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Found 145 Skills
Guided entry point for using Sentry through your agent. Orients you to your current setup and, for a new project, sets up Sentry end to end with sane defaults — provision a project, install the SDK (errors, tracing, and whatever it enables by default), and confirm real telemetry reaches Sentry. Routes other intents (adding more signals, fixing issues) to the right skill.
Configures Google Cloud Build pipelines with caching, parallel builds, and optimization. Use when setting up Cloud Build, optimizing build performance, or configuring CI/CD pipelines.
Design ETL/ELT pipelines with proper orchestration, error handling, and monitoring. Use when building data pipelines, designing data workflows, or implementing data transformations.
Configures nginx load balancing with upstream servers, health checks, and failover strategies. Use when setting up load balancing, distributing traffic across multiple servers, or configuring upstream backends.
Validates dataset formatting and quality for SageMaker model fine-tuning (SFT, DPO, or RLVR). Use when the user says "is my dataset okay", "evaluate my data", "check my training data", "I have my own data", or before starting any fine-tuning job. Detects file format, checks schema compliance against the selected model and technique, and reports whether the data is ready for training or evaluation.
Sync Telegram messages to local storage. Use when user asks to sync, pull, fetch, or download Telegram messages.
Implement Go error handling patterns including error wrapping, sentinel errors, custom error types, and error handling conventions. Use when handling errors, creating error types, or implementing error propagation. Trigger words include "error", "panic", "recover", "error handling", "error wrapping".
Maintains changelogs following Keep a Changelog format, categorizes changes by type. Use when updating CHANGELOG, preparing releases, or documenting version changes.
Validates CloudFormation templates for syntax, security, and best practices. Use when validating CloudFormation templates, checking for security issues, or ensuring compliance with best practices.
Comprehensive web page validation with authentication, screenshot capture, mobile testing, and enhanced error detection
Initialize and onboard a new project repository as an Obsidian Vault. Covers prerequisite installation, vault configuration, exclusion filters, and validation. Use when setting up Obsidian for the first time in a project.
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.