「quality」の検索結果

Rates responses and plans against quality rubrics. Used for plan validation, response quality audits, and multi-agent consensus.

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 memory retrieval quality (drift, staleness, citation-groundedness) and produce remediation backlog.

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。

Code quality expert including clean code, style guides, and refactoring

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。

LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations

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。

Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", or "content audit".

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. Full site audits, single-page analysis, technical SEO (crawlability, indexability, Core Web Vitals with INP), schema markup, E-E-A-T content quality, image optimization, sitemap analysis, GEO for AI search, local SEO, and strategic planning. Uses Wove browser tools for real-page execution. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "structured data", "local SEO", "page speed".

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。

Guide creating and reviewing skills that extend Claude with specialized knowledge, workflows, or tool integrations. Covers SKILL.md structure, frontmatter quality, trigger design, eval pipelines, and packaging. Triggers on create a skill, review this skill, new skill, optimize skill, skill quality.

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。

Validate proposed or existing backlinks for relevance, editorial legitimacy, link attributes, spam/toxicity risk, platform compliance, anchor quality, target-page fit, and monitoring evidence. Use this skill when the user asks whether an external link opportunity or placed backlink is safe and useful, and reject toxic, irrelevant, paid-undisclosed, fake, or spam placements.

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。

Generalised autonomous optimisation loop — soft RLVR for any artifact a user can measure. Use this skill whenever a user wants to iteratively improve an artifact — code, prompts, documents, configs, designs, content — by running structured experiments, evaluating results against a multi-dimensional rubric, and learning from each attempt. Triggers include: "optimise this", "keep improving until it's good", "run experiments on", "autoresearch", "iterate on this overnight", "try different approaches and pick the best", or any request implying repeated evaluate-and-improve cycles. Also use when the user wants to improve a system prompt, a data pipeline, a writing style, or any artifact where quality can be decomposed into measurable tracks. For inference optimisation tasks (model latency, throughput, quantization, GPU deployment), a* delegates the low-level tuning to AITune while maintaining quality tracking and learning.

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。

App Store / Google Play 用のプロモーションスクリーンショットを Pencil (.pen) で生成する Agent Team スキル。creative-director が戦略を立て、screenshot-designer が Pencil で デザインを構築し、copy-writer がコピーを提供し、spec-validator が技術仕様を数値検証し、 quality-reviewer が最終品質を確認する。5エージェント体制で高品質なスクリーンショットを生成。 Use when: App Store スクリーンショットを作りたい、プロモーション画像を作成したい、 スクショのデザインをしたい。 Triggers: "スクリーンショット作成", "App Store 画像", "プロモーションスクショ", "screenshot creator", "スクショ作って", "App Store 素材"

Chrome で表示中の Web 画面を Pencil (.pen) ファイルに高精度で再現する Agent Team スキル。 3つの専門エージェント（screen-analyzer, design-builder, quality-reviewer）が 分析→構築→品質検証のサイクルを回し、忠実な画面再現を実現する。 Use when: Pencil で再現して、画面を Pencil に写して、Chrome を Pencil にコピー、 pencil-replicate、デザインをキャプチャ、UI を Pencil に

Convert SVG files to high-quality PNG images with precise control over dimensions, background color, and CSS rendering (including mix-blend-mode, filters, gradients). Use this skill when the user wants to: (1) convert SVG to PNG, (2) generate app icons or splash screens from SVG source, (3) batch-generate multiple PNG sizes from a single SVG, (4) render SVG with advanced CSS features like mix-blend-mode or filters to PNG. Triggers: "SVG to PNG", "SVG変換", "PNG変換", "アイコン生成", "スプラッシュ生成", "app icon from SVG", "favicon generation", "splash screen generation".

Multi-phase deep codebase review with severity ratings and structured output. Covers architecture, security, code quality, and UX/accessibility in a single coordinated pass. Produces a prioritized findings table suitable for direct conversion to GitHub issues via the create-github-issues skill.

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。

Qualify a vendor or supplier of GxP-relevant software or services. Covers vendor risk classification, assessment questionnaire design, desk and on-site audit approaches, quality agreement evaluation, SLA review, and ongoing monitoring cadence definition. Use when selecting a new vendor for a GxP-critical system, onboarding a cloud provider for regulated data, performing a periodic re-qualification, when a vendor audit finding requires re-assessment, or when EU Annex 11 or ICH Q10 requires supplier qualification.

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。

Conduct a peer review of research methodology, experimental design, and manuscript quality. Covers methodology evaluation, statistical appropriateness, reproducibility assessment, bias identification, and constructive feedback. Use when reviewing a manuscript, preprint, or internal research report, evaluating a research proposal or study protocol, assessing evidence quality behind a claim, or reviewing a thesis chapter or dissertation section.

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。

Review web design for layout quality, typography, colour usage, spacing, responsive behaviour, brand consistency, and visual hierarchy. Covers design principles evaluation and improvement recommendations. Use when reviewing a design mockup before development, assessing an implemented site for design quality, providing feedback during a design review session, evaluating brand consistency, or checking responsive behaviour across breakpoints.

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。

Set up systematic data labeling workflows using Label Studio or similar tools. Implement quality controls, measure inter-annotator agreement, manage labeler teams, and integrate labeled data into ML training pipelines. Use when starting a supervised ML project that requires labeled training data, when model performance is limited by insufficient labeled examples, when labeling text, images, audio, or video, or when implementing active learning to prioritize the most valuable examples.

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。

Analyze pre-trained generative diffusion models (Stable Diffusion, DALL-E, Flux) by computing quality metrics (FID, IS, CLIP score, precision/recall), inspecting noise schedules, extracting and visualizing attention maps, and probing latent spaces. Use when evaluating a pre-trained generative diffusion model's output quality, comparing noise schedule variants, analyzing cross-attention patterns for text-conditioned generation, interpolating between latent codes, or detecting out-of-distribution inputs.

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。

Review a PR for correctness, security, code quality, and testing issues. TRIGGER when user asks to review a PR, check PR quality, or give feedback on a PR.

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。

Review code for quality, bugs, and improvements. Use when user wants code review or quality assessment.

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。

Orchestrate complex development with AUTOMATIC parallel subagent execution, continuous dispatch scheduling, dependency analysis, file conflict detection, and IOSM quality gates. Analyzes task dependencies, builds critical path, launches parallel background workers with lock management, monitors progress, auto-spawns from discoveries. Use for multi-file features, parallel implementation streams, automated task decomposition, brownfield refactoring, or when user mentions "parallel agents", "orchestrate", "swarm", "continuous dispatch", "automatic scheduling", "PRD", "quality gates", "decompose work", "Mixed/brownfield".

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。

Run a strict multi-iteration Reflex Loop with phases (PLAN, PRODUCE||PREPARE, EVALUATE, CRITIQUE, REFINE) to improve an artifact until quality gates pass or iteration limits are reached. Use when user asks for iterative refinement, quality-gated generation, or "generate -> critique -> refine" loops.

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。

Run a strict multi-iteration Reflex Loop with phases (PLAN, PRODUCE||PREPARE, EVALUATE, CRITIQUE, REFINE) to improve an artifact until quality gates pass or iteration limits are reached. Use when user asks for iterative refinement, quality-gated generation, or "generate -> critique -> refine" loops.

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。

Apply product-grounded visual quality constraints during user-visible UI changes. Use for layout, styling, content hierarchy, theming, responsive behavior, or interaction affordances. Stay inactive for logic-only changes that preserve the rendered interface.

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。