「net」の検索結果

Annotate genetic variants (GWAS hits, eQTLs, rare variants) with ENCODE functional data to interpret non-coding variation. Use when the user has variants of interest and wants to understand their regulatory context, identify causal variants from GWAS loci, assess variant impact on regulatory elements, perform enrichment testing of variant sets in tissue-specific annotations, or link variants to target genes through enhancer-gene maps. Handles the full post-GWAS workflow from variant set → tissue mapping → functional annotation → fine-mapping awareness → enrichment → variant-to-gene → prioritization. Use this skill for ANY variant interpretation task involving ENCODE chromatin, accessibility, TF binding, or 3D genome data.

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Query gnomAD (Genome Aggregation Database) for population allele frequencies, gene constraint scores, and variant annotations to interpret ENCODE regulatory variants. Use when the user needs allele frequencies for variants in ENCODE regulatory elements, wants to assess gene constraint (pLI, LOEUF) for ENCODE target genes, needs population-specific frequencies for GWAS variants overlapping cCREs, wants to filter variants by rarity before functional annotation, or is interpreting ENCODE CRISPR/MPRA results in the context of population genetics. Also use when the user mentions gnomAD, allele frequency, pLI, LOEUF, constraint, rare variants, population frequency, ExAC, or variant filtering.

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Build comprehensive epigenomic profiles for tissues or cell types using ENCODE data. Use when the user wants to characterize chromatin states, assemble histone modification panels, create epigenomic landscapes, run ChromHMM segmentation, identify super-enhancers or bivalent domains, profile regulatory elements across a biosample, or understand epigenetic regulation in a specific biological context. Covers histone marks, chromatin accessibility, TF binding, transcription, DNA methylation, and 3D genome structure.

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Integrate multiple ENCODE data types (RNA-seq, ATAC-seq, Histone ChIP-seq, TF ChIP-seq) for a tissue/cell type to build a comprehensive regulatory landscape. Use when the user wants to answer "what are the enhancers, promoters, and regulatory elements active in my tissue, and which transcription factors control them?" by layering expression, chromatin accessibility, histone marks, and TF binding data. Follows the Mawla et al. 2023 framework for cross-assay integration of islet cell type-specific data. Handles chromatin state annotation (ChromHMM), enhancer-gene linkage, TF motif enrichment, and cell type-specific regulatory element identification. Use for ANY multi-omic analysis, enhancer discovery, regulatory network construction, or epigenomic characterization using ENCODE data.

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Spring Boot 4 observability with Actuator, Micrometer, and OpenTelemetry. Use when configuring health indicators, health checks, custom metrics, distributed tracing, production endpoint exposure, Kubernetes probes, Cloud Run probes, logging, or monitoring. Covers Actuator endpoint security, Micrometer Timer/Counter/Gauge patterns, OpenTelemetry span customization, liveness/readiness probe setup, and metric tag best practices.

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Craft high-quality natural-language image prompts for any modern text-to-image or image-edit model that accepts flowing English. Trigger when the user wants help writing, rewriting, improving, or translating an English natural-language image prompt — including "write me an image prompt", "improve this image prompt", "describe this scene for an image model", or "convert these tags into a natural language prompt". Do NOT trigger for requests that are purely about dispatching to an image API, choosing samplers/schedulers, picking LoRAs, or setting up ControlNet — those belong to a runtime skill.

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Comprehensive guide for building, configuring, customizing, and deploying Docsify documentation sites. Use when the user wants to (1) initialize a new Docsify site, (2) add or organize Markdown pages, sidebars, navbars, or cover pages, (3) configure `window.$docsify` options, (4) customize themes / CSS variables / fonts, (5) install built-in or third-party Docsify plugins (search, GA, emoji, zoom, copy-code, comments, pagination, tabs, etc.), (6) write a custom Docsify plugin using lifecycle hooks, (7) use Docsify Markdown helpers (callouts, link attributes, image attributes, heading IDs, task lists, embed files with `:include`), (8) deploy to GitHub Pages, GitLab Pages, Netlify, Vercel, Firebase, Docker, Nginx, etc., (9) enable PWA / offline mode, virtual routes, or Vue compatibility, or (10) upgrade a Docsify site from v4 to v5. Triggers on mentions of "docsify", "_sidebar.md", "_navbar.md", "_coverpage.md", "$docsify", or `docsify-cli`.

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Builds Flux manifests locally, diffs YAML files, patches FluxInstance upgrades, creates authentication secrets, traces GitOps delivery pipelines, and bootstraps clusters with the Flux Operator. Use this skill whenever the user mentions flux-operator, FluxInstance, FluxReport, ResourceSet, ResourceSetInputProvider, Flux CD operator management, or asks about GitOps CLI tooling for Kubernetes with Flux. Also trigger when users ask about building Flux manifests, diffing YAML, patching Flux instances, creating Flux secrets, tracing GitOps delivery pipelines, or bootstrapping clusters with Flux. Even if the user just says "flux operator" or "flux-operator cli" without details, this skill has the authoritative reference.

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Install and configure Tailscale across platforms. Detects OS, distro, and environment (including WSL2 and containers). Verifies existing installations, performs platform-appropriate install, and guides initial connection. Use when setting up Tailscale on a new machine, onboarding a server to a tailnet, or verifying an existing install.

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Deep learning framework development with tinygrad - a minimal tensor library with autograd, JIT compilation, and multi-device support. Use when writing neural networks, training models, implementing tensor operations, working with UOps/PatternMatcher for graph transformations, or contributing to tinygrad internals. Triggers on tinygrad imports, Tensor operations, nn modules, optimizer usage, schedule/codegen work, or device backends.

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Observes runtime behavior of binaries via QEMU emulation, GDB debugging, and Frida hooking — syscall tracing, breakpoints, memory inspection, and function interception. Use when running, tracing, or debugging a binary, verifying hypotheses from static analysis, or watching actual syscalls, network calls, or file access; requires human approval before any execution.

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 biology expert from molecular biology to ecology, covering cell biology, genetics, evolution, and physiology

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Expert guidance across solar physics, planetary science, stellar evolution, cosmology, and observational techniques with 2025 mission data

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Classical and modern physics expert covering mechanics, electromagnetism, thermodynamics, quantum mechanics, and relativity

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Podcast expert covering recording, editing, hosting, promotion, and monetization strategies

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Build and ship features with security baked in — runs OWASP Top 10 pre-scan, builds and ships with /ship, validates with post-build security review, then penetration tests the result. Use when shipping auth flows, payment logic, API endpoints, admin panels, or any security-sensitive code.

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Runs a 5-phase enterprise compliance and security hardening pipeline: regulatory review, GDPR audit, SOC 2 evaluation, dependency scan, and penetration test with cross-framework control mapping..

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Deep game design health assessment across five dimensions: review core loop and progression systems, analyze in-game economy for inflation and sink/source balance, mathematically simulate combat balance and drop rates, audit analytics event coverage, and evaluate monetization ethics..

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Full autonomous design pipeline — builds fast, then the safety net polishes it. Chains: design-setup → design-build → (design-audit ∥ design-optimize) → design-polish → design-animate. Ships production-grade interfaces end to end.

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Runs a 4-phase compliance pipeline: security scan, GDPR audit, dependency vulnerability check, and penetration test, producing a unified pass/fail compliance report. Triggers: on: "compliance check", "compliance gate", "run compliance", "pre-release compliance", "security and compliance".

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。

Audit manufacturing production optimization systems for OEE (Overall Equipment Effectiveness) calculation accuracy, Six Big Losses categorization, job shop and flow shop scheduling algorithms (LP, MIP, constraint programming, genetic algorithm), Theory of Constraints bottleneck detection.

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Audit game analytics and telemetry implementation -- event tracking completeness, FTUE and monetization funnel coverage, retention metric infrastructure, A/B testing framework, heatmap data collection, churn prediction signals, and LTV modeling support..

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Audit demand forecasting models and inventory optimization logic -- forecast accuracy (MAPE, bias), safety stock calculations, reorder point strategies (EOQ, ROP, min/max), ABC/XYZ classification, demand signal pipelines, and multi-location network optimization..

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Profile and audit mobile app performance -- cold/warm/hot startup time, memory leaks, battery drain, network efficiency, frame rate jank, and binary size. Triggers: diagnosing slow launches, investigating ANRs, reducing app size, or benchmarking rendering performance.

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。