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executing-plans

104
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Use when you have a written implementation plan to execute in a separate session with review checkpoints

195 days ago

dispatching-parallel-agents

104
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Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

195 days ago

parallel-exploration

104
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Use when you need parallel, read-only exploration with task() (Scout fan-out)

195 days ago

code-reviewer

104
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Use when reviewing implementation changes against an approved plan or task (especially before merging or between Hive tasks) to catch missing requirements, YAGNI, dead code, and risky patterns

195 days ago

systematic-debugging

104
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Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

195 days ago

writing-plans

104
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Use when you have a spec or requirements for a multi-step task, before touching code

195 days ago

brainstorming

104
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Use before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

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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