74 plugins from public Claude Code marketplaces. Each one bundles skills, slash commands, agents, hooks or MCP servers that install together.
Showing 74 plugins that match these filters.
claude-code-skillsalirezarezvani/claude-skills2
air-gapped-marketplaceair-gapped/skills2
butterbase-skillsbutterbase-ai/butterbase-skills1
azure-skillsmicrosoft/azure-skills1Submit the repo with .claude-plugin/marketplace.json and we list every plugin.
Submit marketplaceCI/CD pipeline configuration, GitHub Actions/GitLab CI workflow setup, and automated deployment pipeline orchestration
Build, launch, grade, and schedule Claude Managed Agents (CMA) in your own Anthropic account — a plugin re-implementation of Anthropic's launch-your-agent reference skill (Apache-2.0; independent, not a fork). Every session starts with a goal (./my-agent/goal.json, opt-in SessionStart hook, driven by /cs-goal); loop_compiler.py compiles it into a bounded grade->iterate loop (max_iterations 1..20), a recurring cron scheduled-deployment loop, or a single-pass interview->stage->launch workflow. 6 skills: orchestrator (context: fork goal router) + interview + stage-launch + grade-iterate + run-without-you + wrap-up. 18 stdlib-only deterministic scaffolders (no network/API calls; live launches emitted as BYOK curl that never prints the key), 4 agents, 8 commands, hooks, 5 references, 4 assets. Validators enforce CMA limits. Distinct from engineering/agent-harness (generic domain loop) and write-a-skill (authors Claude Code skills, not CMAs).
Complete Vercel integration skill pack with 30 skills covering deployments, edge functions, preview environments, performance optimization, and production operations. Flagship+ tier vendor pack.
Complete Groq integration skill pack with 24 skills covering LPU inference, ultra-fast AI, and Groq Cloud deployment. Flagship tier vendor pack.
ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows
Build full-stack apps with Butterbase — AI-Native Backend-as-a-Service. Skills for app creation, schema design, frontend deployment, RLS debugging, serverless functions, and contributing.
Microsoft Azure MCP and Skills integration for cloud resource management, deployments, and Azure services. Manage your Azure infrastructure, monitor applications, and deploy resources directly from your development environment.
Twelve KDD-specific skills covering data-mining conference strategy across both submission cycles: track selection, sigconf submission, rebuttal, Resubmit handling, deployment evidence, and ACM proceedings publication, grounded in official KDD 2026 CFPs and OpenReview groups.
academicGuides developers from brand discovery through iterative design to deployment-ready HTML via Stitch.
Helm chart development — chart scaffolding, values design, template patterns, dependency management, and Kubernetes deployment strategies.
Deploy applications to AWS with architecture recommendations, cost estimates, and IaC deployment. Generate validated AWS architecture diagrams as draw.io XML.
9 short commands (/setup, /list, /trans, /note, /wiki, /add, /page, /cheatsheet, /ralphtrans) for Tongji Look lecture transcription, supplementary material ingestion, course wiki generation, and GitHub Pages deployment.
educationGABBE ops skills (30): operations: deployment, environments, observability, incidents, performance, cost and release management.
GitHub Actions CI/CD workflows for Google Cloud and Vertex AI deployments
Manage environment configurations and secrets across deployments
Create Kubernetes deployments, services, and configurations with best practices
Quick smoke test suites to verify critical functionality after deployments
Vertex AI Agent Engine deployment inspector and runtime validator
vLLM operator reference suite — deployment, configuration, quantization, caching, KV, tool parsers, reasoning parsers, chat templates, benchmarking, performance tuning, observability, omni, input modalities, speculative decoding, NVIDIA hardware, and a Gemma 4 31B operating-point serve recipe.
inferenceSecurity find-and-fix loop — adapted (Apache-2.0) from anthropics/defending-code-reference-harness and generalised to all vulnerability classes. Four read/write-only skills (no target-code execution): threat-model (bootstrap from code+CVEs+git-history, or interview an owner via Shostack's four questions, or both -> THREAT_MODEL.md), vuln-scan (static source review, parallel per-focus-area subagents -> VULN-FINDINGS.json), triage (adversarial N-vote verification, 16 false-positive exclusion rules, root-cause dedup, impact-on-asset x exploitability severity with stated deployment conditions, owner routing, checkpoint/resume -> TRIAGE.json), and patch (root-cause candidate diffs + independent reviewer, fix-first priority for deployment-conditional dangerous primitives, never auto-applied -> PATCHES/). The autonomous C/C++ + AddressSanitizer execution pipeline this was extracted from is referenced, not bundled (vuln-scan/HARNESS.md).
security
