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Effective Tool Design for AI Agents
tool-design
sickn33/antigravity-awesome-skills
434
This skill provides advanced guidelines for designing robust and effective tools specifically for autonomous AI agents. It shifts the focus from traditional developer APIs to contracts optimized for Language Models (LLMs). Key topics covered include treating tool descriptions as prompt engineering, implementing namespacing, applying the Consolidation Principle, and utilizing Architectural Reduction patterns (like file system access) to maximize agent reliability and workflow complexity.
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Neural Pattern Training and Consolidation
neural-train
ruvnet/ruflo
83
This tool manages the lifecycle of learned intelligence patterns, implementing the crucial DISTILL and CONSOLIDATE phases of the 4-step intelligence pipeline. It enables the capture of successful task knowledge, supports multi-domain adaptation via SONA or MicroLoRA, and consolidates learned patterns into long-term storage to prevent catastrophic forgetting.
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简体中文
English