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review

2.8k
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Run parallel code reviews: uncle-bob-reviewer (SOLID/TDD), cupid-reviewer (CUPID properties), test-reviewer (pyramid placement), and pii-reviewer (security/secrets). Surfaces conflicts for orchestrator resolution.

192 days ago

e2e

2.8k
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Generate and verify E2E tests for a feature. Explores live app, creates test plan, generates tests, runs and fixes until passing.

192 days ago

plan

2.8k
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Create a feature file with acceptance criteria before implementation. Use when no specs/features/*.feature file exists for the work.

192 days ago

orchestrate

2.8k
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Orchestration mode for implementation tasks. Manages the plan → code → review loop. Use /orchestrate <requirements> or let /implement invoke it.

192 days ago

sherpa

2.8k
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Delegate repository, agent, or documentation questions to the repo-sherpa. Use for onboarding, DX improvements, or meta-layer changes.

192 days ago

code

2.8k
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Delegate implementation work to the coder agent. Provide requirements or feature file path.

192 days ago

implement

2.8k
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Start implementation of a GitHub issue. Usage: /implement #123 or /implement <issue-url>

192 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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