claude

AI Eval

Evaluate AI models for a real job, starting from start-eval: define the objective and workload, draw candidates from the live OpenRouter catalogue, and run wide and shallow (many models, about two outputs each). Covers in-repo and agent-run eval spaces, framework CLIs, image, RAG, agent, speech and regression evals, private annotation and human feedback Spaces, and findings through to articles.

31 on GitHubby Daniel Rosehillv0.8.0MITupdated yesterdayQA & Agent Sessions
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Plugin ai-eval from marketplace danielrosehill in danielrosehill/Claude-Code-Plugins. Commands read from the repo's manifest — today.

What it installs

No skills, commands, agents, hooks or MCP servers were found in the standard plugin folders.

View source on GitHub blog.danielrosehill.com

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Product research and procurement skills with a particular focus on technical specification conformance — does this part actually meet the requirement, and can you show your working. Marketplace-agnostic: spec definition from a vague want or a photograph, annotated search vocabulary, versioned spec-as-code, manufacturer datasheet retrieval, cross-region part-number equivalence, conformance evaluation matrices, bills of materials and RFQ packages. Plus the surrounding process: intake, research, compare, evaluate, recommend, market-check, spec-driven market landscape surveys, live price/delivery scanning through your own VPN egress, preference memory and hardware-rig profiling. Hands off to the marketplace-specific plugins (shopping, israel-shopping, amazon, aliexpress-israel-skills) once a question becomes about a particular shop.

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Smart home — Home Assistant, Snapcast multi-room audio, Plex media server ops, with HA/audio/media-server variants.

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Audio production — normalize, VAD, transcribe, diarize, podcast assembly, with engineering/podcast/transcript variants.

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PR and media monitoring — scan coverage, summarize press, draft responses, comms strategy, with monitoring/response/strategy variants.

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