Manage prompt versioning, evaluation, and drift detection for LLMs.
npx skills add https://github.com/asfbay-bit/opchain-skills --skill oc-prompt-ops
Please help me install this Agent Skill. Skill: oc-prompt-ops Source: https://github.com/asfbay-bit/opchain-skills/tree/main/skills/oc-prompt-ops Command: npx skills add https://github.com/asfbay-bit/opchain-skills --skill oc-prompt-ops
This Skill manages the versioning, evaluation, and drift detection of prompts for Large Language Models (LLMs), ensuring consistent quality and reducing manual effort.
Run the command '/oc-prompt eval [email protected]' to evaluate the current version of the 'model-routing' prompt against the 'v1.2.0' dataset.
High-intent search queries and answers about installing and using this skill.
Prompt versioning for LLM applications treats prompts as source-controlled code with versioning and diffing capabilities. This ensures consistent quality and reduces manual effort during prompt lifecycle management.
LLM prompt drift detection monitors and identifies changes in prompt performance caused by model updates or external factors. You need it to ensure your prompts remain effective and consistently produce expected outputs over time.
Evaluate LLM prompts by running specific prompt versions against predefined datasets to measure their performance. This process identifies quality changes and ensures prompts meet expected output standards.
Yes, full functionality for prompt evaluation and drift detection requires dependencies including the Claude API, agent forge, and RAG forge components. These provide the necessary environment for complete prompt lifecycle management.
The best way to track prompt changes during LLM model updates is using prompt versioning combined with drift detection. This monitors performance shifts caused by model updates and maintains prompt effectiveness through diffing capabilities.
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