Build React/TypeScript frontends with modern patterns. Use for components, Suspense, lazy loading, useSuspenseQuery, MUI v7 styling, TanStack Router, performance optimization.
原文の言語: 英語
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このリポジトリの skills
SkillsMP は hoanghd218/ZaloCRM から 101 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
hoanghd218/ZaloCRM収集済み skill 101 件中 40 件を表示しています。
Build React/TypeScript frontends with modern patterns. Use for components, Suspense, lazy loading, useSuspenseQuery, MUI v7 styling, TanStack Router, performance optimization.
原文の言語: 英語
Git operations with conventional commits. Use for staging, committing, pushing, PRs, merges. Auto-splits commits by type/scope. Security scans for secrets.
原文の言語: 英語
Semantic code analysis with GitLab Knowledge Graph. Use for go-to-definition, find-usages, impact analysis, architecture visualization. Supports Ruby, Java, Kotlin, Python, TypeScript/JavaScript.
原文の言語: 英語
Build AI agents with Google ADK Python. Multi-agent systems, A2A protocol, MCP tools, workflow agents, state/memory, callbacks/plugins, Vertex AI deployment, evaluation.
原文の言語: 英語
Build queryable knowledge graphs from code, docs, papers, and images. Use for codebase understanding, architecture analysis, cross-file relationship discovery, token-efficient navigation.
原文の言語: 英語
Create a concise, redacted conversation handoff for a fresh agent session. Use when switching context, ending a work session, or preserving decisions and blockers.
原文の言語: 英語
Open the AgentKit help index. Use when users ask how to use ak, what skills are available, or which workflow to run.
原文の言語: 英語
Create local MP4 videos from HTML/CSS/JS templates with nexu-io/html-video. Covers source checkout setup, template discovery, studio customization, preview, and render verification.
原文の言語: 英語
Extract a user's vision and decisions into durable project documents through a guided interview. Use for README, ADR, strategy, principles, and structured-doc authoring.
原文の言語: 英語
Turn a GitHub issue into an audited, validated implementation plan. Reads the issue, scouts the codebase, runs a hard brainstorm gate, and only then plans with mandatory --html --wiki, validate, and red-team, before pushing a plan branch and handing off on…
原文の言語: 英語
Write chronological technical journals for session reflection and change analysis. Journals preserve work history; they do not replace current docs or ADRs.
原文の言語: 英語
Generate llms.txt files from docs or codebase scanning. Follows llmstxt.org spec. Use for LLM-friendly site indexes, documentation summaries, AI context optimization.
原文の言語: 英語
Autonomous iterative optimization loop — run N iterations against a mechanical metric, learn from git history, auto-keep/discard changes. Use for improving measurable metrics (coverage, performance, bundle size, etc.) through repeated experimentation.
原文の言語: 英語
View markdown files in a calm, book-like reader served via HTTP. Use for long-form content review — RFCs, runbooks, design docs, reports, specs, novels — anywhere you want a distraction-free reading mode in the browser.
原文の言語: 英語
Build MCP servers for LLM-external service integration. Use for FastMCP (Python), MCP SDK (Node/TypeScript), tool design, API integration, resource providers.
原文の言語: 英語
Process media with FFmpeg (video/audio), ImageMagick (images), RMBG (AI background removal). Use for encoding, format conversion, filters, thumbnails, batch processing, HLS/DASH streaming.
原文の言語: 英語
Create diagrams with Mermaid.js v11 syntax. Use for flowcharts, sequence diagrams, class diagrams, ER diagrams, Gantt charts, state diagrams, architecture diagrams, timelines, user journeys.
原文の言語: 英語
Build and maintain Mintlify documentation sites. Covers docs.json, MDX components, navigation, page frontmatter, theming, OpenAPI/AsyncAPI, AI docs assets such as llms.txt and skill.md, deployment targets, and local validation CLI commands.
原文の言語: 英語
Build mobile apps with React Native, Flutter, Swift/SwiftUI, Kotlin/Jetpack Compose. Use for iOS/Android, mobile UX, performance optimization, offline-first, app store deployment.
原文の言語: 英語
Coordinate multiple coding-agent CLIs headlessly, plus in-session harness subagents. Use for staged or parallel jobs across Claude Code, Codex, AgentKit skill runs, internal harness subagents (Agent tool via runtime: internal or --internal), and external CLIs…
原文の言語: 英語
Integrate payments with SePay (VietQR), Polar, and Stripe. Checkout, webhooks, subscriptions, QR codes, and multi-provider orders.
原文の言語: 英語
Plan implementations, design architectures, create technical roadmaps with detailed phases. Use for feature planning, system design, solution architecture, implementation strategy, phase documentation, editorial self-contained HTML plan artifacts with --html,…
原文の言語: 英語
Open the AgentKit plans dashboard in the CLI config UI. Use for plan kanban views, progress tracking, timeline checks, and quick navigation into plan files.
原文の言語: 英語
5 expert personas debate proposed changes before implementation. Catches architectural, security, performance, and UX issues early. Use before major features or risky changes.
原文の言語: 英語
View files or generate visual explanations, slides, and diagrams. Use for code walkthroughs, architecture visualization, HTML/Markdown presentations.
原文の言語: 英語
Apply systematic problem-solving techniques when stuck. Use for complexity spirals, innovation blocks, recurring patterns, assumption constraints, simplification cascades, scale uncertainty.
原文の言語: 英語
Track progress, update plan statuses, manage Claude Tasks, generate reports, coordinate docs updates. Use for project oversight, status checks, plan completion, task hydration, cross-session continuity.
原文の言語: 英語
Organize files, directories, and content structure in any project. Use when creating files, determining output paths, organizing existing assets, or standardizing project layout.
原文の言語: 英語
Apply React and Next.js performance optimization patterns from Vercel Engineering. Use for component optimization, rendering performance, bundle analysis.
原文の言語: 英語
Build video content with Remotion in React. Use for programmatic video creation, animated sequences, data-driven video rendering.
原文の言語: 英語
Pack repositories into AI-friendly files with Repomix (XML, Markdown, plain text). Use for new-project onboarding, codebase snapshots, LLM context preparation, security audits, third-party library analysis.
原文の言語: 英語
Draft a self-contained research brief for a human or AI researcher. Use when users ask for a research prompt, research brief, or a deep-research task to hand off.
原文の言語: 英語
Research technical solutions, analyze architectures, gather requirements thoroughly. Use for technology evaluation, best practices research, solution design, scalability/security/maintainability analysis.
原文の言語: 英語
Generate data-driven sprint retrospectives from any git history. Use for sprint reviews, commit analysis, code-health indicators, team-velocity reporting, and quarterly engineering reviews. Works on solo or team repos.
原文の言語: 英語
Review a GitHub pull request thoroughly — analyze diff for correctness, security, breaking changes, code quality, and AI-slop patterns. Supports --fix to auto-remediate findings and --reply to post the review back to GitHub via the gh CLI as a formal review.
原文の言語: 英語
Generate comprehensive edge cases and test scenarios by decomposing features across 12 dimensions. Use for pre-implementation risk discovery, QA planning, regression design, and iterative saturation when coverage must be exhaustive.
原文の言語: 英語
Fast codebase scouting using native search, optional Explore agents, and user-permitted OpenCode probes. Use for file discovery, task context gathering, and scoped searches across directories.
原文の言語: 英語
Scan codebase for security vulnerabilities, hardcoded secrets, dependency issues, and OWASP patterns. Use when asked to 'security scan', 'check for secrets', 'audit security', or before major releases.
原文の言語: 英語
STRIDE + OWASP-based security audit with optional red-team persona discovery loop and auto-fix. Scans code for vulnerabilities from multiple attacker perspectives (auth attacker, supply chain, insider, infrastructure), categorizes by severity, and can…
原文の言語: 英語
Apply step-by-step analysis for complex problems with revision capability. Use for multi-step reasoning, hypothesis verification, adaptive planning, problem decomposition, course correction.
原文の言語: 英語