「nc」の検索結果

研究計画の「もし条件が変わったら」を複数のシナリオで検討し、前提と根拠を整理しながら、代替案の比較、予備策、対応を切り替える判断基準づくりを支援します。

• 試料の脱落が想定より多い場合に備えたいとき
• 試薬やデータが使えない場合の予備策づくり
• 資源制約の下で研究案を比較したいとき

科学論文や研究概要に必要な文献を集め、主張を支える根拠や反対の知見を整理します。参考文献、研究比較表、主張と出典の対応表をまとめ、執筆の準備を支援します。

• 論文の背景文献を集めたいとき
• 支持・反対・差のない研究結果の比較
• 研究比較表と主張・出典対応表の作成

薬剤・遺伝子・疾患の関係を、種類や探索範囲を指定してARAXで調べます。直接の関係や中間要素を一つ挟む経路を取得し、出典や関連文献も確認するスキル。

• 薬剤と遺伝子の関係を調べたいとき
• 薬剤と疾患を結ぶ経路の探索
• 関連文献と元データの出典確認

公開された遺伝子変異の証拠や関連論文、遺伝子と疾患の関係を調べ、出典と検索結果の状態を保ちながら、専門家による確認に向けて整理するスキル。

• 単一変異の公開証拠を確認したいとき
• 特定した変異の関連論文を探したいとき
• 遺伝子と疾患の関係の調査

Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking 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。

Master Rust async programming with Tokio, async traits, error handling, and concurrent patterns. Use when building async Rust applications, implementing concurrent systems, or debugging async code.

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。

Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.

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。

Govern Power Automate flows and Power Apps at scale using the FlowStudio MCP cached store. Classify flows by business impact, detect orphaned resources, audit connector usage, enforce compliance standards, manage notification rules, and compute governance scores — all without Dataverse or the CoE Starter Kit. Load this skill when asked to: tag or classify flows, set business impact, assign ownership, detect orphans, audit connectors, check compliance, compute archive scores, manage notification rules, run a governance review, generate a compliance report, offboard a maker, or any task that involves writing governance metadata to flows. Requires a FlowStudio for Teams or MCP Pro+ subscription — see https://mcp.flowstudio.app

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 guide for configuring and managing GitHub Dependabot. Use this skill when users ask about creating or optimizing dependabot.yml files, managing Dependabot pull requests, configuring dependency update strategies, setting up grouped updates, monorepo patterns, multi-ecosystem groups, security update configuration, auto-triage rules, or any GitHub Advanced Security (GHAS) supply chain security topic related to Dependabot. For pre-commit dependency vulnerability scanning in AI coding agents via the GitHub MCP Server, this skill references the Advanced Security plugin (`advanced-security@copilot-plugins`). Use this skill when an agent needs to scan dependencies for known vulnerabilities before committing.

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 professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers. Extract, normalize, and standardize financial data into investment committee-ready Excel workbooks with consistent structure, proper formatting, and documented assumptions. Use for M&A due diligence, private equity analysis, investment committee materials, and standardizing financial reporting across portfolio companies. Do not use for simple financial calculations or working with already-completed data packs.

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。

Track and analyze portfolio company performance against plan. Ingests monthly/quarterly financial packages (Excel, PDF), extracts KPIs, flags variances to budget, and produces summary dashboards. Use when reviewing portfolio company financials, preparing board materials, or monitoring covenant compliance. Triggers on "review portfolio company", "monthly financials", "how is [company] performing", "covenant check", or "portfolio update".

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。

Complete, populate and fill out 3-statement financial model templates (Income Statement, Balance Sheet, Cash Flow Statement) . Use when asked to fill out model templates, complete existing model frameworks, populate financial models with data, complete a partially filled IS/BS/CF framework, or link integrated financial statements within an existing template structure. Triggers include requests to fill in, complete, or populate a 3-statement model template

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。

Detect MITRE ATLAS AML.T0024 attacks (model stealing, inversion, membership inference) performed via inference-API abuse, by monitoring per-principal query volume/distribution, rate-limiting and perturbing outputs, and red-teaming your model's extractability. Use for a public or partner inference API needing cloning/inversion/membership-inference detection, or a pre-deployment red-team exercise to measure extraction risk.

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 DCSync attacks by abusing MS-DRSR replication rights (DS-Replication-Get-Changes/-All) to impersonate a Domain Controller and extract KRBTGT, Domain Admin, and service account hashes for Golden Ticket forging, typically with Mimikatz. Use in authorized engagements after finding principals with replication rights, to establish long-term domain persistence, or to validate detections for replication abuse.

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。

Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

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。

Examine Linux system artifacts (auth logs, cron/systemd persistence, shell history, SSH keys, and system configuration) to uncover evidence of compromise, detect rootkits or backdoors, and reconstruct user/attacker activity. Use when investigating a compromised Linux server or workstation, hunting for persistence mechanisms, or scoping a Linux-based breach during incident response.

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 guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking 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。

Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.

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 and draft multi-email sequences with full copy, timing, branching logic, exit conditions, and performance benchmarks. Use when building onboarding, lead nurture, re-engagement, win-back, or product launch flows, when you need a complete drip campaign with A/B test suggestions, or when mapping a sequence end-to-end with a flow diagram.

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。

Generate financial statements (income statement, balance sheet, cash flow) with period-over-period comparison and variance analysis. Use when preparing a monthly or quarterly P&L, closing the books and need to flag material variances, comparing actuals to budget, building a financial summary for leadership review, or looking up GAAP presentation requirements and period-end adjustments.

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。

Product marketing skill for positioning, GTM strategy, competitive intelligence, and product launches. Use when the user asks about product positioning, go-to-market planning, competitive analysis, target audience definition, ICP definition, market research, launch plans, or sales enablement. Covers April Dunford positioning, ICP definition, competitive battlecards, launch playbooks, and international market entry. Produces deliverables including positioning statements, battlecard documents, launch plans, and go-to-market strategies.

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。

Canonical reference for Kortix projects, Apps (sites, servers, backends with volumes) and internal business apps, the CLI, sessions, sandboxes, change requests, triggers, connectors, secrets, system skills, and the two session harnesses, pi and OpenCode. Covers `kortix.yaml` versions 1 and 2, App deployments, harness configuration (`harnesses/pi/`, `harnesses/opencode/`), session identity, credential boundaries, and the complete pi and OpenCode references. Load when the user asks how Kortix works, what Kortix can do, how to deploy an App, how an agent discovers platform instructions, how to customize or configure this project's agents (create or fix an agent, subagent, skill, tool, plugin, extension, pi package, command, MCP server, model or permission rule; edit `opencode.jsonc`), how to edit `kortix.yaml`, how to use the `kortix` CLI, how to land work through a change request, or how to schedule and automate work.

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。

Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.

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 a website or digital experience against its supplied source references for originality and plagiarism risk. Use when Codex must compare current or historical site output with reference pages, capture packs, screenshots, copy, brands, numbers, images, assets, videos, layouts, motion, or code; raise evidence-backed red flags; distinguish common visual grammar from distinctive copying; and propose concrete fixes without making unsupported legal claims.

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。