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hosted-studio-debug

89
genlayerlabsgenlayerlabs

Debug GenLayer Studio deployments via ArgoCD CLI

193 days ago

cloudflare-cli

89
genlayerlabsgenlayerlabs

Debug and manage Cloudflare DNS, cache, and proxy settings using flarectl

192 days ago

setup

89
genlayerlabsgenlayerlabs

Setup and launch GenLayer Studio with Docker Compose

192 days ago

sentry-issue-fixer

89
genlayerlabsgenlayerlabs

Fetch, analyze, fix Sentry issues, run tests, and create PRs

192 days ago

discord-community-feedback

89
genlayerlabsgenlayerlabs

Monitor Discord community channel for user-reported bugs and issues

193 days ago

integration-tests

89
genlayerlabsgenlayerlabs

Setup Python virtual environment and run integration tests with gltest

192 days ago

unit-tests

89
genlayerlabsgenlayerlabs

Setup Python virtual environment and run unit tests with gltest

193 days ago

create-pr

89
genlayerlabsgenlayerlabs

Create GitHub pull requests by analyzing branch diff and following the project template

192 days ago

studio-db

89
genlayerlabsgenlayerlabs

Query Studio deployment PostgreSQL databases for transaction debugging and analytics

193 days ago

initial-setup

15
genlayerlabsgenlayerlabs

Sets up the development environment for GenVM repository. Use when setting up the repo for the first time or when dependencies need to be refreshed.

193 days ago

test

15
genlayerlabsgenlayerlabs

Runs tests for the GenVM project. Use after making code changes to verify correctness.

193 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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