Performance and load testing with k6, locust, JMeter, Gatling, and artillery. Use for load/stress/spike/soak tests, API and database benchmarking, profiling, p95/p99 latency analysis, throughput measurement, and bottleneck identification.
REQUIRED skill for creating Loom execution plans. Designs DAG-based plans with mandatory knowledge-bootstrap and integration-verify bookends, parallel subagent execution within stages, and concurrent worktree stages for maximum throughput.
Prometheus monitoring and alerting for cloud-native observability. Use for writing PromQL queries, configuring scrape targets, creating alerting and recording rules, instrumenting applications, and setting up service discovery. Not for dashboards (use loom-grafana) or log analysis (use loom-logging-observability).
Designs and optimizes prompts for large language models including system prompts, agent signals, and few-shot examples. Use for instruction design, prompt security, reasoning-task decomposition, and in-context learning for orchestrated agents.
Python language expertise for idiomatic, production-quality code. Use for web frameworks (FastAPI, Django, Flask), data processing (pandas, numpy), ML patterns (sklearn, pytorch), async programming, type hints, pytest, packaging with uv/poetry, and linting with ruff/mypy/black.
API rate limiting and quota management. Use when implementing request throttling, API quotas, backpressure handling, or abuse protection. Covers token bucket, leaky bucket, sliding/fixed window algorithms, and distributed rate limiting with Redis.
Modern client-side React development patterns. Use for React 19+ SPAs with components, Hooks, Jotai state, React Router v7, accessibility, performance optimization, and testing on the Bun + Vite + Oxc (oxlint/oxfmt) toolchain. Covers client-side routing, composition, and async data loading; not framework-specific SSR…
Restructures existing code to improve readability, maintainability, and performance without changing behavior. Use for extracting methods/classes, removing duplication, applying design patterns, improving organization, and reducing technical debt. Not for bug fixes (use loom-debugging) or new features.
Rust language expertise for idiomatic, production-quality code. Use for ownership and lifetimes, error handling with anyhow/thiserror, async/await with tokio, cargo workspace management, CLI tools with clap, and serialization with serde. Primary language of the Loom project.
Full-text search and search engine implementation. Use when implementing search functionality, autocomplete, faceted search, relevance tuning, or working with search indexes like Elasticsearch, OpenSearch, Meilisearch, or Typesense.
Comprehensive security audits identifying vulnerabilities, misconfigurations, and best-practice violations across applications, APIs, infrastructure, and data pipelines. Use for OWASP Top 10 reviews, compliance assessments (SOC2, PCI-DSS, HIPAA, GDPR), threat modeling, risk assessment, and hardening.
Quick routine security checks for secrets, dependencies, container images, and common vulnerabilities. Use for lightweight pre-commit and CI scans with tools like Semgrep, Trivy, gitleaks, cargo audit, npm audit, and pip-audit. Not a substitute for deep audits (use loom-security-audit).