Encuentra la capacidad perfecta para tu agente.
์นดํผ๋ผ์ดํฐ(copywriter)๊ฐ ์ฌ์ฉํ๋ ์ด๋ฉ์ผ ์นดํผ๋ผ์ดํ ์ ๋ฌธ ์คํฌ. ์ ๋ชฉ์ค ์ฌ๋ฆฌํ, ํ๋ฆฌํค๋ ์ต์ ํ, CTA ์ค๊ณ, ์ค์บ ๊ฐ๋ฅํ ๋ณธ๋ฌธ ๊ตฌ์กฐ ๋ฑ ์ด๋ฉ์ผ ๋งค์ฒด ํนํ ์๋ฌธ ๋ฐฉ๋ฒ๋ก ์ ์ ๊ณตํ๋ค. '์ด๋ฉ์ผ ์นดํผ', '๋ด์ค๋ ํฐ ์์ฑ', '์ ๋ชฉ์ค', 'CTA ์ค๊ณ' ๋ฑ์ ํ์ฉํ๋ค.
๋ด์ค๋ ํฐ ํ๋ ์ด์ , ์์ฑ, A/Bํ ์คํธ, ๋ฐ์ก ์ต์ ํ๋ฅผ ์์ด์ ํธ ํ์ด ํ์ ํ์ฌ ํ ๋ฒ์ ์์ฑํ๋ ํ ํ๋ก๋์ ํ์ดํ๋ผ์ธ. '๋ด์ค๋ ํฐ ์์ฑํด์ค', '๋ด์ค๋ ํฐ ๊ธฐํ', '์ด๋ฉ์ผ ๋ด์ค๋ ํฐ', '๋ด์ค๋ ํฐ ํ๋ ์ด์ ', '๋ด์ค๋ ํฐ A/Bํ ์คํธ', '๊ตฌ๋ ์ ์ด๋ฉ์ผ', '์ํด๋ฆฌ ๋ด์ค๋ ํฐ', '๋ด์ค๋ ํฐ ๋ฐ์ก ์ต์ ํ' ๋ฑ ๋ด์ค๋ ํฐ ์ ์ ์ ๋ฐ์ ์ด ์คํฌ์ ์ฌ์ฉํ๋ค. ๊ธฐ์กด ์ฝํ ์ธ ๊ฐ ์๋ ๊ฒฝ์ฐ์๋ ํธ์งยท์ต์ ํ๋ฅผ ์ง์ํ๋ค. ๋จ, ์ด๋ฉ์ผ ๋ฐ์ก ์์คํ (Mailchimp, Stibee) API ์ฐ๋, ๊ตฌ๋ ์ DB ๊ด๋ฆฌ, ์ค์ A/Bํ ์คํธ ์คํ์ ์ด ์คํฌ์ ๋ฒ์๊ฐ ์๋๋ค.
๊ด๊ณ ์บ ํ์ธ์ ํ๊น๋ถ์, ์นดํผ๋ผ์ดํ , ํฌ๋ฆฌ์์ดํฐ๋ธ ์ค๊ณ, ๋ฏธ๋์ด ํ๋๋์ ์์ด์ ํธ ํ์ด ํ์ ํ์ฌ ํ ๋ฒ์ ์์ฑํ๋ ํ ์บ ํ์ธ ํ์ดํ๋ผ์ธ. '๊ด๊ณ ์บ ํ์ธ ๊ธฐํํด์ค', '๊ด๊ณ ์นดํผ ์จ์ค', '๋ฏธ๋์ด ํ๋ ์ง์ค', '๋ฐฐ๋ ๊ด๊ณ ๋ง๋ค์ด์ค', 'ํ์ด์ค๋ถ ๊ด๊ณ ๊ธฐํ', '๊ฒ์ ๊ด๊ณ ์ธํ ', 'ํ๊น ๋ถ์ํด์ค', '๊ด๊ณ ํฌ๋ฆฌ์์ดํฐ๋ธ', 'SNS ๊ด๊ณ ์ ๋ต' ๋ฑ ๊ด๊ณ ์บ ํ์ธ ์ ์ ์ ๋ฐ์ ์ด ์คํฌ์ ์ฌ์ฉํ๋ค. ๊ธฐ์กด ์นดํผ๋ ํฌ๋ฆฌ์์ดํฐ๋ธ๊ฐ ์๋ ๊ฒฝ์ฐ์๋ ๋ฏธ๋์ด ํ๋๋์ด๋ ๋ฆฌ๋ทฐ๋ฅผ ์ง์ํ๋ค. ๋จ, ์ค์ ๊ด๊ณ ํ๋ซํผ(Google Ads, Meta Business Suite) API ์ฐ๋, ์ค์๊ฐ ์ฑ๊ณผ ๋์๋ณด๋ ๊ตฌ์ถ, ๊ด๊ณ ์์ฌ ์ต์ข ์ ์(ํฌํ ์ต/์ผ๋ฌ์คํธ๋ ์ดํฐ)์ ์ด ์คํฌ์ ๋ฒ์๊ฐ ์๋๋ค.
Convert Figma designs to production-ready React components with Tailwind CSS. Use when user provides a Figma URL, asks to convert Figma designs to React/code, wants to extract components from Figma, or mentions "vibefigma". Requires a Figma access token (via --token flag, FIGMA_TOKEN env var, or .env file).
A full pipeline for transforming legacy codebases into modern architectures. An agent team collaborates to perform technical debt analysis, refactoring strategy formulation, code migration, and regression testing. Use this skill for requests like 'modernize legacy code', 'create a refactoring strategy', 'code migration', 'technical debt analysis', 'legacy system upgrade', 'framework migration', 'code modernization', 'refactoring plan', and other legacy code modernization tasks. Also supports strategy formulation and migration when existing analysis reports are available. Note: actual production deployment, CI/CD pipeline execution, and infrastructure provisioning are outside the scope of this skill.
Airflow DAG pattern, of , retry strategy, etc. , strategy etc. data pipeline orchestration guide. 'Airflow DAG', 'DAG ', 'of', 'retry strategy', 'etc.', '', 'pipeline orchestration', 'Dagster', 'Prefect' etc. pipeline scheduling this for. scheduler-engineerof DAG -ize. , data rule of monitoring dashboard this of scope .
data pipelineof count, transformation, -based, verification, monitoring inthisbefore teamthis to ยทlower pipeline. 'data pipeline ', 'ETL pipeline ', 'data count automatic-ize', 'data lower pipeline', 'ELT ', ' pipeline', 'tree pipeline', 'Airflow DAG only', 'dbt model ', 'data verification ' etc. data pipeline ยท beforein this for. existing pipelineof verificationthis monitoringonly necessary inalso supported. , real-time tree (Flink/Spark Streaming) direct execution, infrastructure provisioning, database administrator(DBA) this of scope .
A full analysis pipeline where an agent team collaborates to perform exploratory data analysis (EDA), data cleaning, statistical analysis, visualization, and report writing. Use this skill for 'analyze this data', 'do EDA', 'exploratory analysis', 'statistical analysis', 'data visualization', 'write an analysis report', 'analyze CSV', 'extract data insights', 'data cleaning', 'outlier analysis', and other data analysis tasks. Note: real-time data streaming, ML model training/deployment, and BI dashboard server construction are outside this skill's scope.
Methodology for systematically designing document chunking strategies for RAG pipelines. Use this skill for 'chunking strategy', 'document splitting', 'RAG chunking', 'embedding optimization', 'semantic chunking', 'text splitting', and other RAG data preprocessing tasks. Note: vector DB infrastructure construction and embedding model training are outside the scope of this skill.
Full pipeline where an agent team collaborates to generate data warehouse design, KPI definitions, visualizations, and automated reports for a BI dashboard. Use this skill for requests like 'build me a BI dashboard', 'dashboard design', 'define KPIs', 'executive reporting dashboard', 'data visualization design', 'report automation', 'data warehouse design', 'build a KPI tree', 'sales dashboard', 'performance metrics framework', and other BI dashboard construction tasks. Also supports visualization or report automation when existing data models or KPI lists are available. Note: direct manipulation of BI tools (Tableau/PowerBI/Looker), database instance creation, and real-time data pipeline operation are outside the scope of this skill.
Airflow DAG ์ค๊ณ ํจํด, ์์กด๊ด๊ณ ๊ด๋ฆฌ, ์ฌ์๋ ์ ๋ต, ๋ฉฑ๋ฑ์ฑ ๋ณด์ฅ, ๋ฐฑํ ์ ๋ต ๋ฑ ๋ฐ์ดํฐ ํ์ดํ๋ผ์ธ ์ค์ผ์คํธ๋ ์ด์ ๊ฐ์ด๋. 'Airflow DAG', 'DAG ์ค๊ณ', '์์กด๊ด๊ณ', '์ฌ์๋ ์ ๋ต', '๋ฉฑ๋ฑ์ฑ', '๋ฐฑํ', 'ํ์ดํ๋ผ์ธ ์ค์ผ์คํธ๋ ์ด์ ', 'Dagster', 'Prefect' ๋ฑ ํ์ดํ๋ผ์ธ ์ค์ผ์ค๋ง ์ ์ด ์คํฌ์ ์ฌ์ฉํ๋ค. scheduler-engineer์ DAG ์ค๊ณ ์ญ๋์ ๊ฐํํ๋ค. ๋จ, ๋ฐ์ดํฐ ํ์ง ๊ท์น ์ ์๋ ๋ชจ๋ํฐ๋ง ๋์๋ณด๋๋ ์ด ์คํฌ์ ๋ฒ์๊ฐ ์๋๋ค.
๋ฐ์ดํฐ ํ์ดํ๋ผ์ธ์ ์์ง, ๋ณํ, ์ ์ฌ, ํ์ง๊ฒ์ฆ, ๋ชจ๋ํฐ๋ง์ ์์ด์ ํธ ํ์ด ํ์ ํ์ฌ ์ค๊ณยท๊ตฌํํ๋ ํ ํ์ดํ๋ผ์ธ. '๋ฐ์ดํฐ ํ์ดํ๋ผ์ธ ์ค๊ณํด์ค', 'ETL ํ์ดํ๋ผ์ธ ๊ตฌ์ถ', '๋ฐ์ดํฐ ์์ง ์๋ํ', '๋ฐ์ดํฐ ์จ์ดํ์ฐ์ค ํ์ดํ๋ผ์ธ', 'ELT ์ค๊ณ', '๋ฐฐ์น ํ์ดํ๋ผ์ธ', '์คํธ๋ฆฌ๋ฐ ํ์ดํ๋ผ์ธ', 'Airflow DAG ๋ง๋ค์ด์ค', 'dbt ๋ชจ๋ธ ์ค๊ณ', '๋ฐ์ดํฐ ํ์ง ๊ฒ์ฆ ์ฒด๊ณ' ๋ฑ ๋ฐ์ดํฐ ํ์ดํ๋ผ์ธ ์ค๊ณยท๊ตฌ์ถ ์ ๋ฐ์ ์ด ์คํฌ์ ์ฌ์ฉํ๋ค. ๊ธฐ์กด ํ์ดํ๋ผ์ธ์ ํ์ง ๊ฒ์ฆ์ด๋ ๋ชจ๋ํฐ๋ง๋ง ํ์ํ ๊ฒฝ์ฐ์๋ ์ง์ํ๋ค. ๋จ, ์ค์๊ฐ ์คํธ๋ฆฌ๋ฐ ์์ง(Flink/Spark Streaming) ์ง์ ์คํ, ํด๋ผ์ฐ๋ ์ธํ๋ผ ํ๋ก๋น์ ๋, ๋ฐ์ดํฐ๋ฒ ์ด์ค ๊ด๋ฆฌ์(DBA) ์ ๋ฌด๋ ์ด ์คํฌ์ ๋ฒ์๊ฐ ์๋๋ค.
Database normalization/denormalization pattern library. An extension skill for data-modeler that provides 1NF-BCNF criteria, functional dependency analysis, step-by-step normalization procedures, strategic denormalization patterns, and common domain ERD templates. Use when data modeling involves 'normalization', 'denormalization', 'ERD patterns', 'functional dependencies', 'table splitting', 'relationship design', etc. Note: DDL generation and query optimization are outside the scope of this skill.
Feature engineering techniques catalog: numeric/categorical/time-series/text transformations, feature selection, feature store design. Use this skill for data preprocessing and feature design involving 'feature engineering', 'variable transformation', 'encoding', 'scaling', 'feature selection', 'feature store', 'feature importance', etc. Enhances the data-engineer's feature engineering capabilities. Note: model design and training management are outside this skill's scope.
A full ML pipeline where an agent team collaborates to perform data preparation, model design, training, evaluation, and deployment readiness. Use this skill for 'design an ML experiment', 'train a model', 'machine learning project', 'build a deep learning model', 'classification model', 'regression model', 'data preprocessing', 'model evaluation', 'hyperparameter tuning', 'MLOps setup', 'XGBoost model', 'PyTorch model', and other ML experiment tasks. Supports data-preprocessing-only or evaluation-only requests as well. Note: model serving infrastructure (SageMaker/Vertex AI) direct deployment, large-scale distributed training cluster management, and real-time inference service operation are outside this skill's scope.
ML model selection matrix by problem type, hyperparameter tuning strategies, and ensemble methodology guide. Use this skill for ML model selection and design involving 'model selection', 'algorithm comparison', 'hyperparameter tuning', 'Optuna', 'ensemble', 'XGBoost vs LightGBM', 'model comparison', 'cross-validation', etc. Enhances the model-designer and evaluation-analyst's model design capabilities. Note: data preprocessing and training infrastructure management are outside this skill's scope.
Methodology for systematically evaluating and optimizing LLM prompt quality. Use this skill for 'prompt optimization', 'prompt improvement', 'guardrail design', 'prompt debugging', 'few-shot optimization', 'system prompt design', and other prompt quality improvement tasks. Note: LLM model fine-tuning and model weight modification are outside the scope of this skill.
ML ์คํ์ ๋ฐ์ดํฐ ์ค๋น, ๋ชจ๋ธ ์ค๊ณ, ํ์ต, ํ๊ฐ, ๋ฐฐํฌ ์ค๋น๋ฅผ ์์ด์ ํธ ํ์ด ํ์ ํ์ฌ ์ํํ๋ ํ ML ํ์ดํ๋ผ์ธ. 'ML ์คํ ์ค๊ณํด์ค', '๋ชจ๋ธ ํ์ตํด์ค', '๋จธ์ ๋ฌ๋ ํ๋ก์ ํธ', '๋ฅ๋ฌ๋ ๋ชจ๋ธ ๋ง๋ค์ด์ค', '๋ถ๋ฅ ๋ชจ๋ธ', 'ํ๊ท ๋ชจ๋ธ', '๋ฐ์ดํฐ ์ ์ฒ๋ฆฌ', '๋ชจ๋ธ ํ๊ฐ', 'ํ์ดํผํ๋ผ๋ฏธํฐ ํ๋', 'MLOps ์ค์ ', 'XGBoost ๋ชจ๋ธ', 'PyTorch ๋ชจ๋ธ' ๋ฑ ML ์คํ ์ ๋ฐ์ ์ด ์คํฌ์ ์ฌ์ฉํ๋ค. ๋ฐ์ดํฐ ์ ์ฒ๋ฆฌ๋ง ํ์ํ๊ฑฐ๋ ๋ชจ๋ธ ํ๊ฐ๋ง ํ์ํ ๊ฒฝ์ฐ์๋ ์ง์ํ๋ค. ๋จ, ๋ชจ๋ธ ์๋น ์ธํ๋ผ(SageMaker/Vertex AI) ์ง์ ๋ฐฐํฌ, ๋๊ท๋ชจ ๋ถ์ฐ ํ์ต ํด๋ฌ์คํฐ ๊ด๋ฆฌ, ์ค์๊ฐ ์ถ๋ก ์๋น์ค ์ด์์ ์ด ์คํฌ์ ๋ฒ์๊ฐ ์๋๋ค.
SQL/NoSQL query optimization pattern, execution plan analysis, index strategy, N+1 resolution etc. database performance optimization guide. 'query optimization', 'execution plan', 'EXPLAIN', 'index ', 'N+1 ', 'slow query', 'slow query', 'DB performance' etc. database query performance improvement this for. bottleneck-analystand optimization-engineerof DB performance analysis -ize. , before system profilingthis benchmark execution this of scope .
Detailed implementation guide for the Strangler Fig pattern and related migration patterns for incrementally replacing legacy systems. Use this skill for 'strangler fig', 'incremental migration', 'refactoring patterns', 'branch by abstraction', 'parallel run', 'gradual replacement', 'migration pattern selection', and other legacy migration pattern applications. Enhances pattern selection and implementation for refactoring-strategist and migration-engineer. Note: full team orchestration and project management are outside the scope of this skill.
