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dagger-codegen

15.5k
daggerdagger

Edit dagger.gen.go output, Go templates (object.go.tmpl, defs.go.tmpl), invoke() dispatch, SDK interfaces (CodeGenerator, ClientGenerator), `dagger develop`, `dagger client install`. Keywords: codegen, SDK, bindings, templates, internal/dagger, dag.*, ModuleMainSrc

190 days ago

cache-expert

15.5k
daggerdagger

Covers Dagger Engine caching internals including cache key derivation, invalidation, and the immutable DAG model. Use when debugging cache misses, unexpected invalidations, or implementing caching-related engine features.

190 days ago

dagger

9
TerminalSkillsTerminalSkills

Write CI/CD pipelines as code with Dagger — portable, cacheable, container-based pipelines that run locally and in any CI system. Use when someone asks to "write CI pipeline in TypeScript", "portable CI/CD", "run GitHub Actions locally", "Dagger pipeline", "CI as code", "containerized build pipeline", or "test my CI locally before pushing". Covers Dagger SDK (TypeScript/Python), pipeline composition, caching, secrets, and multi-stage builds.

190 days ago

dagger-check

1
papercomputecopapercomputeco

Run checks (lints, tests, etc.) using Dagger scafolding

190 days ago

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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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