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Found 6,367 Skills
Validate database integrity, test migrations forward and backward, verify schema constraints, manage seed data, detect migration drift, and identify query performance issues. Covers PostgreSQL, MySQL, MongoDB with Prisma, TypeORM, Drizzle, and SQLAlchemy, plus Testcontainers test databases. Use when: "database test," "migration test," "migration rollback," "rollback test," "data integrity," "SQL test," "schema validation," "seed data," "query performance," "Testcontainers." Not for: synthetic data generation/masking at scale — use test-data-management; Docker/IaC test-environment provisioning — use test-environments; SQL injection — use security-testing. Related: test-data-management, test-environments, security-testing, ci-cd-integration.
AWS Startups reference content — Activate FAQ, credits guide, programs, partner offers, sample architectures, and hundreds of learn articles spanning generative AI, cloud architecture, cost optimization, security, fundraising, go-to-market, and real-world startup case studies. Use when the user asks factual questions about AWS Activate (eligibility, credits, programs, providers), wants a sample architecture or solution guide, or needs an AWS-curated learn article on a specific startup topic. For copy-paste AI prompts (RAG chatbot, MVP scaffold, security baseline, GPU quota, etc.), see the prompt-library-for-startups skill. Do not use for: account-specific lookups (credits balance, Activate membership status, application status), real-time event listings beyond the events stub, or content not present in the bundled `references/` tree.
Migrate workloads from Google Cloud Platform to AWS — including AI and agentic workloads regardless of cloud provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, Google Cloud migration, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform files, app code, or billing exports, clarify migration requirements, design AWS architecture, estimate costs, generate migration artifacts, and collect optional feedback. Clarify must finish before Design, Estimate, or Generate. Includes AI provider migration guidance (for example, OpenAI to Amazon Bedrock) by selecting closest-fit Bedrock model families for required modality, latency/quality targets, context windows, and cost constraints. Model mapping is compatibility-guided, not 1:1 parity; validate prompts, tool-calling behavior, and eval metrics before cutover. Do not use for: Azure or on-premises migrations to AWS, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, GCP-to-GCP refactoring, or multi-cloud deployments that do not involve migrating off GCP.
Rigorously evaluate an Agent Skill end-to-end across ANY coding-agent CLI — verify its scripts emit the documented numbers (deterministic checks), test whether its description triggers on the right prompts, and measure whether an agent following the SKILL.md beats a no-skill baseline (with/without pass-rate delta, mean ± stddev, benchmarked). Use whenever you need to test, benchmark, validate, grade, or quantify a skill's quality, check if a skill "actually works," compare two skill versions, optimize a skill's triggering, or set up an eval suite — even if the user just says "is this skill any good," "does my skill work," or "benchmark this skill." Drives Claude Code, OpenAI Codex, Antigravity (agy), Cursor, GitHub Copilot, Amp, opencode, or Grok in headless mode.
Identify which field values correlate with bad behavior (slowness, errors, anomalies, unusual values) using phi-coefficient correlation analysis over OPAL. Works on any time-series data — metrics, structured logs, span/trace data, or any dataset where rows can be split into a 'bad' and 'good' cohort by a threshold. Use when: (1) User asks for root-cause analysis on a dataset or metric (2) User wants to know what attributes / dimensions / values are most associated with a failure mode, anomaly, or unusual cohort (3) Investigating which services, hosts, regions, namespaces, or attributes drive outliers (4) User mentions phi coefficient, correlation, or outlier detection (5) User asks 'why is X slow/failing', 'what caused the errors on X', or 'what's different about the bad cohort'.
This skill should be used when the user asks to "make this animation feel natural", "fix motion that feels stiff/floaty/cheap", "my animation looks robotic", "choose an easing curve", "how do I use the Graph Editor", "add overshoot or bounce", "Easy Ease isn't enough", "make snappy motion", "pick a duration for this transition", "stagger a list animation", "sync animation to a beat", or "review motion for good timing". It is the tech-agnostic foundation for deciding how something should move.
Optimize an app's store listing for maximum visibility and downloads — keyword strategy, title and subtitle optimization, screenshots, preview videos, rating and review management, and A/B testing on the App Store (iOS) and Google Play (Android). Use when the user says "ASO", "app store optimization", "optimize my app listing", "improve app store ranking", "app store keywords", "app store screenshots", "app store rating", "Google Play optimization", "app visibility", "increase app downloads", "app store SEO", "app store conversion", "my app isn't getting downloads", or wants to improve how their app appears and converts in the App Store or Google Play.
The idea-system craft — never run out of content ideas by running a system instead of waiting for inspiration. Use when someone is out of ideas, stares at a blank calendar, asks where good ideas come from, wants an idea bank/backlog, feels their AI-generated ideas sound like everyone else's, or thinks their niche is "boring." Uses the SPARK framework. Reads brand-profile + social-strategy + content-pillars + audience-research first. The audience is the idea engine (comments/DMs/FAQs clustered into themes); AI expands real signals, it doesn't discover them; systems beat muses; trends are a timing filter, not a source. The agent clusters/expands/scores; the HUMAN supplies proprietary signals and decides; WoopSocial publishes the content, not ideas. Never rewords competitor posts, invents audience questions, or fabricates probe results. Distinct from social-strategy/content-pillars, audience-research, cross-platform-repurposing/ content-recycling, and the format skills.
Query OpenSea marketplace data — listings, offers, sales / events, floor prices, collection stats, drops, traits — and execute Seaport trades via the official `@opensea/cli` and OpenSea REST API across Ethereum, Base, Arbitrum, Optimism, Polygon, and more. Includes search across collections / NFTs / tokens / accounts. NOT for general NFT metadata reads (name, image, traits, ownership), token metadata, current wallet balances, transaction history, or live RPC reads — for those use `alchemy-cli` (live), `alchemy-mcp`, `alchemy-api` (app code), or `agentic-gateway` (no API key). For pure cross-chain token swaps (no marketplace context), prefer the `lifi` ecosystem skill. Requires `OPENSEA_API_KEY` (instant via API).
Use when a user wants to set up, configure, install, or reconfigure the opencode Fusion agent team - a strong main/build agent that plans and reviews but cannot edit files, delegating all edits to a cheaper sidekick subagent, plus an explore search agent and optional research/design/reviewer/vision specialists. Triggers include "set up fusion", "configure fusion", "install fusion", "fusion setup", "undo fusion" / "remove fusion", changing which models the main, sidekick, or explore agents use, or naming a subscription to start from a ready-made profile - e.g. "set up fusion with my OpenCode Go subscription" (also OpenCode Zen, ChatGPT Plus/Pro, GitHub Copilot). Writes the global opencode config under ~/.config/opencode/.
Turn a SPEC, PRD, or any stated goal into a high-level executable PLAN of outcome-shaped tasks, and regenerate that plan when execution reveals it is wrong. Use this skill whenever the user asks to plan, break down, decompose, sequence, or roadmap work from a spec/requirements document or a goal, and whenever an executor's replan gate fires because a task's postcondition failed, expected state does not exist, a planned task is impossible, or new information invalidates a later task. Runs in two modes, initial planning and replanning, and always produces the same PLAN.md format.
This skill should be used when the user asks to "animate an SVG", "make a line draw itself on", "do a stroke draw-on / signature animation", "morph one shape into another", "move an element along a path", "animate an icon/logo", or "animate an SVG gradient or filter". Covers stroke-dashoffset draw-on, path morphing, motion-along-path, and animated icons/gradients/filters via CSS, SMIL, and GSAP.