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dynatrace-control

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Manage Dynatrace environments using dtctl - install/update the CLI, configure authentication with OS keyring tokens, and run kubectl-style operations (get/describe/edit/apply/delete/query/exec) for workflows, dashboards, notebooks, DQL, SLOs, settings, buckets, lookups, OpenPipeline, and Davis AI. Use when the user wants to control Dynatrace resources via dtctl.

195 days ago

deploy-lifecycle

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Deployment lifecycle management: audit deployment observability setup (entity tags, deployment events, Smartscape topology), run pre-deploy and post-deploy health checks (error rate, latency, Davis problems, dependency health), and verify deploy-health.yml configurations. Use when the user wants to check deployment readiness, monitor a deploy, or verify tagging compliance. Works for both new projects (onboarding readiness) and existing monitored services.

195 days ago

github-docs

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Investigate GitHub repositories using the gh CLI. Analyze PRs, issues, commits, CI/CD status, repo health, contributor activity, security vulnerabilities, and fetch repo docs/content. Use for any GitHub-related investigation or documentation retrieval.

195 days ago

FAQ

AgentCC is a discovery hub for AI agent capabilities. We index Agent Skills as the primary dataset, and also organize MCP servers and selected AI tools so developers can quickly find, compare, and evaluate what to integrate into their workflows.
An Agent Skill is a reusable capability package for an AI agent. It can define workflows, tool usage patterns, domain knowledge, or execution rules that help the agent perform more reliably in a specific task or environment.
AgentCC is a resource and discovery layer, not a one-click installer. On each skill page, you should review the repository, file tree, install command, and usage notes, then integrate it according to the runtime or client you are using.
No. AgentCC primarily indexes external repositories and metadata. We help you understand what a skill is, where it comes from, and how it may be used, but execution and security decisions still belong to your own runtime environment.
No directory can guarantee absolute safety. AgentCC can help surface repository links, file structures, and metadata, but you should still verify permissions, external dependencies, API usage, and code quality before using a skill in production or on sensitive machines.
Yes. AgentCC is designed to be an evolving resource graph. As the submission and curation workflow matures, contributors will be able to recommend high-quality skills, MCP servers, and AI tools into the directory.
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