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Found 6,494 Skills
Standardized directory structure and artifact management for agentic research. Ensures consistent data flow across all agent platforms (Gemini, Claude, Antigravity).
Use before running local GPU workloads such as PyTorch, SGLang serving, Ray clusters, CUDA benchmarks, or scripts that use GPUs; instructs agents to wrap commands with gpu-lease run so CUDA_VISIBLE_DEVICES is set through a lease.
Guides agents to interactively discover customer requirements for a Secure n-tier serverless web application and generate a tailored cloud multi-product solution that incorporates opinionated best practices and architecture guidance. Use when users need agentic assistance with designing and creating a multi-product solution in the cloud for Secure n-tier serverless web application. Don't use when designing VM or GKE-based architectures or when not using Google Cloud.
Use this skill for live web tasks where WebFetch or curl would fail or be insufficient: JavaScript-rendered pages, forms, screenshots, PDFs, login flows, CAPTCHA/bot-protection flows, and multi-step navigation. It runs a real Steel cloud browser through the Steel CLI. Use when the agent should visit, click, type, scrape, screenshot, or extract now. Do not use for writing reusable Steel SDK/API code; use steel-developer for code. If a live task fails, hand off to steel-session-debugging; if evidence points to bot detection, proxies, CAPTCHA, or identity, hand off to steel-reliability.
Take the current branch from done-coding to merge-ready in one pass — review the diff against AGENTS.md, deslop, commit and push, open a PR using rule-validate's PR copy, then babysit until mergeable. Use when the user types `/ship` or asks to ship, finalize, or land the current branch.
Use when one Python service must send each agent's, tenant's, team's, or request's spans to its correct Arize space and project using application metadata. Covers dynamic OpenTelemetry routing for custom agent builders and multi-tenant applications, including register_with_routing, set_routing_context, multi-space tracing, and custom span routing.
Log genuine, recurring repository friction to .agents/PAPERCUTS.md — confusing setup, a flaky repo command or script, a misleading in-repo error, stale generated files, or a non-obvious gotcha that will cost the next contributor time. Also use to review, deduplicate, and resolve existing entries. Gate hard before logging: only friction the repository itself can fix counts. Never log the agent's own sandbox/permission errors, shell-scripting mistakes, transient flakiness, or third-party tool quirks the repo can't change.
Delegate a coding task to the Pi coding agent CLI (`pi`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to delegate implementation work to Pi - phrasings like "have Pi implement X", "delegate this to pi", "run it through Pi", or "use pi to implement/fix/refactor" - or wants to run a queue of coding tasks through Pi while staying the reviewer. DO NOT USE for tasks small enough to do inline, or when the user wants the code written directly without delegating.
Audit a JavaScript/TypeScript repo's npm, yarn, or pnpm configuration for supply-chain hardening: tool version, lifecycle scripts, unsafe dependency protocols, and minimum release age ≥3 days. Use when the user invokes /check-npm or asks to audit package manager security, lifecycle scripts, git dependencies, ignore-scripts, min-release-age, allow-git, approvedGitRepositories, strictDepBuilds, or blockExoticSubdeps in a Grafana plugin or JS/TS project.
Guides the migration of existing AI workloads (Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted GKE inference using gcloud and kubectl. Use when the user has an existing AI inference workload (on Cloud Run, the Gemini API, Gemini Enterprise Agent Platform, or a custom VM) and wants to move it to self-hosted inference on GKE, or asks follow-up questions during such a migration (hardware sizing, model staging, manifest generation, validation, traffic cutover). DO NOT use for brand new GKE inference deployments with no existing workload to migrate (use gke-inference instead). DO NOT use if the user intends to automate the migration via the Gemini Cloud Assist MCP server.
AI-native tutor and onboarding workflow for the four independent Claude certification tracks in AI Engineering from Scratch. Use when a learner wants to choose a Claude certification, prepare for CCAO-F, CCDV-F, CCAR-F, or CCAR-P, resume a certification path, learn the next lesson interactively, run and verify practical labs, build scored artifacts, take a diagnostic or mock exam, or remediate weak exam domains from GitHub with Claude Code, Codex, ChatGPT, Cursor, or another agent.
Full brand naming workflow for founders, agencies, and businesses. Use this skill whenever the user says "help me name this brand", "brand naming", "I need a name for", "name ideas for", "what should I call my brand/company/product", "naming a startup", "brand name suggestions", "help with naming", or shares a brand brief and asks for name options. Also triggers when the user shares existing name options and asks for feedback, evaluation, ranking, or scoring of those names. Auto-detects whether to run the full generation workflow or the evaluation workflow based on what the user provides. Always use this skill for any brand or product naming task — even if the user just casually mentions needing a name.