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testing-guide

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Testing architecture and best practices for the Flare Stack Blog. Use when writing, debugging, or refactoring tests with Vitest and Cloudflare Workers pool.

194 days ago

backend-development

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Backend development patterns for the Flare Stack Blog. Use when creating new feature modules, writing Server Functions, defining Zod schemas, implementing Cloudflare Workflows, or working with middlewares.

194 days ago

frontend-development

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Frontend development patterns for the Flare Stack Blog. Use when implementing data fetching with TanStack Query, creating route loaders, building infinite scroll, adding skeleton/pending states, or organizing UI components.

194 days ago

styling-guide

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Official styling and design guidelines for the Flare Stack Blog.

194 days ago

project-architecture

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Provides an overview of the Flare Stack Blog architecture. Use when needing to understand the project structure, tech stack, routing layers (Hono/TanStack), dependency injection, or directory organization.

194 days ago

caching-strategies

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Dual-layer caching strategies for the Flare Stack Blog. Use when implementing CDN cache headers, KV caching with versioned invalidation, or debugging cache-related issues.

194 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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