「oss」の検索結果

Identifies super-enhancers from H3K27ac, MED1, or BRD4 ChIP-seq using ROSE, ROSE2, LILY, HOMER -style super, and ENCODE dELS cross-referencing. Handles peak stitching parameters, ranking choices, hockey-stick inflection, marker choice (H3K27ac vs MED1/BRD4), and cross-condition comparison with spike-in normalization. Constructs core regulatory circuitry (Saint-Andre 2016) from SE-encoded TFs. Use when identifying cell-identity / cancer-associated regulatory domains, comparing super-enhancers between conditions, identifying master transcription factor networks, or predicting BET-inhibitor responsiveness.

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。

Bulk-query Ensembl BioMart (and other BioMart instances) for cross-database ID mapping, gene/transcript/exon coordinates, and ortholog tables. Use when batch-converting Ensembl IDs to other namespaces (HGNC, RefSeq, UniProt, Entrez), pulling gene coordinate tables for thousands of genes, building ortholog wide-tables across species, or replacing slow Ensembl REST loops with one-shot bulk export. Encodes BioMart's XML query format, R biomaRt vs Python pybiomart trade-off, mart-vs-dataset hierarchy, and the URL endpoint that's BioMart-specific (separate from rest.ensembl.org).

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。

Derive an execution roadmap from a project's vision/spec docs by first principles, then diff that fresh derivation against the existing roadmap to prove the task ORDER is correct. Use this whenever the user wants to review, validate, re-derive, or sanity-check an execution roadmap or delivery plan; asks whether the tasks/epics are "in the right order"; suspects a task is scheduled before its prerequisite (a producer-after-consumer / dependency-inversion error like "OpenAPI after the web client that consumes it", OR a cross-cutting inherited default like observability/auth/tenancy scheduled after the feature work that inherits it — a seam-after-consumer error); wants to find missing tasks, circular dependencies, or over-fragmented epics; or wants to compact a plan to raise velocity. Also trigger on "review the roadmap", "re-derive the plan from the spec", "is this the right build order", "check the dependency graph of our epics", "which task should come first". It reads the vision + spec corpus, decomposes actors → use-cases → modules → epics → typed tasks, identifies cross-cutting inherited-default seams, builds a real dependency graph with hard + soft (seam) edges (deterministic helper), breaks cycles, topologically orders, compacts, and emits a derived roadmap PLUS a delta report against the current one — it never blindly overwrites a hand-crafted roadmap.

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Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUS_LANGUAGE.md. Use when user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".

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。

Expert security auditor for AI Skills and Bundles. Performs non-intrusive static analysis to identify malicious patterns, data leaks, system stability risks, and obfuscated payloads across Windows, macOS, Linux/Unix, and Mobile (Android/iOS).

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。

当用户与不同文化背景的人合作、反馈被误解、询问如何给日本/中国/荷兰同事反馈、或管理多元文化团队时触发。基于Netflix跨文化反馈适应框架：4A+第5个A（调整适应）。

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。

Guides AI agents through Senzing entity resolution workflows using the Senzing MCP server. Covers data mapping to Senzing format, SDK code generation (Python, Java, C#, Rust, TypeScript/Node.js), documentation search, error troubleshooting, sample data access, reporting and visualization, SDK setup guides, and V3-to-V4 migration. Use when working with entity resolution, record matching, record linkage, deduplication, Senzing SDK integration, data mapping for Senzing ingestion, or troubleshooting Senzing error codes. Also use when the user mentions matching records across data sources, finding duplicate entities, identity resolution, master data management, or needs to resolve who is who across datasets.

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Generic ad-hoc topic search across CopilotKit + AG-UI Discord/GitHub. "Find all reports about <topic> in the last <N> days." Returns a structured chronological list with reporter handles + 1-line summaries + optional enterprise enrichment. Triggers on "find all reports about", "search across both communities", "look for X in last N days".

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Enterprise-specific view across CopilotKit + AG-UI. "Enterprise" here = CopilotKit's COMMERCIAL surfaces (Premium / CopilotKit Enterprise / Intelligence Platform / paid tiers), NOT CopilotKit running inside a big company. Tracks the commercial product surfaces (from product-surface-scan — Enterprise Intelligence, Cloud, self-host license, threads/persistence tier, Inspector, premium UI/Angular SDK, analytics, security bundle, Slack/Teams), applies the free-vs-paid classifier to decide if an issue belongs here, surfaces cross-page product contradictions, and tracks enterprise questions/complaints, community-sourced prospects (with a sales owner), and enterprise reporters with prior-week trend. Elevated to the top of the weekly report. Runs standalone ("who's at enterprise this week") or invoked by weekly-report. Triggers on "enterprise report", "enterprise signals", "enterprise status", "who at enterprise this week".

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 quality control for U.S. patent application filing documents. Use when the user asks to QC, check, validate, or review patent filing documents before submission to the USPTO. Performs 70+ automated and manual checks across specification, drawings, ADS, declaration, assignment, and power of attorney documents. Detects cross-document inconsistencies, formatting issues, missing required fields, and common errors.

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。

Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.

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 a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task 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。

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task 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。

Zotero ローカル API + REST API (Web API v3) 連携スキル。DOI からの文献一括インポート、コレクション管理、アイテム検索・一覧表示を行う。 REST API 経由でコレクション作成・アイテム CRUD・タグ管理・添付ファイルアップロード・グループライブラリ操作も可能。 Use when: (1) DOI リストから Zotero に文献を登録する, (2) Zotero のコレクション一覧・アイテム一覧を取得する, (3) BibTeX/RIS データを Zotero にインポートする, (4) CrossRef API で文献の DOI を検索する, (5) REST API でコレクション作成・アイテム追加・タグ管理を行う, (6) グループライブラリを操作する。 Triggers: "zotero", "文献登録", "DOI インポート", "コレクション", "論文追加", "文献管理"

Use when you need blast-radius analysis, dependency graphs, cross-repo impact, breaking-change diff, or architectural overview of .NET workspaces. Keywords: blast radius, dependency graph, impact analysis, cross-repo, call graph, endpoint map, EF Core lineage, breaking change, daemon, reindex.

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 designing account-expansion mechanics — upsell vs cross-sell, expansion-trigger signals, NRR cognition. Triggers on 'lift NRR', 'when do we upsell vs cross-sell'.

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。

Modelo da OpenAI que conecta visão e linguagem. Permite classificação de imagens com zero-shot, correspondência imagem-texto e recuperação cross-modal. Treinado em 400M pares imagem-texto. Use para busca de imagens, moderação de conteúdo ou tarefas visão-linguagem sem fine-tuning. Melhor para compreensão geral de imagens.

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, implement, and integrate generalized validation harnesses across a producer-consumer boundary after a local harness contract exists. Use when refactoring custom validation CLIs/MCPs for large polyrepos, extending Steward across sibling repos, or deploying a local tool to a consumer project for dogfooding and testing; use mcp-harness-repo-maintainer first for initial steward.yaml adoption and cold-start proof.

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。

Before building new infrastructure or a non-trivial capability, check whether the Nuxt ecosystem, UnJS, Vite, or other OSS already solves it — within our constraints (Nuxt, OSS, self-hostable, no mandatory SaaS). Use when weighing build-vs-adopt or starting new infra/tooling.

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 capturing or restoring a learner's persistent profile to personalize teaching across sessions.

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。

intake 全 JSON を統合したいとき、intake.md と intake.json を Jinja2 で render して quality_gate と cross_check を通したいときに使う。

HTML-first persistent planning skill. Generates a single self-contained plan.html with interactive phases, drag-and-drop tickets, sliders, mockups, and embedded JSON state. Survives /clear via session catchup, tamper-protected by SHA-256, mirrors across 17 IDEs, ships 10 templates across Thariq's 9 categories, exports back to Markdown on demand. Use when asked to "plan it", "make me an html plan", "show me the plan", "render the plan", or when starting any multi-step task that needs a navigable artifact instead of a markdown wall.

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。

Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.

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。

Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.

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。