「performing」の検索結果

Identify and report code smells indicating poor design or maintainability issues in Python code, including duplicate code, magic numbers, hardcoded values, God classes, feature envy, inappropriate intimacy, data clumps, primitive obsession, and long parameter lists. Use when conducting code quality audits, preparing for refactoring, improving codebase maintainability, or performing design reviews. Produces markdown reports with severity ratings, locations, descriptions, and specific refactoring recommendations with before/after examples. Triggers when users ask to find code smells, identify design issues, suggest refactorings, improve code quality, or detect maintainability problems.

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 this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

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。

Click, type, hover, scroll and more with TestDriver

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。

Perform actions and handle dynamic, async UI so tests adapt to change

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 WooCommerce code changes for coding standards compliance. Use when reviewing code locally, performing automated PR reviews, or checking code quality in WooCommerce projects.

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。

Reconcile accounts by comparing GL balances to subledgers, bank statements, or third-party data. Use when performing bank reconciliations, GL-to-subledger recs, intercompany reconciliations, or identifying and categorizing reconciling items.

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。

Perform differential expression analysis using edgeR in R/Bioconductor. Use for analyzing RNA-seq count data with the quasi-likelihood F-test framework, creating DGEList objects, normalization, dispersion estimation, and statistical testing. Use when performing DE analysis with edgeR.

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。

Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda window scheduling, soft-core potentials, REST2 enhanced sampling, MBAR/BAR analysis, and cycle closure validation. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.

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。

Perform differential expression analysis using DESeq2 in R/Bioconductor. Use for analyzing RNA-seq count data, creating DESeqDataSet objects, running the DESeq workflow, and extracting results with log fold change shrinkage. Use when performing DE analysis with DESeq2.

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 clinical trial analysis workflow from CDISC SDTM/ADaM loading through ICH E9(R1) estimand-driven primary analysis to CONSORT 2025 regulatory-compliant reporting. Covers data preparation, FDA 2023 marginal vs conditional logistic regression, categorical tests with Boschloo, modern HTE/subgroup methods, missing-data sensitivity (MMRM, reference-based MI, Permutt tipping point), graphical multiplicity (Bretz-Maurer), survival analysis (Cox/RMST/competing risks) when applicable, and Table 1. Use when performing a complete analysis of clinical trial 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。

Dimensionality reduction and clustering for single-cell RNA-seq using Seurat (R) and Scanpy (Python). Use for running PCA, computing neighbors, clustering with Leiden/Louvain algorithms, generating UMAP/tSNE embeddings, and visualizing clusters. Use when performing dimensionality reduction and clustering on single-cell 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。

Reconstruct ancestral states at internal phylogenetic nodes for sequences (PAML codeml, IQ-TREE --ancestral, GRASP, FastML), discrete traits (corHMM hidden-rate Markov, ape::ace, phytools::make.simmap stochastic mapping, BayesTraits), and continuous traits (phytools::fastAnc, geiger Brownian/OU, RPANDA). Use when designing constructs for ancestral protein resurrection, tracing trait evolution along a tree, performing stochastic character mapping, testing models of trait evolution (BM vs OU vs EB), inferring ancestral genome content via Dollo or DTL reconciliation, or quantifying ancestral-state uncertainty for downstream comparative analyses.

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。

CesiumJS spatial math - Cartesian3, Cartographic, Matrix4, Quaternion, Transforms, Ellipsoid, BoundingSphere, projections, coordinate conversions. Use when converting between coordinate systems, computing positions on the ellipsoid, performing spatial intersection tests, building model matrices, or working with geographic projections.

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 has a Xiaohongshu niche and needs to find, compare, and extract reusable content structures from low-follower high-performing posts, or diagnose why a post did or did not become a breakout using click rate, retention, and interaction signals. Trigger phrases: "找对标", "低粉爆款", "拆爆款", "内容骨架", "点击率", "停留时长", "互动率", "competitor pattern", "viral post structure". Do not use before the monetization direction is clear.

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 has a Xiaohongshu niche and needs to find, compare, and extract reusable content structures from low-follower high-performing posts, or diagnose why a post did or did not become a breakout using click rate, retention, and interaction signals. Trigger phrases: "找对标", "低粉爆款", "拆爆款", "内容骨架", "点击率", "停留时长", "互动率", "competitor pattern", "viral post structure". Do not use before the monetization direction is clear.

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。

World-class explainer video expertise combining the visual storytelling of Kurzgesagt, the simplification genius of Common Craft, and the conversion science of high-performing SaaS landing pages. Explainer videos transform complex ideas into clear, compelling stories. Great explainers don't just inform—they illuminate. They take abstract concepts and make them feel obvious. The best explainer videos understand that simplicity is the ultimate sophistication, that showing beats telling, and that the goal isn't to impress with complexity—it's to make the viewer feel smart. Use when "explainer, explainer video, how it works, product demo, onboarding video, training video, educational video, whiteboard, animated explainer, explain this, simplify, concept video, SaaS video, explainer, video, animation, educational, product, demo, onboarding, SaaS" mentioned.

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。

World-class expertise in measuring, attributing, and optimizing AI-generated content performance. Combining data science rigor with content strategy intelligence to answer the questions traditional content analytics can't: Is AI content performing? Which AI variations convert? What's the true ROI of AI vs traditional content creation? This isn't vanity metrics for robots. This is the discipline of proving AI content drives business outcomes - and using that data to make AI content systems better, faster, and more profitable. Built on the principles of companies like Jasper, Copy.ai, and Notion who've scaled AI content operations with measurement as the foundation. Use when "ai content performance, ai content analytics, measure ai content, ai content roi, ai vs human content, ai content attribution, ai content testing, ai variation testing, ai content dashboard, ai content metrics, prompt performance, ai content conversion, ai content quality score, content velocity, ai content efficiency, ai-content, analytics, measurement, attribution, roi, ab-testing, performance, optimization, data-driven, content-analytics" mentioned.

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。

Systematic analysis of Google Ads and Meta advertising spend to identify wasted budget. Produces actionable exclusion lists with thematic categorization and statistical validation. Use when onboarding new accounts, performing monthly hygiene, or preparing for budget optimization.

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 a 3-month SEO performance HTML report for any domain using DataForSEO data. Fetches baseline vs current traffic, keyword rankings, top content pages, and competitive landscape, then outputs a report styled with the Infrasity brand design system: #0D0A1A background, #8157F2 purple accent, Instrument Sans + DM Sans + DM Mono typography. Use this skill whenever a user provides a target domain and a list of competitor URLs and asks for an SEO report, performance report, SEO analysis, competitive SEO comparison, traffic report, ranking report, or 3-month SEO summary. Also trigger when the user says "generate SEO report for X vs Y and Z", "create a performance report", "compare my SEO against competitors", or pastes a domain and asks how it's performing versus the market. Always use this skill for SEO report generation — do not attempt to build the report without following this structured data-fetch and HTML generation workflow.

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。

DC power flow analysis for power systems. Use when computing power flows using DC approximation, building susceptance matrices, calculating line flows and loading percentages, or performing sensitivity analysis on transmission networks.

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 this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of "Word doc", "word document", ".docx", or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a "report", "memo", "letter", "template", or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

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。

Extract locational marginal prices (LMPs) from DC-OPF solutions using dual values. Use when computing nodal electricity prices, reserve clearing prices, or performing price impact 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。

Comprehensive competitor analysis, competitive intelligence, and comparison page creation. Use when analyzing competitive landscape, creating competitor comparison pages (alternative pages, vs pages, competitor A vs B pages), performing market research, building SWOT analysis, creating feature matrices, pricing comparisons, competitor teardowns, battle cards, or positioning maps. Covers research workflows, SEO-optimized comparison content, data-grounded reports with citations, 7-layer analysis framework, review mining, and sales enablement. Triggers include competitor analysis, competitive analysis, competitor teardown, vs page, alternative page, competitor comparison, market research, competitive intelligence, SWOT analysis, battle card, competitor pricing, market landscape, feature comparison, positioning map.

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 high-performing ad creatives across Instagram, Facebook, TikTok, LinkedIn, Google (Display / Demand Gen), YouTube, Pinterest, and X/Twitter — locking platform dimensions, safe zones, text overlay policy, character limits, industry visual DNA, ad objective hierarchy, composition patterns, CTA strategy, and prompt sanitation. Use when the user says "create an ad", "design an ad creative", "make an ad", "广告创意", "帮我做个广告图", "Instagram ad", "TikTok ad", "Facebook ad", "Google Display ad", "LinkedIn ad", "YouTube ad", "Pinterest ad", "promotional image", "campaign creative", "ad banner", "投放图", or any platform-specific ad request. Routed from `product-shots` when `asset_type == "ad"` or `is_promotion == True`.

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。