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Found 816 Skills
Design comprehensive Python test suites including unit, integration, and E2E tests. Use when establishing testing patterns for new or existing Python applications.
Defines caching strategies with cache keys, TTL values, invalidation triggers, consistency patterns, and correctness checklist. Provides code examples for Redis, CDN, and application-level caching. Use when implementing "caching", "performance optimization", "cache strategy", or "Redis caching".
Analyzes disease patterns and health events through epidemiological lens using surveillance systems, outbreak investigation methods, and disease modeling frameworks. Provides insights on disease spread, risk factors, prevention strategies, and public health interventions. Use when: Disease outbreaks, health policy evaluation, risk assessment, intervention planning. Evaluates: Transmission dynamics, risk factors, causality, population health impact, intervention effectiveness.
Expert in Jungian analytical psychology, depth psychology, shadow work, archetypal analysis, dream interpretation, active imagination, addiction/recovery through Jungian lens, and the individuation process.
Analyzes living systems and biological phenomena through biological lens using evolution, molecular biology, ecology, and systems biology frameworks. Provides insights on mechanisms, adaptations, interactions, and life processes. Use when: Biological systems, health issues, evolutionary questions, ecological problems, biotechnology. Evaluates: Function, structure, heredity, evolution, interactions, molecular mechanisms.
Use when planning a multi-article content strategy from a research corpus, creating domain maps for content topology, building production plans for pillar and cluster articles, or tracking cross-article production.
Use when evaluating AI tools and agentic workflows against workflow gaps, when conducting quarterly landscape scans, or when assessing integration feasibility of new tools for startup workflows.
Discover and install related skills from inference.sh skill registry. Helps find complementary skills for your AI workflow. Use for: skill discovery, workflow expansion, capability exploration. Triggers: related skills, find skills, skill discovery, complementary skills, expand workflow, more capabilities, similar skills, skill suggestions
This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini Enterprise", "publish to Gemini Enterprise", or needs guidance on the agents-cli publish gemini-enterprise command. Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, and troubleshooting. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for deployment (use google-agents-cli-deploy).
Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines. Triggers: "azure-ai-ml", "MLClient", "workspace", "model registry", "training jobs", "datasets".
Use ONLY when creating NEW registrable components in ML projects that require Factory/Registry patterns. ✅ USE when: - Creating a new Dataset class (needs @register_dataset) - Creating a new Model class (needs @register_model) - Creating a new module directory with __init__.py factory - Initializing a new ML project structure from scratch - Adding new component types (Augmentation, CollateFunction, Metrics) ❌ DO NOT USE when: - Modifying existing functions or methods - Fixing bugs in existing code - Adding helper functions or utilities - Refactoring without adding new registrable components - Simple code changes to a single file - Modifying configuration files - Reading or understanding existing code Key indicator: Does the task require @register_* decorator or Factory pattern? If no, skip this skill.
Track ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow - framework-agnostic ML lifecycle platform