How do I install the Toward Efficient Agents Memory Tool Learning And skill?

Run npx skillmds@latest add adu2021/toward-efficient-agents-memory-tool-learning-and in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Toward Efficient Agents Memory Tool Learning And safe to use?

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Which AI agents work with Toward Efficient Agents Memory Tool Learning And?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Toward Efficient Agents Memory Tool Learning And free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Toward Efficient Agents Memory Tool Learning And?

adu2021 (@adu2021) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Toward Efficient Agents Memory Tool Learning And by adu2021

Name: Toward Efficient Agents Memory Tool Learning And
Author: adu2021

Toward Efficient Agents Memory Tool Learning And

Recent years have witnessed increasing interest in extending large language models into agentic systems. While the effectiveness of agents has continued to improve, efficiency, which is crucial for real-world deployment, has often been overlooked. This paper therefore investigates efficiency from three core components of agents: memory, tool learning, and planning, considering costs such as latency, tokens, steps, etc. Aimed at conducting comprehensive research addressing the efficiency of the a...

adu2021 0a883b8 1.8 KB Updated Sep 17, 2026

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Problem

Toward Efficient Agents addresses key challenges in autonomous agent development. This paper provides solutions for evaluating, building, or improving agent systems.

Key Approach

The paper introduces a novel framework, methodology, or benchmark for toward efficient agents. The core contributions include:

Systematic framework or benchmark for agent evaluation and development
Empirical findings on agent performance, efficiency, or capabilities
Generalizable principles applicable across domains

When to Use

Use this skill when you need to:

Evaluate or benchmark autonomous agent systems
Understand best practices in agent design and evaluation
Learn empirical results on agent performance
Improve agent efficiency, reasoning, or capabilities

When NOT to Use

For non-agent-related tasks
When seeking quick implementation code (see the paper for details)
For general knowledge unrelated to autonomous agents

Resources

ArXiv Abstract: https://arxiv.org/abs/2601.14192
Full PDF: https://arxiv.org/pdf/2601.14192
HTML Version: https://arxiv.org/html/2601.14192

See the paper for comprehensive methodology, experimental protocols, benchmarks, and implementation details.

Frequently asked questions