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Found 1,691 Skills
Operational prompt engineering for production LLM apps: structured outputs (JSON/schema), deterministic extractors, RAG grounding/citations, tool/agent workflows, prompt safety (injection/exfiltration), and prompt evaluation/regression testing. Use when designing, debugging, or standardizing prompts for Codex CLI, Claude Code, and OpenAI/Anthropic/Gemini APIs.
Expert guidance for working with Dagster and the dg CLI. ALWAYS use before doing any task that requires knowledge specific to Dagster, or that references assets, materialization, or data pipelines. Common tasks may include creating a new project, adding new definitions, understanding the current project structure, answering general questions about the codebase (finding asset, schedule, sensor, component or job definitions), debugging issues, or providing deep information about a specific Dagster concept.
Helps users discover and apply shared coding solutions when they ask "has anyone solved this", "search for a fix", "find a workaround", or want proven patterns before debugging from scratch. Uses `npx shareful-ai search` to find relevant shares, compare options, and recommend the best match.
Pinia Colada expert for Vue 3 — queries, mutations, keys, invalidation, optimistic updates, pagination, and debugging.
Expert guidance for writing fast, maintainable Minitest tests in Rails applications. Use when writing tests, converting from RSpec, debugging test failures, improving test performance, or following testing best practices. Covers model tests, policy tests, request tests, system tests, fixtures, and TDD workflows.
Comprehensive toolkit for validating, linting, testing, and analyzing Helm charts and their rendered Kubernetes resources. Use this skill when working with Helm charts, validating templates, debugging chart issues, working with Custom Resource Definitions (CRDs) that require documentation lookup, or checking Helm best practices.
Instrument Python LLM apps, build golden datasets, write eval-based tests, run them, and root-cause failures — covering the full eval-driven development cycle. Make sure to use this skill whenever a user is developing, testing, QA-ing, evaluating, or benchmarking a Python project that calls an LLM, even if they don't say "evals" explicitly. Use for making sure an AI app works correctly, catching regressions after prompt changes, debugging why an agent started behaving differently, or validating output quality before shipping.
Provides Superwall REST API access, documentation lookup, SDK integration triage, dashboard linking, and SDK source cloning. Use when the user asks about Superwall paywalls, campaigns, subscriptions, API usage, SDK integration, webhook events, or debugging SDK behavior.
Check GitHub Actions workflow status after git push using gh CLI. Reports CI status, identifies failing jobs, and suggests local reproduction commands. Use after "git push", when user asks about CI status, workflow failures, or build results. Use for "check CI", "workflow status", "actions failing", or "build broken". Do NOT use for local linting (use code-linting), debugging test failures locally (use systematic-debugging), or setting up new workflows.
Manages Google Cloud Pub/Sub topics, subscriptions, schemas, and messages safely and efficiently. Use when building or managing event-driven, decoupled systems, streaming data pipelines, or integrating push/pull asynchronous message consumers. Don't use when writing or debugging Google Cloud client library code or raw REST/gRPC API interactions directly.
Code quality orchestrator enforcing TRUST 5 validation, proactive code analysis, linting standards, and automated best practices. Use when performing code review, quality gate checks, lint configuration, TRUST 5 compliance validation, or establishing coding standards. Do NOT use for writing tests (use moai-workflow-testing instead) or debugging runtime errors (use expert-debug agent instead).
Cloudflare Workers observability with logging, Analytics Engine, Tail Workers, metrics, and alerting. Use for monitoring, debugging, tracing, or encountering log parsing, metric aggregation, alert configuration errors.