competency-model
역량 모델 설계 프레임워크. jd-writer와 screening-expert 에이전트가 직무별 핵심 역량을 정의하고 평가 기준을 수립할 때 참조. '역량 모델', '직무 역량', '스킬 매트릭스' 요청 시 사용. 단, 인사 평가 시스템 구축이나 급여 체계 설계는 범위 밖.
역량 모델 설계 프레임워크. jd-writer와 screening-expert 에이전트가 직무별 핵심 역량을 정의하고 평가 기준을 수립할 때 참조. '역량 모델', '직무 역량', '스킬 매트릭스' 요청 시 사용. 단, 인사 평가 시스템 구축이나 급여 체계 설계는 범위 밖.
Summarize a CSV, compute basic stats, and produce a markdown report + a plot image.
Проверка консистентности данных в SQLite базах данных MikoPBX после операций REST API. Использовать при валидации результатов API, отладке проблем с данными, проверке связей внешних ключей или инспектировании CDR записей для тестирования.
Integrates Firebase Data Connect into Flutter apps. Use when setting up Data Connect, designing queries, handling errors, or applying security and performance best practices.
Analyze downstream impact of dbt model changes using column-level lineage and the dependency graph. Use when evaluating the blast radius of a change before shipping. Powered by altimate-dbt.
Create and modify dbt models — staging, intermediate, marts, incremental, medallion architecture. Use when building new SQL models, extending existing ones, scaffolding YAML configs, or reorganizing project structure. Powered by altimate-dbt.
Analyze DDL migrations for data loss risks — type narrowing, missing defaults, dropped constraints, breaking column changes. Use before applying schema changes to production.
Applies prompt repetition to improve accuracy for non-reasoning LLMs
Generate validated AWS architecture diagrams as draw.io XML using official AWS4 icon libraries. Use this skill whenever the user wants to create, generate, or design AWS architecture diagrams, cloud infrastructure diagrams, or system design visuals. Also triggers for requests to visualize existing infrastructure from CloudFormation, CDK, or Terraform code. Supports two modes: analyze an existing codebase to auto-generate diagrams, or brainstorm interactively from scratch. Exports .drawio files with optional PNG/SVG/PDF export via draw.io desktop CLI.
Selects a base model and fine-tuning technique (SFT, DPO, or RLVR) for the user's use case by querying SageMaker Hub. Use when the user asks which model or technique to use, wants to start fine-tuning, or mentions a model name or family (e.g., "Llama", "Mistral") — always activate even for known model names because the exact Hub model ID must be resolved. Queries available models, validates technique compatibility, and confirms selections.
Generates a Jupyter notebook that fine-tunes a base model using SageMaker serverless training jobs. Use when the user says "start training", "fine-tune my model", "I'm ready to train", or when the plan reaches the finetuning step. Supports SFT, DPO, and RLVR trainers, including RLVR Lambda reward function creation.
Generates a Jupyter notebook that evaluates a fine-tuned SageMaker model using LLM-as-a-Judge. Use when the user says "evaluate my model", "how did my model perform", "compare models", or after a training job completes. Supports built-in and custom evaluation metrics, evaluation dataset setup, and judge model selection.
Reflect, Evaluate, Fine-tune, Learn, Evolve, Correct, Transform — nightly automated performance review
Invoke IMMEDIATELY via python script to stress-test decisions and reasoning. Do NOT analyze first - the script orchestrates the critique workflow.
Invoke IMMEDIATELY via python script when user requests prompt optimization. Do NOT analyze first - invoke this skill immediately.
Analyze weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Plan a new feature end-to-end — impact analysis across all layers before delegating to /domain, /read-model, /controller skills