「soft」の検索結果

Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx) or Word templates (.dotx). Triggers include: any mention of Microsoft Word Documents, such as 'Word doc', 'word document', '.docx', '.dotx', 'microsoft doc'. Also use when extracting or reorganizing content from .docx or .dotx files, inserting or replacing images in documents, find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a deliverable as a Word or .docx file (to download, email or print), use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or coding unrelated to document 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。

软件开发团队产品经理（许清楚）。擅长产品需求文档（PRD）撰写、竞品分析、市场研究、用户故事编写和需求优先级管理。 触发词：由 software-team-lead 主理人调度执行 PRD 撰写或市场调研任务时激活。不直接面向用户。

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。

软件开发团队架构师（高见远）。基于 PRD 设计系统架构 + 任务分解。擅长技术选型、系统架构设计、API 设计、DB Schema 设计、任务拆解与依赖分析。 触发词：由 software-team-lead 主理人调度执行架构设计任务时激活。不直接面向用户。

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。

软件开发团队 QA 工程师（严过关）。编写全面稳健的测试，确保代码按预期工作。执行智能路由判定，区分源码 Bug 和测试代码 Bug。 触发词：由 software-team-lead 主理人调度执行测试验证任务时激活。不直接面向用户。

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。

软件开发团队工程师（寇豆码）。负责编写优雅、可读、可扩展、高效的代码。按系统设计和任务列表批量编写代码，并进行全局一致性审查。 触发词：由 software-team-lead 主理人调度执行编码任务时激活。不直接面向用户。

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。

Investigate Azure incidents and service degradations with a read-only workflow using Azure CLI, Resource Health, Activity Log, metrics, resource logs, and official Microsoft docs. Use when troubleshooting Azure outages, Resource Health alerts, Azure Firewall or DNS failures, ExpressRoute or BGP instability, VM availability problems, AKS incidents, App Service failures, database connectivity issues, Entra ID sign-in problems, load balancer issues, platform-vs-workload cutover, or drafting a troubleshooting report. Triggers on 'Azure トラブルシューティング', '障害調査', '切り分け', 'Resource Health', '復旧確認', 'Azure Firewall', 'DNS', 'ExpressRoute', 'VPN Gateway', 'BGP', 'AKS', 'App Service', 'SQL', 'PostgreSQL', 'Cosmos DB', 'Entra ID', 'incident', 'degraded', 'unavailable'.

Prepare and verify Microsoft Teams desktop chat drafts with Windows UI Automation, stopping before send. Use for Teamsチャット下書き, デスクトップTeams操作, 宛先確認, メッセージ入力, or when Teams Web/CDP is unavailable.

Build and validate Azure infrastructure in a lab or sandbox using Azure CLI and official Microsoft docs. Use when creating verification environments, provisioning hub-and-spoke VNets, VPN Gateway or ExpressRoute-adjacent validation labs, checking subscription/tenant access, debugging Azure deployment constraints, comparing before/after route behavior, or cleaning up lab resources. Triggers on 'Azure 検証', '検証環境', 'PoC', 'sandbox', 'lab', 'Azure CLI で構築', 'VPN Gateway', 'VNet peering', 'BGP', 'route validation', 'summarizedGatewayPrefixes', 'デプロイして検証', 'インフラ検証'.

Execute lateral movement within Microsoft Entra ID (formerly Azure AD) and Microsoft 365 environments. Use this skill to traverse cloud resources using compromised user tokens, managed identities, Primary Refresh Tokens (PRT), and application permissions (Service Principals) to achieve Global Administrator access.

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。

Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconciliation, audience overlap and campaign self-competition audits, suppression lists, ROAS improvement, media spend optimization, and the media no auction sells — newsletter and podcast sponsorships, community and industry-publication placements, paid review-site listings on G2 and Capterra, and pay-per-lead content syndication. It also covers buying on the AI answer surface — ads inside Google AI Overviews and AI Mode that existing Search, Shopping and Performance Max campaigns already serve into with no opt-out, no placement targeting and no segmented reporting, and ChatGPT Ads and Microsoft Copilot as separate opt-in platforms with their own plan-tier reach limits, no negative keywords, and a landing-page crawler gate. It also owns the conversion signal the bidding algorithms learn from — CRM pipeline stages (SQL, opportunity, closed-won) sent back to Google Ads, LinkedIn, Meta and Microsoft Ads through offline conversion import, enhanced conversions for leads, the Google Data Manager API and the LinkedIn Conversions API, with click-ID capture, stage values, dedupe, EEA consent signals and retractions. It also gates connected TV (CTV) and streaming video for B2B — whether a reach medium belongs in the plan, how a vendor ties a TV household to a target account (member data, IP-to-account graph or contextual), the server-side ad insertion (SSAI) fraud questions, Programmatic Guaranteed deals, and a holdout lift test because CTV has no click. It also runs person-led paid social — LinkedIn Thought Leader Ads and Meta partnership ads that put spend behind an employee's or creator's post — on a paid-usage term, an in-post disclosure check and an end-date register, because the platform approval carries no term. Also triggers on: CTV, connected TV, OTT, streaming TV ads, should we run CTV, LinkedIn CTV, B2B CTV, account-based CTV, SSAI fraud, thought leader ads, boost an employee's post, sponsor a creator's post, partnership ads, whitelisting, creator usage rights, PPC, Google Ads, LinkedIn Ads, social ads, programmatic, ad creative, attribution, media budget, paid campaigns, ROAS, CPA, ad spend, newsletter sponsorship, podcast sponsorship, community sponsorship, sponsor a newsletter, content syndication, pay-per-lead, cost per lead vendor, media kit, rate card, insertion order, direct buy, publisher partnership, make-good, G2 paid listing, Capterra ads, review site advertising, sponsorship ROI, budget pacing, we underspent our budget, are our campaigns competing with each other, audience overlap, self-competition, campaign cannibalization, suppression list, exclusion list, ad frequency across channels, how many ad accounts do we have, ads in AI Overviews, AI Mode ads, ChatGPT Ads, OpenAI Ads Manager, Copilot ads, conversational ads, should we advertise on ChatGPT, can we buy our way into the AI answer, our ads are showing in AI Overviews and we cannot report on it, context hints, OAI-AdsBot, our ad landing page fails review, robots.txt is blocking our ads, our paid leads are junk, Google Ads is optimizing for the wrong leads, offline conversion import, OCI, enhanced conversions for leads, send CRM stages back to Google Ads, upload SQLs to LinkedIn, LinkedIn Conversions API, LinkedIn CAPI, Meta conversion leads, CRM to ad platform, gclid, li_fat_id, msclkid, value-based bidding, optimize for pipeline not form fills, low match rate, conversion lag.

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 a task needs the judgment of a systems engineer/architect working at the whole-program level — decomposing requirements across hardware/software/network subsystems, writing or reviewing an interface control document (ICD), making a build-vs-buy tradeoff for a subsystem, or tracing a verification failure back through the requirements baseline. Distinct from a software engineer (owns one service's code) or DevOps/SRE (owns operational reliability) — this role owns the technical baseline for a whole system-of-systems and is accountable when subsystems built by different teams or vendors don't fit together.

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。

Evaluate architecture and module boundaries for volatility-based decomposition using Juval Lowy's framework (from "Righting Software", building on Parnas 1972). Use when reviewing module splits, service boundaries, new abstractions, or any decomposition decision. Trigger on phrases like "where should this boundary be", "how to split this", "module boundaries", "encapsulate change", "volatility", or references to Lowy, Parnas, or "Righting Software". Complements /hickey (interleaved concerns) with a different lens (change encapsulation).

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 this skill when setting up Service Cloud Voice with Amazon Connect — provisioning the contact center, configuring phone numbers, enabling real-time transcription, and configuring After Conversation Work Time. Covers the deployable metadata behind it: CallCenter, ConversationVendorInfo (vendorType), CallCenterRoutingMap, the Voice ServiceChannel that carries ACW, ServicePresenceStatus, PresenceUserConfig, ServiceCloudVoice.settings, and the VoiceCall / VoiceCallRecording objects. Trigger keywords: Service Cloud Voice, Amazon Connect, contact center, softphone, call transcription, After Conversation Work, ACW, wrap-up time, VoiceCall, CallCenter metadata, vendorType, telephony provider. NOT for Omni-Channel routing setup — use admin/omni-channel-routing-setup. NOT for Open CTI softphone adapters — use apex/cti-adapter-development. NOT for Sales Dialer (Voice.settings) — that is a different product.

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 this skill to select the right Salesforce integration pattern — from point-to-point to event-driven to hub-and-spoke — by applying the official Salesforce two-axis decision framework (integration type × timing) to a business integration scenario. Trigger keywords: integration pattern decision, choose integration approach, Salesforce integration architecture, when to use platform events vs API, integration type selection. NOT for implementation of any specific integration pattern (use domain-specific integration skills), MuleSoft architecture (use architect/mulesoft-anypoint-architecture), or middleware vendor selection. More triggers: integration decision record, Bulk API vs REST for a nightly load, external Id upsert, Named Credential vs Remote Site Setting, platform event vs CDC, who calls whom.

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。

Configure and operate NPSP Gift Entry: gift entry templates, batch gift entry, payment processing, donation allocation, and receipting workflows. NOT for a one-time migration of historical gift data — use data/gift-history-import. NOT for soft credits or matching gifts — use admin/soft-credits-and-matching.

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.

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。

This skill should be used when the user asks to "build a feature", "fix a bug", "implement something", "start a dev cycle", types "/dev", or describes a software task that requires design, implementation, testing, and shipping. Orchestrates the full software development lifecycle from interrogation through shipping, with self-learning that improves over time.

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 creating software diagrams using Mermaid syntax. Use when users need to create, visualize, or document software through diagrams including class diagrams (domain modeling, object-oriented design), sequence diagrams (application flows, API interactions, code execution), flowcharts (processes, algorithms, user journeys), entity relationship diagrams (database schemas), C4 architecture diagrams (system context, containers, components), state diagrams, git graphs, pie charts, gantt charts, or any other diagram type. Triggers include requests to "diagram", "visualize", "model", "map out", "show the flow", or when explaining system architecture, database design, code structure, or user/application flows.

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。

Linting and code quality workflow for Software Metrics Machine. Covers ESLint 9.x flat config, Prettier formatting, lint-staged (auto-fix on commit), per-workspace configs, TypeScript strict mode, and all lint commands. USE FOR: lint, eslint, prettier, format, code style, linting, lint fix, auto-fix, check style, code quality, lint-staged, typecheck, type-check, tsc noEmit. DO NOT USE FOR: writing tests (use tdd skill), building (use build commands), commit hooks 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。

VitePress documentation workflow for Software Metrics Machine docs under docs/vitepress. Use when creating, updating, reviewing, or restyling SMM documentation pages, especially feature docs that must keep CLI terminal examples and dashboard views/screenshots in sync. Covers Markdown style, VitePress tabs, command examples, dashboard screenshots, sidebar links, and docs validation. USE FOR: docs/vitepress, VitePress docs, documentation style, CLI docs, dashboard docs, screenshots, feature pages. DO NOT USE FOR: application code changes unless needed to verify documented behavior.

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-Driven Development workflow for Software Metrics Machine. Covers test frameworks (Vitest 4.x for CLI/REST/core/utils, Jest 30.x for webapp), test patterns (describe/it, builder pattern, mocks via vi.fn), test commands, coverage requirements, and the Red-Green-Refactor cycle. USE FOR: write tests, run tests, test this, add tests, testing, coverage, TDD, test-driven development, vitest, jest, test pattern, test convention. DO NOT USE FOR: linting (use lint skill), building (use build commands directly), debugging production issues.

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。

Acceptance testing workflow for the Software Metrics Machine CLI e2e suite. Use when writing, extending, debugging, or reviewing bashunit acceptance tests under apps/cli/e2e, including command help checks, cached fixture flows, GitHub MSW-backed flows, local git repository fixtures, SMM_STORE_DATA_AT workspaces, and pnpm run test:cli:acceptance. USE FOR: CLI acceptance tests, e2e tests, bashunit, apps/cli/e2e, command smoke tests, persisted CLI output tests. DO NOT USE FOR: unit tests or Vitest tests (use tdd skill), linting (use lint skill), webapp browser tests.

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。

Model organizations as BDI systems with filtered perception, discourse-shaped desires, accommodations, and abstraction-level hierarchy. Use for socio-technical coordination and organizational modeling. NOT for mechanistic workflows, individual psychology, or non-social domains.

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。

Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2024 bioRxiv; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.

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。