> browse/registry

> artillery

When the user wants to perform load testing or performance testing using Artillery with YAML-based scenario definitions. Also use when the user mentions "artillery," "YAML load test," "WebSocket testing," "Socket.io load test," "scenario-based load testing," or "artillery run." For JavaScript-based load testing, see k6.

> soda

You are an expert in Soda, the data quality platform for testing, monitoring, and profiling data. You help developers write data quality checks in YAML that validate freshness, completeness, uniqueness, validity, and business rules — catching data issues before they reach dashboards and ML models.

> capacity-planner

Translates performance test results into infrastructure scaling recommendations with cost estimates. Use when someone has load test data and needs to know what infrastructure changes are required to handle target traffic. Trigger words: capacity planning, scaling plan, infrastructure sizing, how many pods, RDS sizing, handle more traffic, scale for launch.

> locust

When the user wants to perform load testing using Python with Locust's distributed architecture and real-time web UI. Also use when the user mentions "locust," "Python load testing," "distributed load test," "locust web UI," or "locustfile." For JavaScript-based load testing, see k6 or artillery.

> api-load-tester

Generates and executes load test scripts for APIs using k6, wrk, or autocannon. Creates realistic test scenarios from OpenAPI specs, route files, or endpoint descriptions. Use when someone needs to load test, stress test, benchmark, or find the breaking point of their API. Trigger words: load test, stress test, benchmark, RPS, concurrent users, breaking point, performance test, k6, wrk.

> ai-eval-ci

Run AI agent and LLM evaluations in CI/CD pipelines — automated quality gates that fail the build when AI output quality drops. Use when someone asks to "test my AI agent", "add evals to CI", "catch prompt regressions", "compare models", "evaluate LLM output quality", "set up AI quality gates", or "benchmark my agent before deploying". Covers eval frameworks (Cobalt, Promptfoo, Braintrust), LLM-as-judge scoring, threshold-based assertions, and GitHub Actions integration.

> promptfoo

Test and evaluate LLM prompts systematically with Promptfoo — open-source eval framework. Use when someone asks to "test my prompts", "evaluate LLM output", "Promptfoo", "prompt regression testing", "compare LLM models", "LLM evaluation framework", or "benchmark prompts against test cases". Covers test cases, assertions, model comparison, red-teaming, and CI integration.

> axiom-grdb

Use when writing raw SQL queries with GRDB, complex joins, ValueObservation for reactive queries, DatabaseMigrator patterns, query profiling under performance pressure, or dropping down from SQLiteData for performance - direct SQLite access for iOS/macOS

> wp-performance

Use when investigating or improving WordPress performance (backend-only agent): profiling and measurement (WP-CLI profile/doctor, Server-Timing, Query Monitor via REST headers), database/query optimization, autoloaded options, object caching, cron, HTTP API calls, and safe verification.

> analyzing-marketing-campaign

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.

> axiom-ios-performance

Use when app feels slow, memory grows, battery drains, or diagnosing ANY performance issue. Covers memory leaks, profiling, Instruments workflows, retain cycles, performance optimization.

> database-performance

Database access patterns for performance. Separate read/write models, avoid N+1 queries, use AsNoTracking, apply row limits, and never do application-side joins. Works with EF Core and Dapper.

> running-load-tests

This skill enables Claude to create and execute load tests for performance validation. It is designed to generate load test scripts using tools like k6, JMeter, and Artillery, based on specified test scenarios. Use this skill when the user requests to create a "load test", conduct "performance testing", validate "application performance", or needs a "stress test" to identify breaking points in the application. The skill helps define performance thresholds and provides execution instructions.

> chrome-devtools

Browser debugging, performance profiling, and automation via Chrome DevTools MCP. Use when user says "debug this page", "take a screenshot", "check network requests", "profile performance", "inspect console errors", or "analyze page load". Do NOT use for full E2E test suites (use playwright-skill) or non-browser debugging.

> performance-testing-review-multi-agent-review

Use when working with performance testing review multi agent review

> profiling-application-performance

This skill enables Claude to profile application performance, analyzing CPU usage, memory consumption, and execution time. It is triggered when the user requests performance analysis, bottleneck identification, or optimization recommendations. The skill uses the application-profiler plugin to identify performance bottlenecks and suggest code-level optimizations. Use it when asked to "profile application", "analyze performance", or "find bottlenecks". It is also helpful when the user mentions spe

> coreml-ref

CoreML API reference - MLModel lifecycle, MLTensor operations, coremltools conversion, compression APIs, state management, compute device availability, performance profiling.

> llm-evaluation

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.

> agent-orchestration-multi-agent-optimize

Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.

> Performance Engineering Standards

Universal standards for high-performance development. Use when optimizing, reducing latency, fixing memory leaks, profiling, or improving throughput.