3万 件 ・ 関連度順
概要と使いどころ
Unity 6 editor scripting and custom tools guide. Use when creating custom inspectors, EditorWindows, PropertyDrawers, Gizmos, Handles, menu items, or editor extensions. Covers SerializedObject/SerializedProperty pattern, AssetDatabase, and editor-only code with #if UNITY_EDITOR. Based on Unity 6.3 LTS documentation.
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 the user asks for general frontend code review, PR review, merge-readiness assessment, architecture maintainability, type-safety, rendering/state risks, style consistency, testability gaps, or a cross-cutting review summary. Delegate deep security, accessibility, E2E, or performance investigations to their specialized skills; Chinese triggers include code review, code review, review.
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 ENCODE experiment quality using standard metrics and audit flags. Use when the user asks about data quality, wants to filter for high-quality experiments, needs to interpret quality metrics (FRiP, NSC, RSC, NRF, IDR, TSS enrichment, fragment size), wants to understand ENCODE audit warnings, needs to compare quality across experiments, or is deciding whether data is usable for their analysis. Also use when the user mentions QC, quality control, or data filtering.
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。
Scan a project to detect configured quality and testing tools across JVM (Gradle/Maven), Android (AGP/Compose/KMP), Node.js/TypeScript, and Python ecosystems. Cross-reference against research-backed recommendations and assist with setup. Auto-detects project type(s) including monorepos with mixed ecosystems. Use when user asks to "audit tooling", "recommend tools", "quality stack", "what tools am I missing", "setup eslint", "setup detekt", "add coverage", "add ruff", "configure CI quality pipeline", "scan project tools", "tooling audit", "android tooling", "android quality", "compose testing", "kmp testing", or "screenshot 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。
Comprehensive SEO analysis for any website or business type. Orchestrates 52 sub-skills (52 active): full site audits, technical SEO (CWV/INP), schema, E-E-A-T content quality, images, sitemaps, GEO for AI Overviews, llms.txt generation, AI crawler audit, plus live GSC and Ahrefs MCP data. GSC: overview, drops, opportunities, brand-vs-nonbrand, cannibalization, compare, content-decay, index-issues, new-keywords. Ahrefs: overview, backlinks, keywords, competitors, content-gap, broken-links, new-links, anchor-analysis, dr-history, top-pages. Cross-MCP: serp, content-brief, brand-radar, site-audit-pro, report. Local: log-analysis, ai-content-check, internal-links, local, migration-check, obsidian-kb. AI Readability: llms-txt, robots-ai. Performance: lighthouse-audit, core-web-vitals, page-experience. Quality & AI Search: rich-results, ai-optimization, eeat-audit, helpful-content. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "structured data", "GSC", "Ahrefs", "backlinks", "keywords", "search console", "domain rating", "local SEO", "migration", "lighthouse", "pagespeed", "LCP", "INP", "CLS", "page experience", "interstitials", "mobile friendly", "rich results", "rich snippets", "schema eligibility", "AI optimization", "AI search readiness", "EEAT", "trust signals", "helpful content", "people-first", "content quality gate".
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。
Analyzes code diffs and files to identify bugs, security vulnerabilities (SQL injection, XSS, insecure deserialization), code smells, N+1 queries, naming issues, and architectural concerns, then produces a structured review report with prioritized, actionable feedback. Use when reviewing pull requests, conducting code quality audits, identifying refactoring opportunities, or checking for security issues. Invoke for PR reviews, code quality checks, refactoring suggestions, review code, code quality. Complements specialized skills (security-reviewer, test-master) by providing broad-scope review across correctness, performance, maintainability, and test coverage in a single pass.
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Create a requirements traceability matrix linking requirements to design, test, and delivery. Use when the user says "traceability matrix", "RTM", "requirements traceability", "link requirements to tests", "trace requirements", "coverage matrix", "are all requirements tested", "requirements coverage", "forward traceability", "backward traceability" - even if they don't explicitly say "traceability matrix".
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。
AI citation readiness audit as part of SEO, covering classic Google search and AI search surfaces together. Use whenever the user wants their content to rank or be cited in ChatGPT, Perplexity, Claude, Gemini, Copilot, You.com, Google AI Overviews, or Google AI Mode. AI citation optimization audit scoring blog posts for major answer surfaces. Evaluates evidence-backed citability, purpose clarity, entity clarity, structured data, and AI crawler accessibility. Suggests evidence-backed explanations and a 0-100 AI Citation Readiness score. Use when user says "geo", "ai citation", "ai optimization", "citation audit", "aeo", "perplexity optimization", "chatgpt citation".
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。
Orchestrates comprehensive production readiness reviews and assessments for GKE clusters and workloads across scalability, security, reliability, observability, backup/DR, and cost optimization. Use when asked to productionize, prepare, assess, audit, or review a GKE cluster or workload before going live to production. Don't use for deep-dive single-domain implementation (use specific domain skills like gke-workload-scaling, gke-platform-security, gke-workload-security, gke-service-networking, gke-reliability instead).
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 overriding the default UI of an Agentforce agent action's Apex input or output with your own Lightning web components via a LightningTypeBundle (schema.json + editor.json/renderer.json, lightning__AgentforceInput / lightning__AgentforceOutput targets, the @apexClassType binding). NOT for standard agent actions with primitive inputs/outputs (only Apex-class input/output can be overridden), NOT for Flow screen custom property editors (use flow/flow-custom-property-editors), and NOT for general LWC-in-Lightning-page work (use lwc/* skills).
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, configuring, or managing Salesforce Lightning Knowledge — enabling the feature, designing record types on Knowledge__kav, configuring Data Categories for organization and visibility control, setting up publishing workflows, and layering approval processes. Trigger keywords: Lightning Knowledge setup, Knowledge article record types, Data Category visibility, Knowledge publishing workflow, Knowledge__kav configuration. NOT for converting Classic Article Types to Lightning — use admin/knowledge-classic-to-lightning. NOT for bulk-loading articles from an external help center — use data/knowledge-article-import. NOT for sizing the taxonomy itself (how many groups, how deep) — use architect/knowledge-taxonomy-design.
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 Einstein Activity Capture (EAC) for an org: enable the feature, create Configuration profiles, set auth type (User-Level or Org-Level OAuth), define email and calendar sync scope, excluded domains and privacy settings, assign users, verify sync health. NOT for querying synced emails or events in SOQL, Apex or reports — use apex/einstein-activity-capture-api. NOT for Opportunity Scoring or Pipeline Inspection — use agentforce/einstein-copilot-for-sales.
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 choosing between Custom Metadata Types and Custom Settings, understanding hierarchical vs list settings, deployment behavior, governor limit implications, or accessing either from Apex and Flow. Trigger keywords: 'custom metadata vs custom settings', 'hierarchical settings per user profile', 'deployable config vs runtime settings', 'getValues getInstance in apex', 'flow get records custom settings'. NOT for modelling the CMT itself or protecting packaged defaults — use admin/custom-metadata-types. NOT for records users edit as business data — use admin/object-creation-and-design. NOT for secrets — use integration/named-credentials-setup. More trigger keywords: customSettingsType, customSettingsVisibility, SetupOwnerId, getOrgDefaults, getAll, DUPLICATE_VALUE in test, SeeAllData custom settings, enableAdvancedCSSecurity, customSettingAccesses, org default profile user override.
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 deployable Salesforce configuration with Custom Metadata Types, especially when choosing between CMTs, Custom Settings, and Custom Objects, protecting packaged defaults, or exposing config to Apex, Flow, and formulas. Triggers: 'custom metadata vs custom settings', 'deployable config', 'protected custom metadata', 'feature flags in Salesforce'. NOT for hierarchical Custom Settings resolution, getInstance/getValues, or their SOQL cost — use admin/custom-metadata-types-and-settings. NOT for high-churn transactional or user-managed business records — use admin/object-creation-and-design. NOT for secrets — use integration/named-credentials-setup. More trigger keywords: __mdt, CustomMetadata .md file, customMetadata folder, getInstance, getAll, xsi:type, visibility PackageProtected, MetadataRelationship, EntityDefinition field, $CustomMetadata.
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。
One page, hands-on manual tier — drive a live page through the web accessibility (a11y) checks a rule engine can't decide: keyboard operation and focus order, screen-reader names, roles and states from the accessibility tree, reflow and zoom, reduced motion, form errors, and target size. Grades each finding by evidence basis (verified / confirm-with-a-human / human-required) and severity, and closes every criterion in a ledger: verified, flagged, not exercised, or N/A. Locates and assesses; does not fix (use `accessibility-fix`). Use it for keyboard testing, focus-order checks, screen-reader or a11y-tree review, reflow and zoom at 200%, or 'is this operable, not just lint-clean'. The automated tier is `accessibility-scan`; `accessibility-audit` runs both across a sampled site.
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。
WCAG 準拠のアクセシビリティチェックをチェックリスト駆動で実行するスキル。 コンポーネント・ページ・PR に対して Pass/Fail/N/A/Needs review の構造化レポートを 生成し、エビデンスと修正案を提示する。 「アクセシビリティチェック」「a11y チェック」「WCAG をチェック」「a11y レビュー」 「アクセシビリティ監査」「WCAG 準拠確認」「アクセシビリティレポート」への言及、 または PR やコンポーネントのアクセシビリティレビュー依頼で発動する。 English: "check accessibility", "a11y audit", "a11y check", "WCAG review", "accessibility report", "screen reader test", "review for a11y", "review this PR for accessibility", "axe audit"
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。
Use when writing TypeScript code, fixing type errors, or configuring strict type safety. Auto-activates on .ts/.tsx files. Covers null handling, utility types, and ESLint.
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。
Patterns for vibe coding that produce production-quality output instead of garbage. Covers prompt engineering for AI coding, verification without reading every line, accept/reject/refine decision framework, architectural guardrails, context management (CLAUDE.md, .cursor/rules), TDD-driven vibe coding, screenshot-driven development, diff review discipline, and the anti-patterns that destroy quality. Activate on: "vibe coding", "AI coding quality", "Claude Code workflow", "AI-assisted development", "how to use AI for coding", "coding with AI", "agentic engineering workflow", "AI code quality", "vibe code without garbage", "production quality AI code", "CLAUDE.md setup", "cursorrules setup", "pre-commit hooks for AI", "TDD with AI", "test-driven vibe coding". NOT for: multi-person collaborative coding sessions (use cooperative-vibe-coding), building AI/LLM applications (use ai-engineer), prompt engineering for non-coding LLM use cases (use prompt-engineer).
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。
Safety, privacy, cost management, and frank advice for building always-on AI agents with episodic memory. Covers data hygiene, privacy risk surfaces, runaway cost prevention, scope creep, psychological effects of persistent AI companions, and responsible deployment patterns. This is the skill that tells you what can go wrong and how to prevent it. Activate on: "agent safety", "always-on agent privacy", "agent cost control", "persistent agent risks", "AI companion safety", "agent data hygiene", "runaway agent costs", "parasocial AI risk", "/always-on-agent-safety". NOT for: architecture design (use always-on-agent-architecture), input design (use always-on-agent-inputs), application brainstorming (use always-on-agent-applications), healthcare compliance specifically (use hipaa-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。
Work with FASTQ quality scores using Biopython - access Phred scores, filter and trim by quality, compute per-position profiles, and convert between Sanger/Phred+33, Solexa, and Illumina/Phred+64 encodings. Use when analyzing read quality, filtering or trimming low-quality bases, generating quality reports, or deciding which FASTQ quality encoding a file uses before parsing.
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。
Quality control for pooled CRISPR screens covering library representation, Gini index, log-skew, replicate Pearson and Spearman concordance, essentialome precision-recall AUC against CEGv2 (Hart 2017), Cas9 cut-toxicity diagnostics, copy-number amplicon detection (Aguirre 2016 / Munoz 2016), bottleneck propagation through plasmid pool, infection, selection, and endpoint stages, MOI verification, and DepMap-style screen-quality scoring. Use when assessing screen quality before hit calling, deciding whether to repeat or rescue a screen, diagnosing low-confidence hits, choosing between MAGeCK / BAGEL2 / Chronos based on quality grade, picking a normalization strategy from QC signatures, or evaluating whether an in-vivo screen retained adequate library complexity.
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。
How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
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。
Unity Prefab / Scene / Asset の壊れた参照・Variant override・配線ミスを構造化応答で診断し、 dry-run → confirm 経路で安全に修復するための MCP ツールリファレンス。 Editor Bridge のセットアップ手順もここに含む。 トリガー: .prefab, .unity, .asset, .mat, Prefab, Variant, 配線, 参照, 壊れた参照, broken reference, GUID, fileID, override, パッチ, patch plan, validate refs, validate structure, where-used, inspect variant, inspect wiring, inspect hierarchy, wiring, null参照, null reference, MonoBehaviour, 階層, hierarchy, Transform整合, 孤立, orphan, 重複fileID, duplicate fileID, Editor Bridge, Bridge セットアップ, bridge setup, deploy_bridge, UNITYTOOL_BRIDGE_WATCH_DIR, watch ディレクトリ のいずれかに該当する作業で使用する。