「linking」の検索結果

Use this skill when configuring or troubleshooting Data Cloud identity resolution rulesets — matching rules, reconciliation rules, unified profiles, and cross-device identity linking. Trigger keywords: identity resolution ruleset, unified individual, match rule, reconciliation rule, unified profile, cross-device identity, Data Cloud deduplication, cluster creation. NOT for CRM duplicate and matching rules — use admin/duplicate-management. NOT for overall Data Cloud layer and activation design — use architect/data-cloud-architecture.

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Use this skill to configure a Salesforce B2B Commerce storefront: creating the WebStore, linking BuyerGroups, assigning CommerceEntitlementPolicies, and granting buyer contacts transactional access. Trigger keywords: B2B Commerce, WebStore, BuyerGroup, entitlement policy, buyer account, storefront access. NOT for building the product catalog, categories, or variants — use admin/commerce-product-catalog. NOT for a B2C Commerce (SFCC) storefront — use admin/b2c-commerce-store-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。

Firmware development for the ProMicro nRF52840 (V1940) — the nice!nano v2 compatible clone also sold as SuperMini nRF52840, nRF52840 Pro Micro or nRFMicro (nRF52840 QIAA, Cortex-M4F @ 64 MHz, 1 MB flash / 256 KB RAM, BLE 5 + 802.15.4, native USB, Adafruit UF2 bootloader with SoftDevice S140). Covers the PlatformIO + Adafruit nRF52 Arduino setup for a board that ships in neither, the vendored board definition and Pro Micro pin map, USB CDC via TinyUSB, Bluefruit BLE, the 32.768 kHz crystal that clones omit, SAADC pins, NFC pins as GPIO, and Zephyr's promicro_nrf52840 board target. Use when working on this board or any nice!nano v2 / ZMK keyboard controller: project setup, platformio.ini, pin mapping, LED not blinking, double-tap RESET and UF2/DFU flashing, SoftDevice version mismatches, a board that enumerates but never runs, or debugging why something on the board does not work.

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Structured Zettelkasten workflow for AMD — observe, draft, enrich, retrieve, decide, preview, write, verify. Produces high-quality atomic knowledge cards with deliberate linking.

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。

Create conventional commit messages for {{engine_name}} projects by analyzing staged changes. Handles engine-specific concerns like companion file pairing, binary assets, and linking the related plan. ALWAYS use this skill when the user asks to commit, save changes, or create a commit. Trigger phrases include "commit", "create commit", "commit this", "save changes", "save my work". Even if the user simply says "commit" or asks you to commit after finishing a task — invoke this skill, do NOT commit manually via git.

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 novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.

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 enhancer-driven gene regulatory networks (eGRNs) by integrating single-cell RNA-seq and ATAC-seq using SCENIC+, CellOracle base GRNs, Pando, FigR, DIRECT-NET, TRIPOD, and scMEGA. Covers the accessibility-defines-enhancers principle, peak-to-gene linking and its cell-composition confound, the paired-vs-unpaired decision, and TF-region-gene eRegulon triplets. Use when analyzing 10x multiome or paired/unpaired scRNA+scATAC to infer cis-regulatory GRNs. For RNA-only regulons see scenic-regulons; for in silico TF perturbation see perturbation-simulation.

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Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.

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Profiles RNA-binding protein targets without antibody or UV crosslinking using STAMP (APOBEC1-RBP fusion, C-to-U editing), scSTAMP (single-cell), TRIBE/HyperTRIBE (ADAR-RBP, A-to-I editing), DART-seq (APOBEC1-YTH for m6A), or Bullseye/SAILOR edit-site detection pipelines. Use when antibody is unavailable or specificity is doubtful, when single-cell RBP profiling is needed (scSTAMP), or when in vivo RBP profiling without UV is preferred.

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Infer cis-regulatory connections (peak-to-peak co-accessibility) from scATAC-seq using Cicero, ArchR getCoAccessibility, or SCENIC+. Use when linking enhancer accessibility to promoter accessibility, identifying enhancer-gene pairs from chromatin alone (without paired RNA), running gene-regulatory inference combining ATAC + RNA, or comparing predicted regulatory contacts against Hi-C/Micro-C ground truth.

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 says "check Jira", "create ticket", "update issue", or needs JQL queries, ticket transitions, or branch-to-ticket linking.

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Tiefe Pflegerunde für ein veröffentlichtes GitHub-Repository (Stufe 2): enthält den vollständigen surface-after-care-Durchlauf und ergänzt ihn um drei teure Schritte — rechtliche Ersteinschätzung über die Law-Checker mit Wiedervorlage nach einem Jahr (Gutachten bleibt gitignored im Repo), Querverweise zu verwandten Repos über ALLE Organisationen hinweg sowie das Nachziehen aller Sprachen auf App-Ebene, nicht nur in der Doku. Nutze diesen Skill bei "full after care", "deep after care", "tiefe Repo-Pflege", "große Runde", "Repo grundlegend durchgehen", wenn ein Repo länger nicht geprüft wurde, vor größeren Releases oder wenn rechtliche Relevanz, Querverweise oder Mehrsprachigkeit ausdrücklich Thema sind. Für die günstige, oft wiederholte Runde stattdessen surface-after-care; für die Erstveröffentlichung github-repo-care.

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Takes existing content markdown files and builds production-final resource center pages on client websites using their existing tech stack and design system. Output is live-ready — no review pass, no placeholder content, no prototype styling. Implements hub pages, section listings, article pages, and cross-linking for Blog, Guides, Learn, and Comparisons sections.

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 scalable SEO page systems using templates, structured data sources, quality thresholds, internal linking, indexation controls and anti-thin-content gates.

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。

Knowledge graph and smart memory management using graphify + Obsidian-inspired patterns. Use when: setting up a knowledge graph, managing memory health, cross-linking notes, compiling wiki pages from scattered notes, adding structured frontmatter, or running memory health checks. Triggers on: 'knowledge graph', 'graphify', 'wiki', 'cross-link', 'memory health', 'frontmatter', 'compile notes', 'wikilinks'.

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。

Create and manage Netlify deploys — Git continuous deployment, CLI manual/anonymous deploys, Deploy to Netlify buttons, drag-and-drop, and per-context netlify.toml build settings. Use when linking a repo, deploying from the CLI, setting up Deploy Previews or branch deploys, configuring deploy contexts, adding skew protection, fixing a failed or secrets-flagged deploy, or wiring build hooks and Deploy to Netlify buttons.

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Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.

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。

Implement SwiftUI navigation patterns including NavigationStack, NavigationSplitView, sheet presentation, tab-based navigation, and deep linking. Use when building push navigation, programmatic routing, multi-column layouts, modal sheets, tab bars, universal links, or custom URL scheme handling.

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Expert patterns for Plaid API integration including Link token flows, transactions sync, identity verification, Auth for ACH, balance checks, webhook handling, and fintech compliance best practices. Use when: plaid, bank account linking, bank connection, ach, account aggregation.

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Transforms conversations and discussions into structured documentation pages in Notion. Captures insights, decisions, and knowledge from chat context, formats appropriately, and saves to wikis or databases with proper organization and linking for easy discovery.

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 novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.

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。

De novo molecule generation for drug discovery. Scaffold-based analog enumeration, fragment growing/linking, structure-based design, multi-objective optimization, and drug-likeness filtering.

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 enhancer-driven gene regulatory networks (eGRNs) by integrating single-cell RNA-seq and ATAC-seq using SCENIC+, CellOracle base GRNs, Pando, FigR, DIRECT-NET, TRIPOD, and scMEGA. Covers the accessibility-defines-enhancers principle, peak-to-gene linking and its cell-composition confound, the paired-vs-unpaired decision, and TF-region-gene eRegulon triplets. Use when analyzing 10x multiome or paired/unpaired scRNA+scATAC to infer cis-regulatory GRNs. For RNA-only regulons see scenic-regulons; for in silico TF perturbation see perturbation-simulation.

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。

Query and download from NCBI Gene Expression Omnibus (GEO) and EMBL-EBI's BioStudies/ArrayExpress mirror. Use when finding expression datasets, navigating SuperSeries vs SubSeries, choosing between series-matrix (submitter-normalized) and raw supplementary files, downloading via GEOparse (Python) or GEOquery (R/Bioconductor), linking GEO to SRA for raw reads, or distinguishing GSE/GSM/GPL/GDS record types. Encodes the SuperSeries trap, the series-matrix normalization-trust caveat, GEOmetadb deprecation, ArrayExpress migration to BioStudies, and processed-vs-raw decision matrix.

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。