AgentWorkforce.
19 skills across 1 repo
- 100/100
adding-swarm-patterns
Use when adding new multi-agent coordination patterns to agent-relay - provides checklist for types, schema, templates, and docs updates
- 100/100
agent-relay
Use when you need Codex to coordinate multiple agents through Relaycast for peer-to-peer messaging, lead/worker handoffs, or shared status tracking across sub-agents and terminals.
- 100/100
agent-relay-orchestrator
Run headless multi-agent orchestration sessions via Agent Relay. Use when spawning teams of agents, creating channels for coordination, managing agent lifecycle, and running parallel workloads across Claude/Codex/Gemini/Pi/Droid agents.
- 100/100
browser-testing-with-screenshots
Use when testing web applications with visual verification - automates Chrome browser interactions, element selection, and screenshot capture for confirming UI functionality
- 100/100
choosing-swarm-patterns
Use when coordinating multiple AI agents and need to pick the right orchestration pattern - covers 10 patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) with decision framework and reflection protocol
- 100/100
creating-agent-skills-skill
Use when creating Agent Skills packages (SKILL.md format) for Codex CLI, GitHub Copilot, or Amp - provides the agentskills.io specification with frontmatter constraints, directory structure, and validation rules
- 100/100
creating-claude-agents
Use when creating or improving Claude Code agents. Expert guidance on agent file structure, frontmatter, persona definition, tool access, model selection, and validation against schema.
- 100/100
creating-claude-hooks
Use when creating or publishing Claude Code hooks - covers executable format, event types, JSON I/O, exit codes, security requirements, and PRPM package structure
- 100/100
creating-claude-rules
Use when creating or fixing .claude/rules/ files - provides correct paths frontmatter (not globs), glob patterns, and avoids Cursor-specific fields like alwaysApply
- 100/100
creating-skills
Use when creating new Claude Code skills or improving existing ones - ensures skills are discoverable, scannable, and effective through proper structure, CSO optimization, and real examples
- 100/100
debugging-websocket-issues
Use when seeing WebSocket errors like "Invalid frame header", "RSV1 must be clear", or "WS_ERR_UNEXPECTED_RSV_1" - covers multiple WebSocketServer conflicts, compression issues, and raw frame debugging techniques
- 95/100
deploying-to-staging-environment
Use when deploying changes to staging across relay, relay-dashboard, and relay-cloud repos - coordinates multi-repo branch syncing using git worktrees, automatically triggers staging deployments via GitHub Actions
- 100/100
github-oauth-nango-integration
Use when implementing GitHub OAuth + GitHub App authentication with Nango - provides two-connection pattern for user login and repo access with webhook handling
- 100/100
implementing-command-palettes
Use when building Cmd+K command palettes in React - covers keyboard navigation with arrow keys, keeping selected items in view with scrollIntoView, filtering with shortcut matching, and preventing infinite re-renders from reference instability
- 90/100
openclaw-relay
Real-time messaging across OpenClaw instances (channels, DMs, threads, reactions, search).
- 100/100
prpm-json-best-practices
Best practices for structuring prpm.json package manifests with required fields, tags, organization, multi-package management, enhanced file format, eager/lazy activation, and conversion hints
- 100/100
running-headless-orchestrator
Use when an agent needs to self-bootstrap agent-relay and autonomously manage a team of workers - covers infrastructure startup, agent spawning, lifecycle monitoring, and team coordination without human intervention
- 100/100
using-agent-relay
Use when coordinating multiple AI agents in real-time - provides inter-agent messaging via MCP tools
- 100/100
writing-agent-relay-workflows
Use when building multi-agent workflows with the relay broker-sdk - covers the WorkflowBuilder API, DAG step dependencies, agent definitions, step output chaining via {{steps.X.output}}, verification gates, evidence-based completion, owner decisions, dedicated channels, dynamic channel management (subscribe/unsubscribe/mute/unmute), swarm patterns, error handling, event listeners, step sizing rules, authoring best practices, and the lead+workers team pattern for complex steps