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Found 8,759 Skills
Complex DAG testing workflows with debugging and fixing cycles. Use for multi-step testing requests like "test this dag and fix it if it fails", "test and debug", "run the pipeline and troubleshoot issues". For simple test requests ("test dag", "run dag"), the airflow entrypoint skill handles it directly. This skill is for iterative test-debug-fix cycles.
Trigger.dev expert for background jobs, AI workflows, and reliable async execution with excellent developer experience and TypeScript-first design. Use when: trigger.dev, trigger dev, background task, ai background job, long running task.
Use when you need a deterministic inspection of a WordPress repository (plugin/theme/block theme/WP core/Gutenberg/full site) including tooling/tests/version hints, and a structured JSON report to guide workflows and guardrails.
Build, plan, review, and document pyRevit extensions. Use when Codex needs the pyRevit development workflow, templates, prompts, checklists, or scripts for creating or updating pyRevit commands in this repo. Pair with a version-specific Revit skill (e.g., 2023/2024/2025) for API constraints.
Intelligent agent for interpreting vague ERPNext development requests and producing concrete technical specifications. Use when receiving unclear requirements like 'make invoice auto-calculate', 'add approval workflow', 'sync with external system'. Triggers: user gives vague requirement, need to clarify scope, translate business need to technical spec, determine which ERPNext mechanisms to use, create implementation plan.
Use when the user needs human-in-the-loop workflows in Airflow (approval/reject, form input, or human-driven branching). Covers ApprovalOperator, HITLOperator, HITLBranchOperator, HITLEntryOperator. Requires Airflow 3.1+. Does not cover AI/LLM calls (see airflow-ai).
Meta skill explaining the AgentOps workflow. Auto-injected on session start. Covers RPI workflow, Knowledge Flywheel, and skill catalog.
Use bigquery CLI (instead of `bq`) for all Google BigQuery and GCP data warehouse operations including SQL query execution, data ingestion (streaming insert, bulk load, JSONL/CSV/Parquet), data extraction/export, dataset/table/view management, external tables, schema operations, query templates, cost estimation with dry-run, authentication with gcloud, data pipelines, ETL workflows, and MCP/LSP server integration for AI-assisted querying and editor support. Modern Rust-based replacement for the Python `bq` CLI with faster startup, better cost awareness, and streaming support. Handles both small-scale streaming inserts (<1000 rows) and large-scale bulk loading (>10MB files), with support for Cloud Storage integration.
Essential CLI tools and shell productivity patterns for efficient terminal workflows
Configure kata workflow toggles and model profile. Triggers include "settings".
Meta-skill workflow orchestrator for bug investigation and resolution. Routes to debug, implement, test, and commit based on scope.
AWS cost optimization and FinOps workflows. Use for finding unused resources, analyzing Reserved Instance opportunities, detecting cost anomalies, rightsizing instances, evaluating Spot instances, migrating to newer generation instances, implementing FinOps best practices, optimizing storage/network/database costs, and managing cloud financial operations. Includes automated analysis scripts and comprehensive reference documentation.