by Tencent · Codex Skill · ★ 4.5k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is TencentDB-Agent-Memory safe to install? View the security audit →
Agents remember,Humans innovate. Highlights · Overview · Core Technology · Features · Quick Start English · 简体中文 ✨ Highlights TencentDB Agent Memory = symbolic short-term memory + layered long-term memory. - Symbolic short-term memory offloads heavy tool logs and condenses them into compact Mermaid symbols, cutting token usage and improving task success. - Layered long-term memory distills fragmented conversations into structured personas and scenes, instead of flat vect
No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
| Stars | 4,540 |
| Forks | 379 |
| Language | TypeScript |
| Category | Codex Skill |
| Quality Score | 68.9686248318477/100 |
| Open Issues | 56 |
| Last Updated | 2026-06-02 |
| Created | 2026-04-07 |
| Platforms | node |
| Est. Tokens | ~216k |
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Explore other popular codex skill tools:
TencentDB-Agent-Memory is TencentDB Agent Memory delivers fully local long-term memory for AI Agents via a 4-tier progressive pipeline, with zero external API dependencies.. It is categorized as a Codex Skill with 4.5k GitHub stars.
TencentDB-Agent-Memory is primarily written in TypeScript. It covers topics such as agent, ai-agent, embedding.
You can find installation instructions and usage details in the TencentDB-Agent-Memory GitHub repository at github.com/Tencent/TencentDB-Agent-Memory. The project has 4.5k stars and 379 forks, indicating an active community.
The top alternatives to TencentDB-Agent-Memory on Agent Skills Hub include MemOS, Acontext, note-gen. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: