Awesome-Efficient-Agents: Survey and paper list on efficiency-guided LLM agents (memory, tool use, planning)

by yxf203 · Agent Tool · ★ 309

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 51/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-memoryawesomeefficiencyplanningsurveytool-learning

Quick Facts

Stars309
Forks14
CategoryAgent Tool
Quality Score51/100
Open Issues2
Last Updated2026-09-29
Created2026-01-13
Est. Tokens~28k

About Awesome-Efficient-Agents

Awesome Efficient Agents: A Survey of Memory, Tool Use, and Planning 🤝 Contributions welcome! This repository is actively maintained and continuously updated. Feel free to open an issue or submit a pull request to add papers, fix links, or improve categorization. ⚡Introduction Recent years have seen growing interest in extending large language models into agentic systems.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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