Use this to build a good evaluation dataset for an LLM app, the part everyone underestimates. Trigger on "make an eval set", "what should I test my LLM on", "I don't have test data for my prompt", "build a golden dataset", or before setting up evals. A great eval set beats a great metric; garbage-in means your evals lie to you.
How to install build-eval-dataset?
contextjet-ai/awesome-llm-observability/build-eval-dataset
$npx -y skills add contextjet-ai/awesome-llm-observability --skill build-eval-datasetInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/contextjet-ai/awesome-llm-observability" --skill "contextjet-ai/awesome-llm-observability/build-eval-dataset"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/contextjet-ai/awesome-llm-observability" that are relevant to the current task. Run `npx skills add "https://github.com/contextjet-ai/awesome-llm-observability"` and select the relevant skills, then follow their instructions.
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