genpark-agent-dynamic-few-shot-example-selector-skill
Enables MCP-compliant clients and autonomous agents to pick optimal few-shot in-context exemplars by combining semantic token overlap, cosine similarity, and Maximal Marginal Relevance diversity ranking for prompt optimization. Runs deterministically on the Python standard library with zero external dependencies, avoiding frontier LLM round-trips for sub-millisecond selection.
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