「quality」の検索結果

Expert en data engineering (ETL, Airflow, dbt, data lakes, streaming pipelines, data 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。

Expert en annotation de données avancé (annotation, quality, active learning, consensus, tools)

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。

Improve AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.

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。

Iteratively improve a Claude Code skill using the skill-reviewer agent until it meets quality standards. Use when improving a skill with multiple quality issues, iterating on a new skill until it meets standards, or automated fix-review cycles instead of manual editing.

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 taste-informed design reviews using Observation > Principle > Question. Use when facilitating design critiques, improving feedback quality on a team, or building a shared vocabulary for 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。

Consistent radii, pixel-perfect alignment, state coverage, and the details that signal design quality. Use when polishing designs, auditing quality, or evaluating whether a design is ready to ship.

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。

新機能を実装まで一気通貫で走らせる action skill。Agent Teams で要件・設計・タスク分解・実装・quality-gate を自動実行し、コードがコミット可能な状態になるまで止まらない（Sisyphus Loop）。auto mode でも planning ではなく action として積極発動する。「実装して」「作って」「機能を追加して」「新機能を作りたい」「要件から実装まで一気に」「計画して」「この機能を実装したい」で発動。

Review a git diff or explicit file scope for reuse, code quality, efficiency, clarity, and standards issues, then optionally apply safe Codex-driven fixes. Use when the user asks to "simplify code", "review changed code", "check for code reuse", "review code quality", "review efficiency", "simplify changes", "clean up code", "refactor changes", or "run simplify".

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。

Runs a comprehensive 20-point code quality audit on a "vibe-coded" codebase that was shipped fast and now needs hardening. Use this skill whenever the user mentions vibe coding, vibe audit, code audit, code review, code cleanup, hardening a prototype, productionizing a codebase, technical debt cleanup, or asks Claude to "audit my code", "review my codebase", "clean up my project", or check a freshly-shipped project for common quality issues. Also use when a user shares a repo and asks what's wrong with it or how to make it production-ready.

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。

VibeFarsi quality auditing: production-level item audit, accessibility, CSS conflicts. Use when implementing, reviewing or testing vibefarsi quality auditing for React, Vite, Next.js or Perfect_AI projects.

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 technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality 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。

Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.

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 Codex/Claude agent skills, profile manifests, and skill-related deploy changes before they ship. Use when creating, editing, importing, installing, or reviewing SKILL.md files, agent manifests, optional third-party skills, or plugin skill bundles. Checks trigger quality, progressive disclosure, evidence gates, security, hallucination risk, validation, and deployment impact.

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。

Convergence loop that iteratively improves work until quality thresholds are met. Scores, diagnoses specific weaknesses, rewrites, re-scores, and repeats until all dimensions reach 8/10 or diminishing returns are detected. Use when you want to refine or iterate on work, after the analyst gives a REVISE verdict, or when output quality is below your bar. Part of the architect-system loop. Outputs to system/refinery-log.md.

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。

Senior engineering analyst for code review, plan review, and automation review. Four-lens review covering architecture, code quality, reliability, and performance, each scored 1-10. Delivers APPROVE, REVISE, or REJECT verdicts. Use when you need a code review, plan review, quality check, or want to verify work before shipping. Part of the architect-system loop. Reads from system/blueprints/ and source code. Outputs to system/reviews/.

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。

Convergence loop that iteratively improves work until quality thresholds are met. Use when: (1) "refine this", "make this better", "iterate on this", (2) After /analyst gives a REVISE verdict, (3) Output quality is below 8/10, (4) "run the refinery loop on this". Reads analyst reviews from system/reviews/. Generates, scores, diagnoses, rewrites, re-scores. Stops when all dimensions >= 8/10 or diminishing returns detected. Outputs to system/refinery-log.md.

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。

Senior engineering analyst for code review, plan review, and automation review. Use when: (1) "review this", "analyze the code", "check this plan", (2) After implementation to verify quality, (3) "is this good enough?", (4) Before marking a task complete, (5) Reviewing a blueprint from /architect, (6) Reviewing output from /refinery. Four-lens review: architecture, code quality, reliability, performance. Reads from system/blueprints/ and source code. Outputs to system/reviews/.

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 fullstack development skill for building complete web applications with React, Next.js, Node.js, GraphQL, and PostgreSQL. Includes project scaffolding, code quality analysis, architecture patterns, and complete tech stack guidance. Use when building new projects, analyzing code quality, implementing design patterns, or setting up development workflows.

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。

変更内容からミューテーション/E2Eの推奨度を判定し、強く推奨・範囲が小さい・副作用なしのものは確認なしで実施し、それ以外は最後の報告で確認する。quality-check Step 5から参照実行されるほか、開発中の任意タイミングで単体実行できる。

UI実装後の検証時に使用。agent-browser CLIでブラウザ上の動作を手動検証する。「UIを確認」「画面テスト」と言われたら使用（プロジェクトの E2E スイート実行は quality-check Step 5（推奨度・範囲で自動実施または確認）/ server-startup が担当）。

Generates high-quality image prompts for AI image generators (Midjourney, DALL-E, Stable Diffusion). Use when user mentions "イラスト作成", "画像プロンプト", "プロンプト生成", or "画像生成".

Autonomous model validation and benchmarking. Investigates any ML model (LLM, image gen, TTS, time series, etc.), runs it on GPU cloud, evaluates quality and performance, and generates HTML reports. Use when user asks to verify, benchmark, evaluate, or test a model. Triggers on "verify model", "benchmark", "evaluate model", "test model", "run benchmark", "model evaluation", "モデルを検証", "ベンチマーク", "モデルを試して".

Use after changing prompts, skills, the compiler, or editorial policies — or when the user asks to measure edit quality, run regression evals, check agreement with approved edits, or says '評価して', '一致率を測って', 'eval を回して'. Compares agent output against human-approved golden projects.

Build training datasets for LLM specialization from production data, frontier model distillation, and synthetic bootstrapping. Use when formatting production logs into SFT data, distilling from frontier APIs, or preparing data for fine-tuning. Covers JSONL formatting, data quality validation, deduplication, and train/eval splitting.

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。