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概要と使いどころ
This skill should be used when the user asks to review a diff or pull request, write review comments, audit code quality, establish review standards, or improve how a team performs code 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。
Run comprehensive quality checks on tabular data (CSV/Excel/TSV/JSON), detecting missing values, duplicates, outliers, format issues, and type inconsistencies to produce an overall score, grade, and actionable suggestions. Triggered when users ask to check data quality, find missing or duplicate values, detect outliers, validate formats, profile data, or clean data.
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 review a diff or pull request, write review comments, audit code quality, establish review standards, or improve how a team performs code 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。
Use this skill whenever a pull request is opened, reopened, or synchronized in microsoft/apm to assess whether and how the documentation corpus must change to stay truthful with the proposed code change. Activate even when the PR title or body says nothing about docs -- the skill must run on every PR to detect silent drift between code and docs. Classifies impact as no-change, in-place edit (one to a few paragraphs), or structural change (new page or TOC reshape), then orchestrates a CDO + doc-writer + python-architect + editorial-owner + growth-hacker loop to produce a patch-ready advisory. Does NOT review code quality, security, or test coverage. Does NOT auto-merge or auto-push doc edits.
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。
Create publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.
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。
Post-implementation gate review: run manual QA on the real surface yourself, then launch ONE gate reviewer (never a panel) to audit goal, constraints, code quality, security, missed context, and QA evidence. Use before a PR handoff or when the user explicitly asks to review completed 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。
Review and create distinctive, production-grade frontend interfaces with high design quality and design system compliance. Evaluates using three pillars: frictionless insight-to-action, quality craft, and trustworthy building. USE FOR: PR reviews, design reviews, accessibility audits, design system compliance checks, creative frontend design, UI code review, component reviews, responsive design checks, theme testing, and creating memorable UI. DO NOT USE FOR: Backend API reviews, database schema reviews, infrastructure or DevOps work, pure business logic without UI, or non-frontend 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。
Remove AI-generated code slop, unnecessary comments, and over-engineering from the current branch diff. Cleans up boilerplate, simplifies abstractions, strips defensive code, and in skill-file mode lints SKILL.md files for quality. Use when cleaning up code, simplifying, removing boilerplate, before committing, or when reviewing a skill before promoting it.
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 wants to migrate code that calls OpenAI, Gemini/Google AI, or the Anthropic API to Amazon Bedrock — a pure model/SDK rewrite. End-to-end: assesses the codebase, rewrites SDK calls, evaluates output quality against Bedrock, and delivers a ready-to-merge git branch. Also has an access-only mode for checking or enabling Bedrock model access for specific models (e.g. 'request access to Claude on Bedrock', 'which models do I turn on') with no code migration — it checks each model and walks the right access step, then stops. Not for agent runtime selection or agent migration planning (use agent-advisor), nor standalone cost estimates or infra-only migration. The full migration REQUIRES gcp-to-aws OR azure-to-aws installed alongside this skill (gcp-to-aws preferred when both are present); access-only mode needs neither.
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。
Production readiness checklist for Anima design-to-code pipelines. Use when deploying automated design-to-code services, preparing CI/CD Figma-to-code automation, or validating output quality before production. Trigger with: "anima production", "anima go-live", "anima prod checklist".
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。
Diagnose and fix common Anima SDK design-to-code errors. Use when encountering Figma token errors, code generation failures, node not found issues, or output quality problems. Trigger with: "anima error", "anima not working", "anima debug", "figma to code error".
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。
Manage software complexity through deep modules, information hiding, and strategic programming. Use when the user mentions "module design", "API too complex", "shallow class", "complexity budget", "strategic vs tactical", "deep module", "information leakage", "pass-through method", "this code is over-engineered", or "simplify this design". Also trigger when reviewing an interface for simplicity, evaluating whether an abstraction is pulling its weight, deciding whether a comment is worth writing, or choosing between general-purpose and special-purpose approaches. Covers deep vs shallow modules, red flags for complexity, and comments as design documentation. For code quality, see clean-code. For architecture boundaries, see clean-architecture.
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 meta-principles of software craftsmanship: DRY, orthogonality, tracer bullets, and design by contract. Use when the user mentions "best practices", "pragmatic approach", "broken windows", "tracer bullet", "software craftsmanship", "avoid technical debt", "code ownership", or "how do I become a better developer". Also trigger when evaluating build-vs-buy decisions, designing estimation approaches, or choosing between reversible and irreversible architectural decisions. Covers estimation, domain languages, and reversibility. For code-level quality, see clean-code. For refactoring techniques, see refactoring-patterns.
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 a UI component spec to the house quality bar — anatomy, variants, sizes, the 8 states, token mapping, and accessibility. Use when the user wants to design or document a component (button, input, tabs, toast, combobox, date picker, modal, etc.) at the spec level before or alongside code. For generating framework code, use design-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。
Reviews test code to identify and fix common testing anti-patterns including flaky tests, over-mocking, brittle assertions, test interdependency, and hidden test logic. Flags bad patterns, explains the specific defect, and provides corrected implementations. Use when reviewing test code, debugging intermittent or unreliable test failures, or when the user mentions flaky tests, test smells, brittle tests, test isolation issues, mock overuse, slow tests, or test maintenance problems.
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 quality review drawing on twelve classic engineering books — with primary focus on xUnit Test Patterns, The Art of Unit Testing, How Google Tests Software, and Working Effectively with Legacy Code — that diagnoses structural problems in an existing test suite: brittleness, mock abuse, coverage illusions, slow execution, poor readability. Triggers when: user asks about test quality, shares test files for review, or expresses frustration: "tests keep breaking whenever I change anything", "our tests take forever", "tests pass but bugs still reach production", or "we have too many mocks". Do NOT trigger for: writing new tests from scratch (use the regular test-writing workflow) or testing framework/syntax questions — this skill reviews an existing suite for structural quality problems, not individual test authoring.
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 changed code for naming, stale references, unnecessary complexity, and comment quality. Use after completing implementation work, before committing, or when the user asks to review or audit 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。
Quality gate: verify each acceptance criterion of a completed task/work unit, run quality checks, and create follow-up tasks for gaps. Use before merging or to audit delivered work. Invoked as /agiflow:review-work <work-unit-or-task>. Uses get_work_unit, get_task, update_task, create_task, create_task_comment.
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 generated or changed test code against universal testing rules before it ships. Best used reactively after an agent writes, edits, generates, or refactors tests, before presenting, committing, or merging them. Use for pytest (test_*.py, *_test.py), PHPUnit/Pest (*Test.php), Jest/Vitest (*.test.ts, *.spec.js), Go (*_test.go), files under tests/, __tests__/, or spec/, and review requests like 'write tests for X', 'add tests', 'test this', 'review these tests', or PR diffs containing tests. Can also guide test writing when explicitly invoked before the work. This skill is the quality gate that prevents AI-generated test bloat. DO NOT USE for production or implementation code review (use clean-code-guard), CI or test-runner configuration, running or debugging tests, or general architecture discussion.
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。
ATAC-seq library quality control -- TSS enrichment, FRiP, fragment-size periodicity, library complexity (NRF/PBC1/PBC2), mitochondrial fraction, and ENCODE 4 thresholds. Use when assessing whether an ATAC-seq library passes ENCODE acceptance criteria, diagnosing transposition artefacts, comparing Omni-ATAC vs standard prep quality, or selecting which replicates to drop before peak calling.
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。
Plan, build and quality-check a premium short commercial for a real business (roofing, property, ecommerce, B2B software) using AI-generated footage, code-built motion (HTML/GSAP), selective Three.js and an independent-critic "Gauntlet" loop. Use when asked to make a launch-style / SaaS-style video, business ad, explainer, sample reel or pitch video, or to review and improve one. Encodes motion principles distilled from 28 professional launch films, a quality bar, audio rules and a business-offer playbook.
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。
Systematic code review for bugs, security, style, and performance
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。
Fullstack development toolkit with project scaffolding for Next.js/FastAPI/MERN/Django stacks and code quality analysis. Use when scaffolding new projects, analyzing codebase quality, or implementing fullstack architecture patterns.
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 code review for diffs. Analyzes changed code for security vulnerabilities, anti-patterns, and quality issues. Auto-detects domain (frontend/backend) from file paths.
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。