[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7EK12BZPYYVDPEJDFZZGDWW":3,"skill-same:01M7EK12BZPYYVDPEJDFZZGDWW":47},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":25,"commitSha":26,"skillDirectory":27,"forksCount":14,"repositoryHtmlUrl":28,"repositoryHomepageUrl":29,"ownerHtmlUrl":30,"ownerBlogUrl":6,"ownerDescription":31,"updatedAt":32,"install":33,"resources":46},"01M7EK12BZPYYVDPEJDFZZGDWW","agent-evaluation",null,"Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.","marnixGeerkens\u002Frocketlauncher-claude-code","marnixGeerkens","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F143275741?v=4","01M7EJY825SFPHDDZNFDAJHCA9","Marnix Geerkens","01M7EJY82TBA6ABXJ62JWR9B9F",0,"MIT","https:\u002F\u002Fgithub.com\u002FmarnixGeerkens\u002Frocketlauncher-claude-code\u002Fblob\u002Fmain\u002Fcomponents\u002Fskills\u002Fai-research\u002Fagent-evaluation\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: agent-evaluation\ndescription: \"Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.\"\nsource: vibeship-spawner-skills (Apache 2.0)\n---\n\n# Agent Evaluation\n\nYou're a quality engineer who has seen agents that aced benchmarks fail spectacularly in\nproduction. You've learned that evaluating LLM agents is fundamentally different from\ntesting traditional software—the same input can produce different outputs, and \"correct\"\noften has no single answer.\n\nYou've built evaluation frameworks that catch issues before production: behavioral regression\ntests, capability assessments, and reliability metrics. You understand that the goal isn't\n100% test pass rate—it\n\n## Capabilities\n\n- agent-testing\n- benchmark-design\n- capability-assessment\n- reliability-metrics\n- regression-testing\n\n## Requirements\n\n- testing-fundamentals\n- llm-fundamentals\n\n## Patterns\n\n### Statistical Test Evaluation\n\nRun tests multiple times and analyze result distributions\n\n### Behavioral Contract Testing\n\nDefine and test agent behavioral invariants\n\n### Adversarial Testing\n\nActively try to break agent behavior\n\n## Anti-Patterns\n\n### ❌ Single-Run Testing\n\n### ❌ Only Happy Path Tests\n\n### ❌ Output String Matching\n\n## ⚠️ Sharp Edges\n\n| Issue | Severity | Solution |\n|-------|----------|----------|\n| Agent scores well on benchmarks but fails in production | high | \u002F\u002F Bridge benchmark and production evaluation |\n| Same test passes sometimes, fails other times | high | \u002F\u002F Handle flaky tests in LLM agent evaluation |\n| Agent optimized for metric, not actual task | medium | \u002F\u002F Multi-dimensional evaluation to prevent gaming |\n| Test data accidentally used in training or prompts | critical | \u002F\u002F Prevent data leakage in agent evaluation |\n\n## Related Skills\n\nWorks well with: `multi-agent-orchestration`, `agent-communication`, `autonomous-agents`\n","# Agent Evaluation\n\nYou're a quality engineer who has seen agents that aced benchmarks fail spectacularly in\nproduction. You've learned that evaluating LLM agents is fundamentally different from\ntesting traditional software—the same input can produce different outputs, and \"correct\"\noften has no single answer.\n\nYou've built evaluation frameworks that catch issues before production: behavioral regression\ntests, capability assessments, and reliability metrics. You understand that the goal isn't\n100% test pass rate—it\n\n## Capabilities\n\n- agent-testing\n- benchmark-design\n- capability-assessment\n- reliability-metrics\n- regression-testing\n\n## Requirements\n\n- testing-fundamentals\n- llm-fundamentals\n\n## Patterns\n\n### Statistical Test Evaluation\n\nRun tests multiple times and analyze result distributions\n\n### Behavioral Contract Testing\n\nDefine and test agent behavioral invariants\n\n### Adversarial Testing\n\nActively try to break agent behavior\n\n## Anti-Patterns\n\n### ❌ Single-Run Testing\n\n### ❌ Only Happy Path Tests\n\n### ❌ Output String Matching\n\n## ⚠️ Sharp Edges\n\n| Issue | Severity | Solution |\n|-------|----------|----------|\n| Agent scores well on benchmarks but fails in production | high | \u002F\u002F Bridge benchmark and production evaluation |\n| Same test passes sometimes, fails other times | high | \u002F\u002F Handle flaky tests in LLM agent evaluation |\n| Agent optimized for metric, not actual task | medium | \u002F\u002F Multi-dimensional evaluation to prevent gaming |\n| Test data accidentally used in training or prompts | critical | \u002F\u002F Prevent data leakage in agent evaluation |\n\n## Related Skills\n\nWorks well with: `multi-agent-orchestration`, `agent-communication`, `autonomous-agents`\n",{"name":5,"source":24,"description":7},"vibeship-spawner-skills (Apache 2.0)","main","4e647b68aabe849e143b6950971c380f7adccdef","components\u002Fskills\u002Fai-research\u002Fagent-evaluation","https:\u002F\u002Fgithub.com\u002FmarnixGeerkens\u002Frocketlauncher-claude-code","https:\u002F\u002Frocketlauncher.ai\u002Fclaude-code","https:\u002F\u002Fgithub.com\u002FmarnixGeerkens","CEO of Rocketlauncher.ai\r\n\r\nObsessed with AI\r\n\r\njoin  https:\u002F\u002Fwww.skool.com\u002Frocketlauncher-university\r\n👉🏻 it's free ","2026-10-13 00:52:14",{"source":8,"skillName":5,"commands":34,"prompt":44,"zipAvailable":45},[35,38,41],{"tool":36,"command":37},"npx","npx skills add marnixGeerkens\u002Frocketlauncher-claude-code --skill agent-evaluation",{"tool":39,"command":40},"bunx","bunx skills add marnixGeerkens\u002Frocketlauncher-claude-code --skill agent-evaluation",{"tool":42,"command":43},"pnpm","pnpm dlx skills add marnixGeerkens\u002Frocketlauncher-claude-code --skill agent-evaluation","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FmarnixGeerkens\u002Frocketlauncher-claude-code\u002Fblob\u002Fmain\u002Fcomponents\u002Fskills\u002Fai-research\u002Fagent-evaluation\u002FSKILL.md",true,[],[48,55,64,71,78,85],{"skillNo":49,"name":50,"nameZh":6,"description":51,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":52,"categories":53,"keywords":54,"publishedAt":19},"01M7EQFDF4T3K89WMFVFQVT3C8","zapier-make-patterns","No-code automation democratizes workflow building. Zapier and Make (formerly Integromat) let non-developers automate business processes without writing code. But no-code doesn't mean no-complexity - these platforms have their own patterns, pitfalls, and breaking points.  This skill covers when to use which platform, how to build reliable automations, and when to graduate to code-based solutions. Key insight: Zapier optimizes for simplicity and integrations (7000+ apps), Make optimizes for power","https:\u002F\u002Fgithub.com\u002FmarnixGeerkens\u002Frocketlauncher-claude-code\u002Fblob\u002Fmain\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fzapier-make-patterns\u002FSKILL.md",[],[],{"skillNo":56,"name":57,"nameZh":6,"description":58,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":59,"licenseFileUrl":60,"sourceHtmlUrl":61,"categories":62,"keywords":63,"publishedAt":19},"01M7EQFA5XQ0811Q4Q0WCFASZG","yeet","Use only when the user explicitly asks to stage, commit, push, and open a GitHub pull request in one flow using the GitHub CLI (`gh`).","Apache-2.0","https:\u002F\u002Fgithub.com\u002FmarnixGeerkens\u002Frocketlauncher-claude-code\u002Fblob\u002Fmain\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fyeet\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FmarnixGeerkens\u002Frocketlauncher-claude-code\u002Fblob\u002Fmain\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fyeet\u002FSKILL.md",[],[],{"skillNo":65,"name":66,"nameZh":6,"description":67,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":68,"categories":69,"keywords":70,"publishedAt":19},"01M7EQF4J6C2WKQWD9E2RQC6MJ","workflow-automation","Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, workflows resume exactly where they left off.  This skill covers the platforms (n8n, Temporal, Inngest) and patterns (sequential, parallel, orchestrator-worker) that turn brittle scripts into production-grade automation.  Key insight: The platforms make different tradeoffs. n8n optimizes for accessibility","https:\u002F\u002Fgithub.com\u002FmarnixGeerkens\u002Frocketlauncher-claude-code\u002Fblob\u002Fmain\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fworkflow-automation\u002FSKILL.md",[],[],{"skillNo":72,"name":73,"nameZh":6,"description":74,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":75,"categories":76,"keywords":77,"publishedAt":19},"01M7EQF1AT655CYYZBEQ8V6Z9D","trigger-dev","Trigger.dev expert for background jobs, AI workflows, and reliable async execution with excellent developer experience and TypeScript-first design. Use when: trigger.dev, trigger dev, background task, ai background job, long running task.","https:\u002F\u002Fgithub.com\u002FmarnixGeerkens\u002Frocketlauncher-claude-code\u002Fblob\u002Fmain\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Ftrigger-dev\u002FSKILL.md",[],[],{"skillNo":79,"name":80,"nameZh":6,"description":81,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":82,"categories":83,"keywords":84,"publishedAt":19},"01M7EQEY9ENH0G2EJ1WD6C1CE8","slack-automation","Automate Slack workspace operations including messaging, search, channel management, and reaction workflows through Composio's Slack toolkit.","https:\u002F\u002Fgithub.com\u002FmarnixGeerkens\u002Frocketlauncher-claude-code\u002Fblob\u002Fmain\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Fslack-automation\u002FSKILL.md",[],[],{"skillNo":86,"name":87,"nameZh":6,"description":88,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":59,"licenseFileUrl":6,"sourceHtmlUrl":89,"categories":90,"keywords":91,"publishedAt":19},"01M7EQESHEKPTE0QPW9R6XV5K2","rote","Compile a proven agent skill (a SKILL.md plus references) into a deterministic pipeline that runs without an LLM in the loop, then serve it back to Claude as an MCP tool. Use when: rote, compile this skill, turn this skill into a workflow, make this skill deterministic, make this skill cheaper or faster, harden this skill for production, run this skill as a background job.","https:\u002F\u002Fgithub.com\u002FmarnixGeerkens\u002Frocketlauncher-claude-code\u002Fblob\u002Fmain\u002Fcomponents\u002Fskills\u002Fworkflow-automation\u002Frote\u002FSKILL.md",[],[]]