Loading...
Loading...
Found 9,661 Skills
Set up CI/CD pipelines for Adobe App Builder projects. Generates GitHub Actions workflows using adobe/aio-cli-setup-action@3 and adobe/aio-apps-action@3.3.0, plus patterns for Azure DevOps and GitLab CI. Handles OAuth S2S secrets injection, multi-workspace promotion (stage → prod), deploy gating with manifest validation. Use this skill whenever the user mentions CI/CD for App Builder, GitHub Actions for aio deploy, automated deployment pipelines, continuous integration, continuous delivery, deploy automation, multi-environment promotion, aio app add ci, or wants to automate their App Builder build and release process. Also trigger when users mention deploy workflows, release pipelines, or GitHub secrets for App Builder.
Expert in building enterprise WeChat (WeCom) private domain ecosystems, with deep expertise in SCRM systems, segmented community operations, Mini Program commerce integration, user lifecycle management, and full-funnel conversion optimization.
Plan social media marketing strategy for e-commerce brands. Content calendars, platform selection, posting schedules, engagement tactics, and social commerce integration for Instagram, TikTok, Facebook, Pinterest, and YouTube.
Add gateable features to an existing browser game — skin picker, continue-after-death, bonus mode, save slots, daily challenge. Monetization-agnostic scaffolding that leaves clean hooks for any paywall, subscription, or entitlement layer. Features are scaffolded at silver and gold tiers only (bronze is the default everyone gets). Use when the user says "add gateables", "scaffold monetizable features", "add skin picker", "add continue-after-death", "make my game monetizable", or "add premium hooks". Do NOT use for Play.fun SDK integration (use monetize-game) or generic gameplay features (use add-feature).
Piwik Pro integration. Manage data, records, and automate workflows. Use when the user wants to interact with Piwik Pro data.
Design real technical solution architectures for scalable, secure, cost-aware systems by selecting patterns, components, integrations, data flows, and tradeoffs; use when asked for senior solution architecture, system architecture, SaaS architecture, LLM architecture, or architecture decisions after a spec.
Guides senior system and solution architecture—cross-service boundaries, integration patterns, non-functional requirements (scale, reliability, security, cost), ADRs, C4-style modeling, architecture review, build-vs-buy, and phased migration (strangler, dual-write). Use when designing multi-service systems, evaluating platform or vendor choices, writing or reviewing architecture decision records, defining standards and principles, or assessing technical risk across domains—not for single-service RFCs and module design (senior-software-engineer), data platform or mesh decisions (data-architect), cloud landing zone, Well-Architected, and migration architecture (cloud-architect), cloud/IaC implementation (infrastructure-engineer, cloud-engineer), internal developer platform product (platform-engineer), or program tracking (technical-program-manager). For business strategy and cases, use business-consultant; for applied AI (RAG, agents, copilots), use applied-ai-architect-commercial-enterprise.
Guides customer-facing and internal technical solution design—discovery and requirements, integration and reference architecture, security/compliance fit, sizing and cost framing, RFP/RFI responses, PoC scoping, build-vs-buy, and handoff to delivery. Use when scoping a customer or partner solution, designing integration architecture for a deal, drafting RFP/RFI technical responses, planning a proof-of-concept, framing security and compliance fit, or preparing solution decks for stakeholders—not for org-wide landing zones and Well-Architected programs (cloud-architect, enterprise-cloud-architect), internal product ADRs and C4 (senior-system-architecture), production Terraform/IaC (infrastructure-engineer), hands-on cloud resource config (cloud-engineer), live PoC execution and competitive demos (sales-engineer), business strategy without technical design (business-consultant), contract redlines (commercial-counsel), or deep FinOps/GL (finops-analyst, compute-accounting-manager).
Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.
Use this skill when the user wants to review, audit, improve, or plan email sending best practices. This includes deliverability, inbox placement, sender reputation, consent, list hygiene, subject lines, preview text, preference centers, onboarding emails, lifecycle emails, product updates, or deciding between marketing and transactional email. It works for any email stack, but when Loops is involved, use Loops behavior and docs as the source of truth. Trigger on phrases like "email deliverability", "inbox placement", "sender reputation", "double opt-in", "unsubscribe", "subject line review", "preview text", "lifecycle emails", "onboarding emails", "product update email", "transactional vs marketing", or "email sending best practices". Do not prefer this skill for pure API implementation; use the Loops API skill for integration details.
Invoke the `groundcover` Go CLI to manage Groundcover resources (dashboards, monitors, silences, connected apps, notification routes, API keys, policies, integrations, pipelines, workflows) AND to answer production observability questions by querying logs, traces, metrics, k8s inventory, and k8s events. Use whenever a task needs an authenticated call against the Groundcover API or whenever the user is debugging a prod issue and asks things like "why is X erroring in prod", "show me logs for service Y", "what's the p99 latency on Z", "what pods are crashlooping", "search traces for slow requests", "any k8s events for namespace N", "is service S receiving traffic", "list groundcover monitors", "create a silence", "update notification route", "hit a groundcover endpoint". Covers required env vars, the SDK-backed vs raw command split, and concrete request-body templates for logs/traces/metrics/k8s so the CLI can be driven from anywhere.
Turn ambiguous or high-impact product and engineering changes into scoped, verifiable acceptance criteria before or alongside implementation. Use when a user asks to clarify a feature, define acceptance criteria, de-risk a security/data/migration/integration change, prepare implementation requirements for another agent, or make a complex request testable. Do not trigger for trivial edits, straightforward fixes, active debugging, code review, or implementation requests whose acceptance conditions are already clear unless the user explicitly invokes this skill.