Initialize, consult on, operate, validate, and recover task-card-driven multi-agent software projects. Use when Codex needs a bounded multi-session roundtable for a complex topic, product, architecture, risk, or requirements question—including a topic outside a repository—or needs to scaffold or upgrade a repository…
Reverse-engineer an AI product from authenticated UI evidence, including autonomous screenshot collection when safe browser or desktop controls are available, producing traceable user journeys, Agent I/O contracts, functional-equivalent prompts, or layered product architecture. Use for read-only product teardowns…
Add x402 payment execution to AI agents — per-task budgets, spending controls, and non-custodial wallets via MCP tools. Use when agents need to pay for APIs, services, or other agents.
Polish a generated CLI to pass verification and become publish-ready. Runs diagnostics (dogfood, verify, scorecard, go vet, gosec), automatically fixes all issues (verify failures, static-analysis findings, dead code, descriptions, README, MCP tool quality), reports the before/after delta, and offers to publish. Use…
Use when ask-dora routes a routine idea, when running dora harness new, or when grilling a loop-able idea into a routine. Collect skills to run, skills to refer to, the Scalekit Agent Gateway MCP URL, and a Hermes model, provider, and reasoning level from dora harness models. After one good one-pass, may freeze a…
Scaffold and maintain MaaFW (MaaFramework) application projects with the create-maa-project CLI. Use when creating a new MaaFW pipeline or Python agent project, adding add-ons such as dev-tools, GitHub workflows, resource packs, or the Python agent template, syncing project metadata, updating MaaFramework or…
VORTEX-OS is a Hierarchical Autonomous Orchestration Engine designed to treat AI agency as a high-stakes, closed-loop corporate operation. Built exclusively to maximize the native capabilities of the MiniMax ecosystem, VORTEX-OS decouples strategic planning from operational labor. It enables you to ship complex…
Build LLM pipelines, tool-using agents and parallel fan-outs in Python with yait-aichain (Skill, Chain, Pool, Agent, Tool) — provider-independent. Use when writing, fixing or reviewing code that imports yaitaichain.
A tool for creating same-length patches to Claude Code’s bundled or npm-installed JavaScript. It helps change how Claude Code behaves, including checks and limits.
Build and debug Pydantic AI v2 agents using best practices for dependencies, instructions, tools, capabilities, hooks, and structured output validation. Use when the user wants to: (1) Create a new Pydantic AI agent, (2) Debug or fix an existing agent, (3) Add features like tools, validators, capabilities, hooks, or…
Harness Kit documentation — installation, plugin catalog, creating plugins, cross-harness setup, architecture, and FAQ. Use when working with or configuring harness-kit plugins, understanding the plugin/skill system, installing slash commands, setting up AI coding tool configuration, answering questions about the…
A guide for building applications with Anthropic's Managed Agents, a cloud service that runs AI agents in managed containers. It covers creating agents and environments, running sessions, receiving event streams, and auditing usage.
Use when the user wants to "set up a loop", build a self-running or run-until-done agent, automate a recurring engineering task (triage, keep-CI-green, dependency bumps, backlog burndown), or stop hand-prompting an agent turn by turn. Sets up an autonomous engineering loop in the current project. It discovers work…
Migrate community plugins from Claude Code, Codex, or Skills.sh into AgentPlugins. Use when the user wants to convert a plugin they wrote or found into the AgentPlugins v1 manifest format so it can be installed via agentplugins add or agentplugins import.
Run an LLM council — Claude (correctness), Gemini (edge cases), Cursor (integration), Kilo (maintainability), and you (scope) tackle the same task in parallel. Use when the user wants multiple independent perspectives on a decision, approach, or problem.
Design, generate, audit, or revise minimal validation-driven AI agent packs for Codex, Claude Code, and Claude skills from project descriptions, README files, specs, existing workflows, or repository evidence. Use when creating or improving AGENTS.md, CLAUDE.md, context routers, primary workflow agents, reviewers…
Use when helping a user inspect, organize, plan, apply, activate, back up, or restore SOS-managed agent skill packs on Codex or Claude Code without assuming global installation.
Orchestrate Ralph automation loops for spec-driven development. Use when starting, stopping, monitoring, or checking status of Ralph loops. Triggers on Ralph start, Ralph stop, Ralph status, spec automation, task loop, run tasks, check progress, kill Ralph, resume Ralph, or tmux session management.
Use when the user wants to find or discover a Claude Code skill that is NOT already installed — e.g. "is there a skill for X", "find me a skill that…", "what skills exist for…", or "/find-skill ". Searches the official plugin marketplace, GitHub, and curated awesome-lists for community skills matching a need, removes…
Use when a coding task needs an objective-first long-running loop with fresh-context work and review phases, explicit acceptance criteria, resumable state, and real blocked handling.
★not rated 10 6mo agoA42 tokens
originalMIT
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: