「anti」の検索結果

Assesses ChIP-seq quality across antibody specificity, fragmentation, enrichment, replicate concordance, and library complexity. Computes FRiP, NSC/RSC (phantompeakqualtools), library complexity (NRF/PBC1/PBC2), deepTools plotFingerprint (JS distance, AUC, synthetic JS), ChIPQC, IDR with ENCODE Nself/Nt rules, and detects hyper-ChIPable artifacts. Use when validating an antibody, diagnosing failed peak calls, deciding whether to proceed with downstream analysis, grading against ENCODE thresholds, or auditing replicate concordance.

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Quantifies alternative splicing as PSI (percent spliced in) from RNA-seq using rMATS-turbo (BAM-based event), SUPPA2 (TPM-based event), MAJIQ V3 (LSV-based Bayesian), leafcutter (annotation-free intron clusters), VAST-TOOLS (cross-species with microexon support), Shiba (junction-imbalance-corrected, 2025 SOTA at low coverage), or IRFinder-S (intron retention coverage-aware). Distinguishes the five canonical event classes (SE, A5SS, A3SS, MXE, RI), special classes (microexons, exitrons, AFE/ALE), intron retention subtypes (canonical RI vs detained introns), and applies effective-length normalization. Use when measuring splice-site usage or isoform inclusion ratios from short-read RNA-seq.

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Build, debug, optimize, and deploy ComfyUI workflows for diffusion image, video, and audio generation. Activate on: ComfyUI workflow, ComfyUI custom node, ComfyUI API, ComfyUI Manager, KSampler, FLUX in ComfyUI, Wan 2.2 ComfyUI, Hunyuan video ComfyUI, LTX video ComfyUI, IPAdapter, ControlNet ComfyUI, Kijai wrapper, ComfyDeploy, RunComfy, ComfyUI security, GGUF quantization, TeaCache, Nunchaku, ACE-Step ComfyUI, F5-TTS ComfyUI, subgraphs ComfyUI. NOT for: A1111/Forge/Invoke (different UIs), training pipelines from scratch, non-diffusion ML models, or general image-API integrations (use generative-video-2026 / generative-music-audio / media-gen-deployment).

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Semantic image-text matching with CLIP and alternatives. Use for image search, zero-shot classification, similarity matching. NOT for counting objects, fine-grained classification (celebrities, car models), spatial reasoning, or compositional queries. Activate on "CLIP", "embeddings", "image similarity", "semantic search", "zero-shot classification", "image-text matching".

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Install Port Daddy's bounded interactive coordination hooks ("tentacles", from the Giant Squid Harness) into the INTERACTIVE sessions of agentic coding CLIs (Claude Code, Codex, Gemini, Antigravity/agy) by auto-detecting which CLIs are installed and writing PER-PROJECT hook config behind a runtime gate, so coordination fires only inside a Port Daddy project while the daemon is running — never machine- wide-always-on. Use when the user says "install port daddy hooks", "agent CLI hooks", "interactive session hooks", "make coordination hooks fire in interactive sessions", "codex/gemini/agy hooks", or "auto-detect agent CLIs". NOT for generic software/package installation; NOT for installing the Port Daddy daemon or `pd` CLI itself (delegate to the `port-daddy` skill / `pd setup`); NOT for MCP server setup (delegate to `pd mcp install`); NOT for authoring new skills (delegate to `skill-architect` / `skill-creator`); NOT for editing the tentacle scripts themselves (owned by the Giant Squid Harness program; this installer layer is pd-adr-090).

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SERP-based semantic topic clustering for content architecture planning. Groups keywords by actual Google SERP overlap (not text similarity), designs hub-and-spoke content clusters with internal link matrices, and generates interactive visualizations. Optionally executes content creation if claude-blog is installed. Use when user says "topic cluster", "content cluster", "semantic clustering", "pillar page", "hub and spoke", "content architecture", "keyword grouping", or "cluster plan".

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自分のClaude Codeログから3回以上繰り返している作業を洗い出し、実用できるエージェントスキルを生成する。「定期作業洗い出し」「ログから繰り返し作業」「スキル化候補出して」「この作業をスキル化して」と言われたら起動。2モード搭載 (keyword=高速30秒・無料 / semantic=並列サブエージェント・3-5分・$1〜$3)。出力は候補リスト、生成SKILL.md、実インストールはユーザー承認後

Search academic paper repositories (arXiv, Semantic Scholar) for scholarly articles in physics, mathematics, computer science, quantitative biology, AI/ML, and related fields

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Generates DDD Anti-Corruption Layer for PHP 8.5. Creates translation layer between bounded contexts or external systems. Includes adapters, translators, facades, and unit tests.

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Orchestrate multiple Antigravity skills through guided workflows for SaaS MVP delivery, security audits, AI agent builds, and browser QA.

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Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.

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Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)

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。

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered 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。

Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library

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Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.

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Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants measurable accessibility, performance, responsive, theming, or anti-pattern findings—not when they mainly want an overall UX critique or final visual/detail polish.

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 or refine UI color systems, warmth, semantic color, and color-based hierarchy in designs that are too gray, monochromatic, or missing color meaning. Use when the user mentions dull colors, gray UI, missing warmth, weak semantic color, or a need for stronger color hierarchy.

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Expert in vector databases, embedding strategies, and semantic search implementation. Masters Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recommendation systems, and similarity search. Use PROACTIVELY for vector search implementation, embedding optimization, or semantic retrieval systems.

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。

Test Data Builder Pattern complete implementation guide. Used when using builder pattern to create maintainable test data or simplify complex object test preparation. Covers fluent interface, semantic methods, default value design, and Builder composition patterns. Keywords: test data builder, builder pattern test, test data builder, object mother, fluent interface, fluent interface, UserBuilder, ProductBuilder, .With(), .Build(), AUser(), test data preparation, complex object creation, semantic testing

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。

Integrates AI/LLM via Semantic Kernel. Plugins, prompt templates, memory stores, agents.

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。

Semantic Design System Skill for Google Stitch. Generates agent-friendly DESIGN.md files that enforce premium, anti-generic UI standards — strict typography, calibrated color, asymmetric layouts, perpetual micro-motion, and hardware-accelerated performance.

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Sets up vector databases for semantic search including Pinecone, Chroma, pgvector, and Qdrant with embedding generation and similarity search. Use when users request "vector database", "semantic search", "embeddings storage", "Pinecone setup", or "similarity search".

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。

Automates releases and package publishing with changesets or semantic-release. Handles versioning, changelog generation, git tags, and release notes. Use for "release automation", "semantic versioning", "package publishing", or "changelog 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。

Generates semantic commit messages following the Conventional Commits specification with proper types, scopes, breaking changes, and footers. Use when users request "write commit message", "conventional commit", "semantic commit", or "format commit".

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。