openai-evals-and-observability
byamritmalla· 56 skills
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Use when adding regression evaluation, prompt and model versioning, token and cost telemetry, latency tracking, tracing, dashboards, or operational monitoring for OpenAI-backed AI capabilities. Produces eval dataset structure, scoring harness, regression thresholds, prompt/model metadata, logs, metrics, traces, and runbook notes. Do not use for initial AI architecture, feature ideation, RAG implementation, tool implementation, or agent orchestration.
How to install openai-evals-and-observability?
amritmalla/claude-full-stack-2.0/openai-evals-and-observability
$npx -y skills add amritmalla/claude-full-stack-2.0 --skill openai-evals-and-observabilityInstalls into the current project.
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Run `npx skills use "https://github.com/amritmalla/claude-full-stack-2.0" --skill "amritmalla/claude-full-stack-2.0/openai-evals-and-observability"` 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/amritmalla/claude-full-stack-2.0" that are relevant to the current task. Run `npx skills add "https://github.com/amritmalla/claude-full-stack-2.0"` and select the relevant skills, then follow their instructions.
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