4.3천건 · 관련도순
Maintain Remotion’s expert listings, portraits, and generated cards, then regenerate the homepage animation with transparency. The workflow covers separate Chrome and Safari video formats and checks that matching assets stay consistent across both homepage consumers.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build and train Mixture of Experts models, which activate selected specialist networks for each input. Use DeepSpeed or HuggingFace workflows to configure routing, balance workloads, distribute experts across GPUs, and optimize inference.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Review CSS custom properties, often called CSS variables, used in animations and transitions. Add @property registrations with value types, initial values, and inheritance settings to support smooth changes and validate assigned values.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Find professionals with relevant experience and request a written or voice answer, or a short call, through Instant Expert. Use it for customer discovery and practical advice, with a free simulated test mode to try the process.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Train Mixture of Experts models, which activate selected specialist networks for each input. The skill guides architecture, input routing, workload balancing, and GPU distribution using DeepSpeed or HuggingFace, with examples for training configuration and inference optimization.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
MSBuild property definition patterns: conditional defaults, composition/concatenation, path normalization, trailing slash handling, TFM detection helpers, and property evaluation order. Only activate in MSBuild/.NET build context. USE FOR: diagnosing and fixing MSBuild property definition issues in .props or .csproj files, reviewing and fixing shared property configuration anti-patterns, fixing DefineConstants or NoWarn being overwritten instead of appended, fixing unconditional property assignments that prevent project-level overrides, fixing unquoted conditions that fail when properties are empty, fixing hardcoded paths that break cross-platform builds, setting property defaults that can be overridden, understanding property evaluation order and last-write-wins semantics. DO NOT USE FOR: props vs targets placement (use directory-build-organization), item operations (use item-management), target structure (use target-authoring), general anti-patterns (use msbuild-antipatterns), non-MSBuild build systems.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Add a person to the Remotion experts page by placing their portrait, entering their profile and contact links, and generating an expert card image. The instructions specify file locations, profile fields, and how to verify card generation.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Writes, reviews, and debugs property-based tests, which generate inputs to check general rules. Helps test conversions, parsers, normalization, and state invariants, assess whether existing assertions are meaningful, and distinguish faulty rules from implementation bugs.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Diagnose and fix MSBuild property problems, including overwritten settings, ineffective conditions, and environment-dependent paths. Review defaults, list appending, and evaluation order so project files and shared build settings retain the intended values.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Use this skill to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation. **Trigger when user asks to:** - Migrate or convert PostgreSQL tables to hypertables - Execute hypertable migration with minimal downtime - Plan blue-green migration for large tables - Validate hypertable migration success - Configure compression after migration **Prerequisites:** Tables already identified as candidates (use find-hypertable-candidates first if needed) **Keywords:** migrate to hypertable, convert table, Timescale, TimescaleDB, blue-green migration, in-place conversion, create_hypertable, migration validation, compression setup Step-by-step migration planning including: partition column selection, chunk interval calculation, PK/constraint handling, migration execution (in-place vs blue-green), and performance validation queries.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analyzes single-cell pooled CRISPR screens (Perturb-seq, CROP-seq, Perturb-CITE-seq, ECCITE-seq, multiome) where each cell carries an sgRNA and a scRNA-seq / surface-protein / chromatin readout. Covers experimental design (direct-capture Perturb-seq Dixit 2016 vs CROP-seq 3'UTR-barcoded Datlinger 2017 vs ECCITE-seq vs Multiome), MOI for sgRNA assignment, escaper-cell filtering (Mixscape, Papalexi 2021), SCEPTRE NB GLM + permutation for low-MOI (Barry 2024 Genome Biol 25:124), the Pertpy framework, factor decomposition, genome-scale Perturb-seq (Replogle 2022 Cell, 2.5M cells), and per-perturbation single-cell DE. Use when running a single-cell CRISPR screen, choosing direct-capture vs CROP-seq architecture, filtering escaper cells, performing single-cell DE, integrating Perturb-seq with pathway analysis, scaling to GW CRISPRi via Replogle protocol, or analyzing multi-omics screens.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Provides patterns for unit testing `@ConfigurationProperties` classes with `@ConfigurationPropertiesTest`. Validates property binding, tests validation constraints, verifies default values, checks type conversions, and mocks property sources for Spring Boot configuration properties. Use when testing application configuration binding, validating YAML or application.properties files, verifying environment-specific settings, or testing nested property structures.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analyzes single-cell pooled CRISPR screens (Perturb-seq, CROP-seq, Perturb-CITE-seq, ECCITE-seq, multiome) where each cell carries an sgRNA and a scRNA-seq / surface-protein / chromatin readout. Covers experimental design (direct-capture Perturb-seq Dixit 2016 vs CROP-seq 3'UTR-barcoded Datlinger 2017 vs ECCITE-seq vs Multiome), MOI for sgRNA assignment, escaper-cell filtering (Mixscape, Papalexi 2021), SCEPTRE NB GLM + permutation for low-MOI (Barry 2024 Genome Biol 25:124), the Pertpy framework, factor decomposition, genome-scale Perturb-seq (Replogle 2022 Cell, 2.5M cells), and per-perturbation single-cell DE. Use when running a single-cell CRISPR screen, choosing direct-capture vs CROP-seq architecture, filtering escaper cells, performing single-cell DE, integrating Perturb-seq with pathway analysis, scaling to GW CRISPRi via Replogle protocol, or analyzing multi-omics screens.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analyzes single-cell pooled CRISPR screens (Perturb-seq, CROP-seq, Perturb-CITE-seq, ECCITE-seq, multiome) where each cell carries an sgRNA and a scRNA-seq / surface-protein / chromatin readout. Covers experimental design (direct-capture Perturb-seq Dixit 2016 vs CROP-seq 3'UTR-barcoded Datlinger 2017 vs ECCITE-seq vs Multiome), MOI for sgRNA assignment, escaper-cell filtering (Mixscape, Papalexi 2021), SCEPTRE NB GLM + permutation for low-MOI (Barry 2024 Genome Biol 25:124), the Pertpy framework, factor decomposition, genome-scale Perturb-seq (Replogle 2022 Cell, 2.5M cells), and per-perturbation single-cell DE. Use when running a single-cell CRISPR screen, choosing direct-capture vs CROP-seq architecture, filtering escaper cells, performing single-cell DE, integrating Perturb-seq with pathway analysis, scaling to GW CRISPRi via Replogle protocol, or analyzing multi-omics screens.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analyzes single-cell pooled CRISPR screens (Perturb-seq, CROP-seq, Perturb-CITE-seq, ECCITE-seq, multiome) where each cell carries an sgRNA and a scRNA-seq / surface-protein / chromatin readout. Covers experimental design (direct-capture Perturb-seq Dixit 2016 vs CROP-seq 3'UTR-barcoded Datlinger 2017 vs ECCITE-seq vs Multiome), MOI for sgRNA assignment, escaper-cell filtering (Mixscape, Papalexi 2021), SCEPTRE NB GLM + permutation for low-MOI (Barry 2024 Genome Biol 25:124), the Pertpy framework, factor decomposition, genome-scale Perturb-seq (Replogle 2022 Cell, 2.5M cells), and per-perturbation single-cell DE. Use when running a single-cell CRISPR screen, choosing direct-capture vs CROP-seq architecture, filtering escaper cells, performing single-cell DE, integrating Perturb-seq with pathway analysis, scaling to GW CRISPRi via Replogle protocol, or analyzing multi-omics screens.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
조사한 매매·임대 매물을 사진, 가격, 편의 시설, 확인 사항, 출처가 담긴 카드로 정리하여 Hermes 데스크톱 대화에서 후보를 비교할 수 있게 합니다.
Retrieve Airbnb property details from a numeric listing ID, including descriptions, amenities, photos, location, house rules, ratings, and bedroom arrangements. Gather structured information for reviewing accommodation options, with dates required for nightly pricing.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Diagnose and fix concrete MSBuild property defects in projects and existing shared-file hierarchies. USE FOR: conditions, defaults, append versus overwrite, last-write-wins values, OS/TFM checks, portable paths, normalization, and reviews centered on those property defects. Property defects in Directory.Build.* remain in scope, including overwritten values across parent/child imports and conditions that run before TargetFramework is set, even when the fix changes import order or moves a property group to .targets. DO NOT USE FOR: placement-only or import-only requests with no concrete property defect, such as discovering shared files or choosing which file owns a target or customization (use directory-build-organization); item operations; target structure; broad reviews without a concrete property defect; non-MSBuild work.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert guide for property-based testing (fast-check, Hypothesis) and mutation testing (Stryker, mutmut) — AI-generated test properties, invariant discovery, mutation score optimization, and test suite quality verification / Panduan ahli property-based testing (fast-check, Hypothesis) dan mutation testing (Stryker, mutmut) — properti tes yang dihasilkan AI, penemuan invarian, optimasi skor mutasi, dan verifikasi kualitas suite tes.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
デジタルプロダクト系の専門領域（UI/UX, マーケティング, コピーライティング, ASO, グロース等）の 暗黙知を抽出・言語化・構造化し、他のSkillで使えるエージェント定義と評価基準を生成するスキル。 素人では判断できない「良い/悪い」の基準を、AI が専門家レベルで調査・分析・言語化し、 再利用可能なドメインナレッジとして出力する。 Use when: 評価基準を作りたい、ドメイン知識を抽出したい、専門家の視点を言語化したい、 暗黙知を構造化したい、ベストプラクティスを整理したい。 Triggers: "ドメイン知識", "専門知識", "評価基準", "domain expertise", "expertise extract", "知識抽出", "暗黙知", "ベストプラクティス抽出", "評価基準を作りたい", "専門家の視点", "ドメインナレッジ", "domain knowledge", "expertise builder"
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Automate Google Analytics administration through its Admin API. Manage accounts, properties, data streams, custom dimensions for additional analysis fields, event settings, and product links, with guidance on authentication and official client libraries.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Strengthen existing tests with fast-check by checking properties across generated inputs. Find bugs that example tests miss and reduce failing inputs to small, reproducible cases. Property testing is available; the other listed workflows remain planned.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Convert English-language properties in PROPERTIES.md (produced by the Fizz skill) into Solidity assertions inside the existing fuzz harness, then flip their checkboxes. Trigger on "fizz-convert", "convert properties", "implement properties from PROPERTIES.md", "convert PROPERTIES.md to Solidity".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Simulate transcription factor perturbation effects on cell state in silico with CellOracle and Dynamo, and predict transcriptional responses to genetic perturbations with GEARS, scGen, and CPA. Covers the direction-not-magnitude principle, local-linear validity, the GRN/velocity error it inherits, baseline discipline (mean and additive baselines), and the validation gap. Use when predicting TF knockout or overexpression effects, ranking driver TFs for fate transitions, or planning perturbation experiments. For GRN construction see multiomics-grn; for experimental Perturb-seq see single-cell/perturb-seq.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.