4,894 件 ・ 関連度順
概要と使いどころ
DingTalk Workspace CLI (dws) - officially open-sourced cross-platform CLI tool from DingTalk. Provides 86 commands across 12 products: Contact, Chat, Bot, Calendar, Todo, Approval, Attendance, Ding, Report, AITable, Workbench, DevDoc. Built in Go with zero-trust security architecture. Use when user wants to operate DingTalk 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。
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。
Generates complete Mendelian randomization study designs from a user-provided exposure and outcome direction. Always use this skill whenever a user wants to design, plan, or build a Mendelian randomization study — even if phrased as "help me write a paper on X", "design an MR study for Y", or "I want to test whether A causally affects B using GWAS". Covers core two-sample MR design, optional bidirectional follow-up, optional multivariable MR, IV selection logic, ancestry alignment, harmonization, IVW as the default primary estimator, weighted median / MR-Egger / MR-PRESSO / leave-one-out sensitivity analyses, Steiger directionality, heterogeneity / pleiotropy checks, and explicit claim-boundary control. Always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, stepwise workflow, method rationale, validation ladder, figure plan, minimal executable version, and strictly verified literature guidance with no fabricated 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。
Generates complete dual-disease shared-transcriptome biomarker and hub-gene research designs from a user-provided disease pair and shared-biology direction. Always use this skill whenever a user wants to design, plan, or build a non-oncology two-disease transcriptome study centered on per-disease differential expression, shared-signal intersection or concordance, PPI-based hub-gene prioritization, diagnostic evaluation across both diseases, immune infiltration context, pathway interpretation, and optional orthogonal validation. Covers five study patterns (shared-DEG-first workflow, hub-gene-first shared-biomarker workflow, hybrid shared-biomarker compression workflow, immune-context shared-biomarker workflow, orthogonal 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。
Use when performing sample-level dimensionality reduction and visualization on abundance or OTU-style matrices with a companion group file, generating UMAP and/or t-SNE coordinates and plots for group separation assessment. NOT for: differential expression testing, single-cell workflows requiring dedicated embeddings pipelines, or analyses without a sample grouping file.
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 analyzing network packet captures (PCAP files) and computing network statistics using Python, with tested utility functions.
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。
Provide number theory algorithm implementations and guidance
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。
System and API design guidance covering component boundaries, data flow, integration patterns, and scalability considerations.
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 the user asks about "key startup metrics", "SaaS metrics", "CAC and LTV", "unit economics", "burn multiple", "rule of 40", "marketplace metrics", or requests guidance on tracking and optimizing business performance 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。
You are a compliance expert specializing in regulatory requirements for software systems including GDPR, HIPAA, SOC2, PCI-DSS, and other industry standards. Perform compliance audits and provide implementation guidance.
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。
Master Python 3.12+ with modern features, async programming, performance optimization, and production-ready practices. Expert in the latest Python ecosystem including uv, ruff, pydantic, and FastAPI. Use PROACTIVELY for Python development, optimization, or advanced Python 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 Haskell engineer specializing in advanced type systems, pure functional design, and high-reliability software. Use PROACTIVELY for type-level programming, concurrency, and architecture guidance.
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 high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2. Master microservices, WebSockets, and modern Python async patterns. Use PROACTIVELY for FastAPI development, async optimization, or API architecture.
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。
Plan incremental dependency upgrades with breaking-change analysis, migration guidance, and regression testing. Use when updating packages while controlling compatibility risk.
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。
You are an accessibility expert specializing in WCAG compliance, inclusive design, and assistive technology compatibility. Conduct audits, identify barriers, and provide remediation guidance.
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。
Clause-by-clause contract risk analysis with severity scoring, financial exposure estimates, and prioritized remediation guidance
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。
Writing plays and screenplays in the Chekhovian mode (契诃夫戏剧法) — distilled from the complete plays (没有父亲的人/普拉东诺夫, 伊凡诺夫, 林妖→万尼亚舅舅, 海鸥, 三姊妹, 樱桃园, nine one-acts) plus Chekhov's own letters, Stanislavsky's and Nemirovich-Danchenko's rehearsal notes and 焦菊隐/童道明 criticism. Covers the four-act mood-based structure without central climax, off-stage events, "correct answer stated in Act 1 and refused", the announced event that never happens, three-layer endings (hope monologue + nihilist line + household action), no-villain conflict with environment, every character's object and catchphrase, one-way love chains, half-step-off dialogue, philosophy cut by thirst, the shortest words for the deepest pain, stage-direction and sound discipline, and how Chekhov revised The Wood Demon into Uncle Vanya. Use when the user wants an ensemble drama, a "nothing happens" play, subtext-heavy dialogue, a family estate / provincial story, an anti-climactic structure, or asks how to "Chekhov-ize" a script.
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。
Pre-screen analysis outputs (tables, figures, logs) built on restricted or confidential data for statistical-disclosure-limitation problems before any release. Scans for small cell counts, complementary-suppression gaps, dominance (p-percent / (n,k)), re-identifiable exact counts, PII leakage, and unrounded sensitive statistics; classifies each finding CRITICAL / WARNING / OK and gates on any CRITICAL. Use before depositing or sharing restricted-data results, or when the user says "disclosure check", "SDL scan", "is this output safe to release", "check for small cells", "disclosure avoidance", "pre-screen for the RDC", or "can I export this from the enclave".
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 candidate learnings in Claude Code's native auto memory (`~/.claude/projects/<project>/memory/`, machine-local) and run them through a five-critic council in parallel: generality, staleness, redundancy, evidence, format. Majority vote (3+ of 5) promotes the entry to MEMORY.md. Use when user says "promote memory", "review my learnings", "what should graduate to MEMORY.md", "five-critic council", or as monthly memory maintenance.
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。
将参考图或简要描述解码为可编辑的半色调纸张拼贴规范，默认使用 Codex 内置 image_gen 生成品牌一致的静帧和透明图层，再用本地 FFmpeg 或 HyperFrames 制作“从空背景逐件组装”的确定性动态视频。用户提到半色调拼贴、纸张拼贴、剪纸拼贴、编辑式拼贴、杂志拼贴、复古印刷拼贴、拼贴动效、拼贴动画、剪纸动画、纸片组装、逐层组装、从无到有、元素飞入拼装、定格拼贴、定格动画、Arcads 风格、参考图拆解、风格拆解、反向拆解视觉、照这个风格做、做类似的、生成拼贴静帧、让这张图动起来、让这些元素组装起来、制作拼贴广告或拼贴解释视频时使用。英文触发语义包括 editorial collage、halftone collage、paper collage、paper-cut motion、stop-motion graphic、assemble from empty、build-on motion、analyze this、break this down、reverse-engineer this look、generate the stills、animate this、make these move。默认不调用 Arcads、Nano Banana、Seedance 或 Kling；只有用户明确要求且对应连接器可用时才进入外部生成路径。
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。
AI DevKit · Testing phase guidance for adding and validating feature test coverage. Use when the user wants to write tests, update testing docs, run coverage, close coverage gaps, or run dev-lifecycle phase 8.
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。
AI DevKit · Final code review phase guidance for holistic pre-push review. Use when the user wants code review, final lifecycle review, design alignment checks, integration risk review, or dev-lifecycle phase 9.
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。
AI DevKit · Worktree setup and resume guidance for isolated feature work. Use when starting, resuming, switching, or verifying a feature branch/worktree for lifecycle, debugging, implementation, review, or multi-agent workflows.
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。
AI DevKit · Requirements phase guidance for starting features and reviewing requirements. Use when the user wants to capture a new requirement, clarify product scope, initialize feature docs, review requirements, or run dev-lifecycle phases 1-2.
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。