Skills
AI agent Skills için açık kayıt: önerilen modeller, örnek prompt'lar ve uyumlu araçlar içeren yapılandırılmış prompt'lar ve iş akışları.
Skills
37
Kategoriler
9
Uyumlu araçlar
5
Katkıda bulunanlar
1
Turns raw meeting transcripts or rough notes into clear, structured summaries. Extracts key decisions, action items with owners and due dates, open questions, and discussion highlights. Produces a concise recap suitable for sharing, plus an optional follow-up email draft.
Transforms feature ideas and product requirements into well-formed agile user stories with clear acceptance criteria. Follows the "As a / I want / so that" format, adds Gherkin-style Given/When/Then criteria, estimates relative complexity, and breaks epics into right-sized stories ready for sprint planning.
Classifies the sentiment and emotional tone of text — reviews, support tickets, social posts, and survey responses. Supports document-level and aspect-based sentiment, returns confidence scores and representative quotes, and aggregates trends across large batches with themes and actionable insights.
Summarizes web pages, PDFs, articles, and documents into concise, structured summaries. Extracts key points, main arguments, data, and conclusions. Supports multiple output formats including bullet points, executive summaries, and structured notes with citations.
Fetches current weather conditions and forecasts for any location using free public APIs. Provides temperature, humidity, wind, precipitation probability, and multi-day forecasts. Useful for agents that need environmental context for travel planning, event scheduling, or outdoor activity recommendations.
Facilitates structured brainstorming sessions using proven ideation frameworks — SCAMPER, Six Thinking Hats, How Might We, Crazy Eights, and more. Generates diverse ideas, challenges assumptions, and helps converge on the strongest concepts.
Rewrites vague or technical error messages into clear, actionable user-facing messages. Considers the audience (end-user vs developer), suggests error codes, and provides guidance on what the user can do to resolve the issue.
Generates structured changelogs from git history, commit messages, or PR descriptions. Follows Keep a Changelog format, groups changes by type (Added, Changed, Fixed, Removed), and highlights breaking changes. Supports semantic versioning recommendations.
Drafts professional emails for various business contexts — follow-ups, introductions, requests, escalations, and announcements. Adapts tone from formal to friendly based on audience and relationship. Keeps messages concise and action-oriented.
Generates realistic test data, fixtures, and seed files for databases and APIs. Creates data that respects constraints (foreign keys, unique fields, valid formats) and covers edge cases. Supports JSON, SQL, CSV, and factory patterns.
Explains complex code in plain language at the requested level of detail. Breaks down algorithms, design patterns, and architecture decisions. Adapts explanation depth from high-level overview to line-by-line walkthrough based on audience.
Generates .env files, configuration schemas, and environment variable documentation from application requirements. Includes validation rules, default values, required vs optional flags, and example values. Supports multiple environments (dev/staging/prod).
Builds and explains cron expressions from natural language schedules. Supports standard cron (5-field), extended cron (6-field with seconds), and cloud-specific formats (AWS EventBridge, Google Cloud Scheduler). Validates expressions and shows next run times.
Generates clear, structured pull request descriptions from code diffs. Includes summary of changes, motivation, testing notes, and reviewer guidance. Follows team conventions and links related issues automatically.
Builds, explains, and tests regular expressions from natural language descriptions. Supports multiple regex flavors (PCRE, JavaScript, Python, Go). Provides step-by-step breakdowns, test cases, and performance considerations for complex patterns.
Generates clear, conventional commit messages from code diffs. Follows Conventional Commits specification with appropriate type prefixes, scopes, and descriptions. Handles breaking changes, multi-file changes, and produces both concise subjects and detailed bodies.
Skills ve MCP sunucuları
aralarındaki fark nedir?Skills“ne yapılacağı”
Bir Skill; talimatları, örnek prompt'u ve önerilen modelleri paketleyerek agent'ın görevi tutarlı şekilde yapmasını sağlar. Skills yeni bağlantılar değil, bilgi ekler.
MCP sunucuları“nasıl bağlanılacağı”
Bir MCP sunucusu, gerçek sistemlere (veritabanları, API'ler ve dosyalar) bir taşıma yöntemi üzerinden bağlanarak agent'a yeni yetenekler kazandırır. MCP görev talimatları değil, bağlantılar ve eylemler ekler.
Kısa kural: modelin bir görevi iyi yapması gerekiyorsa Skill, bir araca veya sisteme erişmesi gerekiyorsa MCP sunucusu kullanın. Birlikte çalışabilirler; Skill, MCP sunucusunun sunduğu araçlardan yararlanabilir.
Faydalı bir Skill mi geliştirdiniz?
Bir SKILL.md gönderin; açık kaynaklıdır ve topluluk tarafından sürdürülür.