Run Maestro YAML flows against a Limrun cloud iOS simulator with `lim ios maestro`, from any environment (Linux, Windows, macOS, VM, container).
Configure CI/CD pipelines for testing Lindy AI agent integrations. Use when setting up automated testing, configuring GitHub Actions for webhook receiver tests, or validating…
Create your first Lindy AI agent with a real trigger and action. Use when starting with Lindy, testing your setup, or learning basic agent workflow patterns.
Create a minimal working Lindy AI agent example. Use when starting a new Lindy integration, testing your setup, or learning basic Lindy API patterns.
Create a minimal working Lindy AI agent example. Use when starting a new Lindy integration, testing your setup, or learning basic Lindy API patterns.
Set up local development workflow for testing Lindy AI agent integrations. Use when building webhook receivers, testing agent callbacks, or iterating on Lindy-connected…
Integrate Linear with GitHub Actions CI/CD pipelines. Use when setting up automated testing, PR-to-issue linking, or creating Linear issues from CI failures.
Set up local Linear development environment and testing workflow. Use when configuring local dev, testing integrations, or setting up a development workflow with Linear webhooks.
Use when adding or enforcing lint rules as part of a test or verification plan. Extends testing-strategy with lint-specific guidance: rule selection, gate placement, failure…
Investigate ONE failed or expensive factory trajectory and prove whether a fix helped. Records the job contract, observes the baseline, locates the earliest failed handoff,…
Add the Lite-Basic (Tier 2) sprite atlas to an EXISTING Codogotchi pet that already has a Codex `spritesheet.webp`.
Testing patterns for litefs-py and litefs-django. Use when writing tests, setting up fixtures, understanding test organization, or configuring pytest marks.
Use when building real-service end-to-end tests with fixtures, cleanup, rate limits, and evidence. Triggers:
Comprehensive guide for building functional tools for LiveKit voice agents using the @function_tool decorator.
LLM evaluation harness for accuracy benchmarking. MMLU/HumanEval/MATH eval runners, model-graded scoring, prompt regression testing, and per-skill accuracy tracking.
Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing. — from whatamelon/AGENT-HARNESS-BASELINE
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
LLM testing and evaluation tools including promptfoo, trulens, and evals frameworks
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing. — from majiayu000/claude-skill-registry
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking.
Comprehensive guide to using LLMs throughout the game development lifecycle - from design to implementation to testingUse when "ai game development, llm game dev, claude game, gpt…
LLM gateway and routing configuration using OpenRouter and LiteLLM. Invoke when: - Setting up multi-model access (OpenRouter, LiteLLM) - Configuring model fallbacks and r — from…
LLM gateway and routing configuration using OpenRouter and LiteLLM. Invoke when: - Setting up multi-model access (OpenRouter, LiteLLM) - Configuring model fallbacks and r — from…
LLM inference load testing for throughput and concurrency limits. Token/s benchmarks, concurrent request sweeps, latency-vs-throughput curves, and breaking-point identification.
Testing LLM-powered features including output quality validation, hallucination detection, token usage monitoring, and prompt regression testing.
Creates test documentation (testing-strategy.md, tests/README.md) with Risk-Based Testing philosophy. Use when setting up test strategy for a project.
Executes test tasks (label 'tests') through Todo to To Review with risk-based limits. Use for test task execution. Not for implementation tasks.
Orchestrates test planning pipeline (research → manual → auto tests). Coordinates ln-511, ln-512, ln-513. Invoked by ln-500-story-quality-gate.
Performs manual testing of Story AC via executable bash scripts saved to tests/manual/. Creates reusable test suites per Story. Worker for ln-510.
Plans automated tests (E2E/Integration/Unit) using Risk-Based Testing after manual testing. Calculates priorities, delegates to ln-301-task-creator. Worker for ln-510.
Analyzes application logs: classifies errors, checks log quality, maps stack traces to source. Use when logs need review after test runs or during development.
Orchestrates test planning pipeline: research, manual testing, automated test planning. Use when Story needs comprehensive test coverage planning.
Performs manual testing of Story AC via executable bash scripts in tests/manual/. Use when Story implementation needs hands-on AC verification.
Plans automated tests (E2E/Integration/Unit) using Risk-Based Testing after manual testing. Use when Story needs a test task with prioritized scenarios. — from engineering/testing
Use when auditing the test surface through the evaluation platform with mandatory research, coordinated test audit workers, and structured summaries.
Detects tests validating framework/library behavior instead of project code. Use when auditing test business logic focus.
Validates E2E coverage for critical paths (money, security, data integrity). Risk-based prioritization. Use when auditing E2E test coverage.
Scores each test by Impact x Probability, returns KEEP/REVIEW/REMOVE decisions. Use when auditing test value and pruning low-value tests.
Identifies missing tests for critical paths (money, security, data integrity, core flows). Use when auditing test coverage gaps.
Checks test isolation (API/DB/FS/Time/Network), determinism, flaky tests, order-dependency, anti-patterns. Use when auditing test isolation.
Checks manual test scripts for harness adoption, golden files, fail-fast, config sourcing, idempotency. Use when auditing manual test quality.
Checks test file organization, directory layout, test-to-source mapping, domain grouping, co-location. Use when auditing test structure.
Audits assertion strength and test oracles that prove real defects. Use when finding weak tests that execute code but prove little.
Sets up test infrastructure with Vitest, xUnit, and pytest. Use when adding testing frameworks and sample tests to a project.
Executes all test suites and reports results with coverage. Use when verifying that test infrastructure works after bootstrap.
Executes optimization hypotheses with keep/discard testing loop. Use when applying validated performance improvements.
Replaces custom modules with OSS packages using atomic keep/discard testing. Use when migrating custom code to established libraries.
Disposable Lightning wallets via lncurl.lol. Use for temporary wallets, testing, or bootstrapping child agents.
Testing load balancer configurations including health check validation, routing algorithms, session affinity, failover behavior, and SSL termination.
Design a defensible load test — a realistic workload model, a deliberate test type, and SLO-tied pass/fail thresholds — instead of a meaningless tight-loop script that hammers one…