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Found 9,621 Skills
agent-team: Show one workflow run and grouped task status counts.
Programmatic screenshot capture on macOS. Find window IDs with Swift CGWindowListCopyWindowInfo, control application windows via AppleScript (zoom, scroll, select), and capture with screencapture. Use when automating screenshots, capturing application windows for documentation, or building multi-shot visual workflows.
Debug CI E2E failures from pull requests by inspecting GitHub checks, downloading Playwright reports, and mapping failures to local Nx commands. Use when debugging failed E2E tests in PR workflows.
Hokodo integration. Manage data, records, and automate workflows. Use when the user wants to interact with Hokodo data.
Jobadder integration. Manage data, records, and automate workflows. Use when the user wants to interact with Jobadder data.
Elastic Path integration. Manage data, records, and automate workflows. Use when the user wants to interact with Elastic Path data.
Expert-level Git version control with advanced workflows, branching strategies, and best practices for team collaboration
Build AI agents and agentic workflows. Use when designing/building/debugging agentic systems: choosing workflows vs agents, implementing prompt patterns (chaining/routing/parallelization/orchestrator-workers/evaluator-optimizer), building autonomous agents with tools, designing ACI/tool specs, or troubleshooting/optimizing implementations. **PROACTIVE ACTIVATION**: Auto-invoke when building agentic applications, designing workflows vs agents, or implementing agent patterns. **DETECTION**: Check for agent code (MCP servers, tool defs, .mcp.json configs), or user mentions of "agent", "workflow", "agentic", "autonomous". **USE CASES**: Designing agentic systems, choosing workflows vs agents, implementing prompt patterns, building agents with tools, designing ACI/tool specs, troubleshooting/optimizing agents.
Expert knowledge of Apache Airflow for building, scheduling, and monitoring data pipelines and workflows
Design and build multi-agent harness architectures for long-running AI application development. GAN-inspired Generator-Evaluator pattern, Sprint Contract negotiation, context management, quality criteria calibration. Based on Anthropic Engineering patterns. Use when: "build a harness", "multi-agent architecture", "agent orchestration", "generator-evaluator", "long-running app", "harness design", "agent pipeline", "quality evaluation loop", "sprint contract", "build app with agents", "Claude Agent SDK architecture", or when building complex full-stack apps that need planning → generation → evaluation cycles. Also use when discussing context degradation, self-evaluation bias, or assumption testing in AI workflows.
cmux release workflow, version bumping, changelog updates, pretag guard, release tags, and release asset expectations. Use when preparing or troubleshooting a cmux release.
Logit.io integration. Manage data, records, and automate workflows. Use when the user wants to interact with Logit.io data.