data-labeling
claudeData labeling: annotation guidelines, platforms, inter-annotator agreement, active learning, weak supervision, and label error detection.
1 skill · 1 command · 1 agent
0
claude
prompt-engineering
Prompt engineering: prompting techniques, system prompts, structured output, injection defense, DSPy, and prompt versioning.
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Plugin prompt-engineering from marketplace libre-mlops in HermeticOrmus/LibreMLOps-Claude-Code. Commands read from the repo's manifest — 1 month ago.
What it installs
Skills (1)
prompt-engineering-patternsPrompt patterns with code: chain-of-thought with few-shot examples, structured output with Pydantic and instructor, ReAct agents with tool calls, prompt injection defense, and DSPy optimization. Use when building prompts for a production LLM feature.
Slash commands (1)
/prompt-engineering:prompt-engDesign a prompt with the right technique, test it against labeled examples, optimize few-shot examples with DSPy, or version it with its evaluation results.
Subagents (1)
prompt-engineerUse this agent when writing, testing, or hardening prompts for a production LLM feature: choosing a technique (zero-shot, few-shot, chain-of-thought, ReAct), designing system prompts, getting structured output with Pydantic and instructor, defending against prompt injection, optimizing with DSPy, an
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