCraft hallucination. Use this skill when: (1) Designing protein binders with built-in AF2 validation, (2) Running production-quality binder campaigns, (3) Using different design protocols (fast, default, slow), (4) Need joint backbone and sequence optimization, (5) Want high experimental success rate. For backbone-only generation, use rfdiffusion. For QC thresholds, use protein-qc. For tool selection guidance, use binder-design.
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 falsifiable trade strategy hypotheses from market data, trade logs, and journal snippets. Use when you have a structured input bundle and want ranked hypothesis cards with experiment designs, kill criteria, and optional strategy.yaml export compatible with edge-finder-candidate/v1.
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。
Goal-directed research missions that interleave web research with data experimentation and end on a structured best-effort verdict
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 when the user asks to "generate subject line variants", "pre-score my subject lines", or "will this subject get truncated / trigger spam filters"; produces a labeled subject + preheader variant set and a per-variant heuristic pre-score card — spam-trigger flags, length/truncation across desktop + mobile, emoji-count, and the inbox preview render (from-name + subject + preheader) — before any test is run. Not for the body copy or CTA — use email-creative-builder; not for the A/B test design or significance read — use send-experiment-designer; not for the profile-weighted EQS or the S1/S2/N1/D1 vetoes — use email-quality-auditor. 邮件主题行生成/主题行预打分/截断与垃圾词检查
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 when the user asks to "write the email", "draft subject lines", or "build email creative"; produces the pre-click unit — subject-line variants + preheader, body copy, one clear CTA, and a plain-text alt — message-matched to the destination page and claims-ledger-aware. Not for pre-scoring or ranking subject-line variants (spam/truncation/render pre-score) — use subject-line-lab; not for scoring the email or computing EQS — use email-quality-auditor; not for the multi-step flow — use email-sequence-designer; not for the A/B test plan — use send-experiment-designer. 邮件文案/主题行/邮件创意
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 when the user asks to "design an email A/B test", "set up a multivariate subject/CTA test", "run a send-time test", "build a hold-out group", or "is this email result statistically and practically material?"; produces a falsifiable hypothesis, one-variable-per-cell matrix, sample-size/MDE/duration/power plan, and an effect/uncertainty read from own ESP data. Applies only a precommitted owner-approved action rule; the helper never chooses a business action. Not for EQS/vetoes or writing the email. 邮件AB测试设计/多变量测试/发送时间测试/留出组/显著性判定
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。
Design an A/B experiment — hypothesis, variants, primary metric, and sample size. Use when a change can be measured quantitatively at scale. For observing behaviour qualitatively, use `test-scenario`.
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。
Design unbiased survey instruments — question wording, scales, and sampling — to measure attitudes at scale. Use when you need quantitative breadth. For behavioural experiments, use `a-b-test-design` (prototyping-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。
Run repeated, measured Git experiments toward a numeric target; keep improvements and revert failures. Use for autonomous optimization or managing an autoresearch run, not one-shot edits.
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。
Runs and interprets AWS Resilience Hub v2 failure mode assessments. Covers starting assessments, understanding findings (severity, categories, recommendations), triaging by achievability, working with AI-generated service functions, and resolving findings. Applies when the user wants to run an assessment, review findings, or understand failure modes, or has a specific finding and asks how to resolve, remediate, or fix it. Does not apply to initial setup (use resilience-hub-getting-started) or FIS experiments.
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。
Configures AWS Application Recovery Controller (ARC) for operational resilience: routing controls with safety rules for cross-Region failover, and zonal shift / zonal autoshift for AZ-impairment recovery. Applies when setting up failover routing, configuring safety rules, enabling zonal shift, or configuring zonal autoshift with practice runs. Also applies when shifting traffic out of a specific Availability Zone (AZ) for an ALB/NLB or other resource. For a broader "an AZ is impaired, what is my response across services" question, see aws-resilience-lifecycle. Does not apply to Resilience Hub setup or FIS experiments.
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。
Sets up AWS Resilience Hub v2 from scratch: creates resilience policies with SLO targets, registers systems and user journeys, onboards services with input sources, and runs a first failure mode assessment. Applies when the user wants to get started with Resilience Hub v2, create a policy, onboard a service, or run an assessment — including creating one concrete policy with specific availability/RTO/RPO targets and a DR approach for a single service (even a tier-1 one). Does not apply to FIS experiments or ARC routing controls.
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。
Designs a resilience program: how to structure and standardize resilience policies across an organization, team, or portfolio (tiered policy model with availability/RTO/RPO targets and DR approach selection), and how often to run resilience activities (operational cadence). Applies when the user asks how to structure policies org-wide, what tiers/targets to set, which DR approach fits a tier, or how frequently to run assessments, FIS experiments, GameDays, or autoshift practice. Does not apply to creating or configuring a specific policy or resource for a single workload (use resilience-hub-getting-started), to step-by-step lifecycle execution (see aws-resilience-lifecycle), or to service-specific setup.
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。
Archive a completed OpenSpec change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete. Also use when the user says "openspec archive" or "opsx archive".
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。
Run and control a user's app on a remote iOS/Android simulator hosted on EAS cloud. Read before running any `eas simulator:*` commands - it has the current syntax for this experimental API. Use whenever the user needs a simulator they can't run locally - 'run my app on a cloud simulator', 'use eas simulator to run/install/screenshot my app', 'I'm on Linux/Cursor and need an iOS device', 'no sim on this box / headless CI', 'let an agent click through my app and screenshot it', 'test my dev build on a remote sim with live reload', 'stream a sim to my browser' - even when they don't say 'EAS Simulator' or 'cloud'. On a host WITHOUT a local simulator (Linux, CI, cloud sandbox) it's the default; on macOS, do NOT auto-trigger for a plain 'run on the simulator' - use it only for a cloud/remote/shareable sim, an iOS version they lack, or an agent-driven session. NOT for local sims (expo run:ios, Xcode, Android Studio), EAS Build/Update, web preview, or physical 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。