「structure」の検索結果

Web scraping with structured data extraction - define your output schema

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Extract structured data matching a JSON schema from websites. Handles complex nested schemas, arrays, pagination, and validation. Always outputs via formatOutput.

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Modern .NET project structure including .slnx solution format, Directory.Build.props, central package management, SourceLink, version management with RELEASE_NOTES.md, and SDK pinning with global.json.

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Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

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Estimates time-scaled phylogenies, molecular-clock rates, effective reproduction number R_e, and population dynamics from dated pathogen genomes using TreeTime (maximum-likelihood) and BEAST2 (Bayesian; strict/relaxed clocks; coalescent, Bayesian-Skyline, Skygrid, Birth-Death-Skyline, and sampled-ancestor priors; structured coalescent via MASCOT). Covers root-to-tip clock QC via TempEst, date-randomisation tests, recombination masking via Gubbins/ClonalFrameML before clock inference for recombining bacteria, BDSKY origin-vs-rootHeight pitfalls, sampling-bias correction, multi-chain convergence diagnostics, and reconciling phylodynamic R_e with case-based R_t. Use when dating outbreak origins, estimating substitution rates, inferring R_e through time, building time-calibrated Nextstrain Augur trees, choosing between strict and relaxed clocks, fitting Birth-Death-Skyline models, diagnosing temporal-signal failure, running MASCOT for structured-population analyses, or using UShER for pandemic-scale placement.

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Detect distant homologs using profile and structure-aware methods that go beyond standard BLAST. Use when sequence identity falls into the twilight zone (<35% pairwise), when BLAST fails to find homologs that should exist, when working at metagenomic scale (DIAMOND, MMseqs2), or when structure beats sequence (Foldseek). Covers PSI-BLAST (iterative PSSM), jackhmmer (iterative HMM), HHblits/HHsearch (profile-profile), DIAMOND, MMseqs2, and Foldseek (3Di structural alphabet, van Kempen 2024).

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Standardizes molecular structures using the ChEMBL structure pipeline for normalization and parent selection plus RDKit rdMolStandardize for explicit custom steps such as tautomer canonicalization, salt/solvent stripping, charge handling, stereochemistry handling, mixture selection, and isotope normalization. Explicitly compares ChEMBL, canSARchem, RDKit, and PubChem standardization choices. Use when preparing libraries for QSAR training, joining datasets across sources, deduplicating compound collections, or building canonical compound registries.

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Searches molecular libraries for substructure matches using SMARTS patterns with explicit handling of recursive SMARTS, ring membership, aromaticity dialect, vector binding, atom map indices, and reactive/PAINS/REOS/Brenk filter catalogs. Use when filtering compounds by pharmacophore features, functional groups, scaffold matches, or screening for assay-interference / structural alerts.

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Build custom PCB structures with pcbComponent, shapes, Boolean ops, feeds, and multi-layer stackups for non-catalog geometries. TRIGGER: user asks to build, modify, or customize a pcbComponent — add/remove shapes, edit polygons, place feeds, add metal layers, cut slots, or create non-catalog RF structures. Also when modifying geometry of an existing catalog-designed component (e.g., adding pads, removing elements, editing vertices). Invoke BEFORE writing pcbComponent code — layer/shape/feed API is non-obvious. SKIP: designing catalog components like filters/couplers/txlines (use the specific matlab-design-pcb-* skill), material/stackup definition only (use matlab-manage-pcb-material), EM analysis (use matlab-analyze-em), importing PCB files (use matlab-read-pcb-layout).

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Design and analyze electrically large antenna structures using MATLAB Antenna Toolbox. Covers reflector antennas (parabolic, Cassegrain, Gregorian, offset, corner, cylindrical, spherical, custom STL), reflectarrays and reconfigurable intelligent surfaces (RIS), antennas installed on platforms (vehicles, aircraft, ships, satellites), and radar cross section (RCS) analysis. Includes solver selection (MoM-PO, PO, MoM, FMM), mesh control, and GPU acceleration. Use when the user wants to design a dish/reflector antenna, reflectarray, analyze an antenna on a platform, or compute RCS.

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AWS CloudFormation infrastructure as code for stack management. Use when writing templates, deploying stacks, managing drift, troubleshooting deployments, or organizing infrastructure with nested stacks.

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Build and operate Retrieval-Augmented Generation (RAG) infrastructure with vector stores, embedding pipelines, and hybrid search. Covers ingestion, chunking strategies, reranking, and production deployment patterns.

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Write structured strategic documents for small and medium businesses: SWOT analyses, lean business plans, OKRs, competitive analyses. Each mode has a defined structure and quality bar. Use whenever a business asks to articulate strategy, set goals, analyse competition, plan for growth, do a SWOT, write OKRs, or build a lean business plan. Produces actionable documents, not generic frameworks.

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Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.

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Format reference for Power BI Enhanced Report (PBIR) JSON schemas and patterns. Automatically invoke when the user asks about PBIR JSON structure, visual.json properties, PBIR expressions, objects vs visualContainerObjects, theme inheritance, conditional formatting patterns, extension measures, bookmarks, field references, filter formatting, query roles, PBIR page structure, report wallpaper, or any PBIR metadata format question.

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When the user wants to decide domain structure for multiple products or brands—subfolder vs subdomain vs independent domain. Also use when the user mentions "subfolder vs subdomain," "subdirectory vs subdomain," "multiple products domain," "multiple websites," "brand architecture," "branded house," "house of brands," "where to host product," "domain structure," or "hub-spoke domain." For brand SERP, use multi-domain-brand-seo.

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When the user wants to plan, design, or optimize pricing strategy and structure. Also use when the user mentions "pricing strategy," "pricing model," "pricing tiers," "freemium," "value-based pricing," "anchoring," "price structure," or "monetization strategy." For pricing page, use pricing-page-generator.

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When the user wants to improve crawlability, fix orphan pages, or optimize site structure for search engines. Also use when the user mentions "crawlability," "crawl budget," "orphan pages," "internal links," "site structure," "site crawlability," "infinite scroll," "pagination," "masonry SEO," "AI crawler optimization," "GPTBot crawlability," "ClaudeBot crawlability," or "content not indexed." For internal links, use internal-links.

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When the user wants to optimize internal linking, fix orphan pages, or improve link structure. Also use when the user mentions "internal links," "internal linking," "anchor text," "link equity," "internal linking strategy," or "orphan pages." For IA, use website-structure.

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When the user wants to write or optimize H1-H6, fix heading hierarchy, improve content structure, rewrite an H1, or align headings with page intent. This skill owns actual heading changes; page-metadata may only check and report metadata-to-heading alignment.

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When the user wants to create, optimize, or validate URL slugs for content pages. Also use when the user mentions "URL slug," "URL path," "blog URL," "article URL," "short URL," "clean slug," "permalink," "slug optimization," "URL structure," "SEO-friendly URL," "create URL slug," or "SEO slug." For site-wide URL policy, use url-structure.

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Generate a single-file MCP App widget for an MCP tool, with either bundled runtime code or user-approved public CDN imports. Describe the visual and provide a plain structured payload or a full tool result with content, structuredContent, and meta.

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Patterns for individual long-form content pieces. Case studies, whitepapers, research reports, definitive guides, manifestos, ebooks, long-form tutorials. The structural disciplines that distinguish publication-quality long-form from bloggy-long padding or academic bloat. Different from pillar-content-architecture (which covers hub structure); this skill covers individual deep-dive pieces. Triggers on long-form content, case study writing, whitepaper, research report, definitive guide, ebook, manifesto, long-form tutorial, deep-dive article, anchor piece, foundational article, structural archetypes. Also triggers when a piece is over 3,000 words and the team is unsure how to structure it, when a long-form draft feels padded or saggy, or when a flagship asset needs the depth to actually earn the length.

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Optimize content and site structure for AI-driven search experiences including AI overviews, large language model citations, generative answer engines, and AI assistants. Use this skill whenever the user wants to optimize for AI search, get cited by language models, appear in AI overviews, build llms.txt, structure content for AI extraction, or future-proof their SEO for the shift from blue links to AI answers. Triggers on AEO, GEO, AI search, AI SEO, AI overview, generative search, LLM optimization, llms.txt, AI citation, ChatGPT search, Perplexity, Gemini, Claude search, AI assistant optimization, answer engine. Also triggers when the user expresses concern about AI eating their organic traffic or wants to understand how to remain visible as search shifts.

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。