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Found 4,132 Skills
Redis observability guidance — which metrics to monitor (memory, connections, hit ratio, ops/sec, rejected connections), which built-in commands to reach for during incident triage (SLOWLOG, INFO, MEMORY DOCTOR, CLIENT LIST, FT.PROFILE), and when to use the Redis Insight GUI. Use when setting up monitoring or alerts for a Redis instance, diagnosing a performance regression, profiling a slow FT.SEARCH query, or wiring Redis metrics into Prometheus, Datadog, or similar.
Enforces vendor-neutral UTM naming conventions by validating marketing links and generating a normalized, policy-compliant output.
Decision frameworks for DatoCMS content modeling — schema shape, field choice, content reuse, taxonomies, content vs presentation, admin UI organization. Use for modeling *decisions*, not implementation: model vs block; single_block vs Modular Content vs Structured Text; references vs embedded blocks; taxonomy shape (flat/tree/faceted); refactoring page-shaped schemas to reusable content; fitting 300 KB / 500-block / 5-level record limits; model behaviour (singleton, draft mode, all_locales_required, sortable/tree/ordering_field, presentation_title_field, collection_appearance, inverse_relationships_enabled); field config (validator + appearance — enum + string_select, slug auto-fill, required_alt_title, structured_text allowlists, framed vs frameless single_block). Also schema review (reuse, editor ergonomics, omnichannel). *Creating* schema → `datocms-cli` or `datocms-cma`. Query/render → `datocms-cda` + `datocms-frontend-integrations`. Validators + cascade: `datocms-cma/references/schema.md`.
Bootstrap evaluators from production traces — emit SDK code, a framework-agnostic JSON spec, or publish online LLM-judge evaluators directly to Datadog. Use when user says "bootstrap evaluators", "generate evaluators", "create evals from traces", "eval bootstrap", "write evaluators", "build eval suite", "publish evaluators", or wants to generate BaseEvaluator/LLMJudge code or online judge configs from production LLM trace data. Works with ml_app and optional RCA report or failure hypothesis.
Designs user experiences and interfaces grounded in research. Use when creating user journeys, wireframes, prototypes, or improving usability. Use for information architecture, interaction design, accessibility audits, design system creation, and developer handoff.
Design, audit, and refactor production-safe agentic harnesses with provider-neutral best practices for tools, permissions, planning, context, and observability.
Build AI-driven security operations automation with ASP's agent-centric SIRP, modules, and playbooks
Bootstrap a fresh Ubuntu VPS into a complete multi-agent AI development environment with safety tools and coordination infrastructure in 30 minutes
Enable AI agents to safely make real-world merchant purchases using Snaplii's tokenized gift card payment layer with up to 10% savings.
Context layer for AI data agents - teach Claude Code, Codex, and AI agents to query data warehouses accurately with semantic layer, wiki knowledge, and MCP tools
Automatically monitors OKX Flash Earn, Fixed Earn and Flexible Earn opportunities, sends push notifications, and guides subscription. 自动监控 OKX 闪赚、定期和活期赚币机会，推送通知并引导申购。Use when user says: 有闪赚通知我, 监控赚币, monitor earn, notify me about earn, 定时检查理财, 执行 earn-hunter 扫描, earn-hunter scan, 活期年化高了通知我, 监控活期.
Build a survival-crafting game: resource gathering, inventory, crafting and a tech tree, needs (hunger/thirst/temperature), and base building. Use for a survival or crafting/base-building game.