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documentation-process

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After implementing a new feature or fixing a bug, make sure to document the changes. Use after finishing the implementation phase for a feature or a bug-fix

195 days ago

testing-process

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Guidelines describing how to test the code. Use whenever writing new or updating existing code, for example after implementing a new feature or fixing a bug.

195 days ago

analysis-process

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Turn the idea for a feature into a fully-formed PRD/design/specification and implementation-plan. Use when you have a spec or requirements that needs implementation. Use in pre-implementation (idea-to-design) stages to make sure you understand the spec/requirements and ensure you have a correct implementation plan before writing actual code.

195 days ago

cove

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Apply Chain-of-Verification (CoVe) prompting to improve response accuracy through self-verification. Use for complex questions requiring fact-checking, technical accuracy, or multi-step reasoning.

195 days ago

development-guidelines

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Use this task to ensure you follow development best practices during development and implementation.

195 days ago

implementation-process

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Implement a feature using the written implementation plan. Use when you have a fully-formed written implementation plan to execute in a separate session with review checkpoints

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.
Can't find your answer here? Get in touch

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