Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
39,866 skills from 1,828 repositories · updated 12 minutes ago
39,866 skills
- postgresql-optimizationgithub/awesome-copilotPostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem.DataNo warnings★ 40.4K↓ —Also in 1 other repo
- axiomsickn33/agentic-awesome-skillsFirst-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.OtherNo warnings★ 48.4K↓ —Also in 1 other repo
- postgresql-code-reviewgithub/awesome-copilotPostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS).DataNo warnings★ 40.4K↓ —Also in 1 other repo
- update-specificationgithub/awesome-copilotUpdate an existing specification file for the solution, optimized for Generative AI consumption based on new requirements or updates to any existing code.PlanningNo warnings★ 40.4K↓ —
- cloud-design-patternsgithub/awesome-copilotCloud design patterns for distributed systems architecture covering 42 industry-standard patterns across reliability, performance, messaging, security, and deployment categories. Use when designing, reviewing, or implementing distributed system architectures.DesignNo warnings★ 40.4K↓ —
- gem-devops-guidelinesgithub/awesome-copilotDesign or review infrastructure, deployment, CI/CD, Docker, Kubernetes, health checks, rollback, feature flags, production readiness, and mobile release workflows. Use for DevOps, platform, container, pipeline, or release tasks.DevOpsNo warnings★ 40.4K↓ —
- finalize-agent-promptgithub/awesome-copilotFinalize prompt file using the role of an AI agent to polish the prompt for the end user.OtherNo warnings★ 40.4K↓ —
- what-context-neededgithub/awesome-copilotAsk Copilot what files it needs to see before answering a questionProductivityNo warnings★ 40.4K↓ —
- seo-geosickn33/agentic-awesome-skillsOptimize content for AI Overviews, ChatGPT, Perplexity, and other AI search systems. Use when improving GEO, AI citations, llms.txt readiness, crawler accessibility, and passage-level citability.MarketingNo warnings★ 48.4K↓ —Also in 1 other repo
- moatmrisickn33/agentic-awesome-skillsAnalyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.PlanningNo warnings★ 48.4K↓ —Also in 1 other repo
- google-cloud-recipe-onboardinggoogle/skillsGuides a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource. Use when a new developer wants to initialize their first Google Cloud project, configure billing, and verify deployment. Don't use for enterprise organization setup (use Google Cloud Setup guided flow for that instead). Don't use for complex multi-project architectures.OfficialDevOpsNo warnings★ 21.5K↓ —Also in 1 other repo
- google-cloud-waf-operational-excellencegoogle/skillsGenerates operational guidance for CI/CD deployment pipelines, observability, monitoring, logging, and incident management on Google Cloud based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use when the user asks about operations-related topics like capacity management, change management, incident and problem management, configuration management, deployment automation using infrastructure as code (IaC), or operational health checks for Google Cloud workloads.OfficialDevOpsNo warnings★ 21.5K↓ —
- create-specificationgithub/awesome-copilotCreate a new specification file for the solution, optimized for Generative AI consumption.PlanningNo warnings★ 40.4K↓ —
- tmuxsickn33/agentic-awesome-skillsExpert tmux session, window, and pane management for terminal multiplexing, persistent remote workflows, and shell scripting automation.OtherNo warnings★ 48.4K↓ —Also in 1 other repo
- google-cloud-solution-agentic-ai-borderless-data-lakehousegoogle/skillsDiscovers requirements and designs a borderless open data lakehouse using Lakehouse for Apache Iceberg and BigQuery data agents. Use when architecting multi-cloud storage infrastructure (Cloud Storage, AWS S3, Azure Blob), establishing ingestion and AI serving subsystems, configuring Cross-Cloud Interconnect, or deploying Gemini Enterprise Agent Platform and BigQuery data agents. Don't use for single-cloud data warehouses, or when the focus is on Knowledge Catalog metadata governance and Spark-driven IDE analytics workflows (use google-cloud-solution-agentic-analytics-spark-knowledge-catalog instead).OfficialDevOpsNo warnings★ 21.5K↓ —
- google-cloud-recipe-foundation-buildergoogle/skillsDeploys a baseline landing zone foundation for a Google Cloud Organization, establishing security guardrails using Organization Policies, resource hierarchy folders and projects, billing association, and centralized logging and monitoring. Deploys Google Cloud's recommended security controls and architecture. Use when setting up a new Google Cloud Organization or establishing a secure, enterprise-grade landing zone foundation. Don't use for individual project onboarding (use google-cloud-recipe-onboarding or product-specific skills instead).OfficialSecurityNo warnings★ 21.5K↓ —
- finding-google-skillsgoogle/skillsGoogle platform decision and setup guidance, loaded on demand from Google's skill catalog. Use when a developer is choosing or setting up part of their stack, such as where to run a service, a database, storage, messaging, authentication, analytics, ads, or AI model serving, and a Google product is a reasonable candidate - whether or not a vendor is named - or when a request names a Google product or API. Brings in the matching Google skill so the answer can weigh Google options, their trade-offs, and when they are not the right fit. Skip when the stack is already settled on another provider and no Google product is named, or the task involves no platform choice.OfficialDataNo warnings★ 21.5K↓ —Also in 1 other repo
- dataladK-Dense-AI/scientific-agent-skillsRetrieves, versions, and publishes scientific datasets with DataLad and git-annex, and captures computational provenance with datalad run, rerun, and containers-run. Use when cloning or fetching data from OpenNeuro, DANDI, datasets.datalad.org, or any DataLad dataset; when a file in a dataset reads as a broken symlink or a small pointer instead of real data; when an analysis needs a machine-readable record of how each output was produced so it can be re-executed; or when publishing a dataset to siblings such as a GitHub repository plus a storage remote. Also use to decide between DataLad and plain Git for a data-carrying repository.ScienceNo warnings★ 54.4K↓ —Also in 1 other repo
- dotnet-best-practicesgithub/awesome-copilotEnsure .NET/C# code meets best practices for the solution/project.EngineeringNo warnings★ 40.4K↓ —
- google-cloud-solution-agentic-ai-bidirectional-streaminggoogle/skillsGuides agents to interactively discover customer requirements for live, bidirectional multi-agent AI systems that process continuous streams of multimodal data for real-time technical guidance and safety monitoring. Generates a custom Google Cloud solution that uses opinionated best practices and architecture guidance. Use when users need agentic assistance to design and create a multi-product solution in the cloud for live bidirectional multimodal streaming workloads. Don't use for simple text-based chat applications or workloads without real-time streaming requirements.OfficialDesignNo warnings★ 21.5K↓ —
- google-cloud-solution-agentic-ai-data-science-workflowgoogle/skillsDesigns a tailored multi-product agentic data science architecture on Google Cloud that incorporates opinionated best practices. Use when architecting multi-product solutions for agent-based data analytics or ML workloads. Don't use for simple queries, non-agentic pipelines, general cloud reviews, or writing agent code.OfficialDataNo warnings★ 21.5K↓ —
- breakdown-feature-prdgithub/awesome-copilotPrompt for creating Product Requirements Documents (PRDs) for new features, based on an Epic.PlanningNo warnings★ 40.4K↓ —
- rebase-current-branchgithub/awesome-copilotRebase the currently checked out feature branch onto the latest upstream default branch. Use when asked to update a branch with main or master, rebase the current branch onto the default branch, or sync a feature branch before review. Detects whether the repository uses main or master and guides safe conflict handling.EngineeringNo warnings★ 40.4K↓ —
- google-cloud-recipe-authgoogle/skillsProvides expert guidance on Identity and Access Management (IAM) and authenticating and authorizing to Google Cloud services and APIs, covering human users, service identities, Application Default Credentials (ADC), and best practices for secure access.OfficialOtherNo warnings★ 21.5K↓ —Also in 1 other repo
marketing-loops
coreyhaines31/marketingskills
MarketingUpdated 2 days ago
From the author
When the user wants to set up a recurring, self-running marketing workflow — a repeatable loop an AI agent runs on a cadence (weekly, daily, on a trigger) rather than a one-off task. Also use when the user mentions 'marketing loop,' 'recurring marketing workflow,' 'automate my marketing,' 'marketing on autopilot,' 'weekly marketing review,' 'ad fatigue check,' 'weekly ads check,' 'content refresh loop,' 'churn watch,' 'ranking drop alert,' 'run my SEO,' 'SEO operator,' 'daily SEO agent,' 'run my outbound,' 'AI SDR,' 'reply triage,' 'always-on marketing,' 'marketing automation workflow,' or 'run this every week.' Use this to pick, adapt, and schedule an ongoing marketing loop that orchestrates the other marketing skills. For one-off marketing ideas, see marketing-ideas. For the experimentation loop specifically, see ab-testing.
Install
npx skills add coreyhaines31/marketingskills --skill marketing-loops -a claude-code
Installs to .claude/skills/marketing-loops/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Download .zip
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Instructions onlyNo network use seenLicence: MIT
Safety checks on SKILL.md
No warnings.
Why 95
Security100
Provenance95
Maintenance100
Licence100
Adoption73
Files (9)
- SKILL.md
- evals/evals.json
- references/loop-catalog.md
- references/loop-guardrails.md
- references/loop-orchestration.md
- references/loop-state.md
- references/loop-template.md
- references/outbound-operator.md
- references/seo-operator.md