Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/jacksonl1/superchat/elite-longterm-memorynpx skills add JacksonL1/superChat --skill elite-longterm-memorygit clone --depth 1 https://github.com/JacksonL1/superChatWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jacksonl1/superchat/elite-longterm-memory)<a href="https://agentmods.dev/skills/jacksonl1/superchat/elite-longterm-memory"><img src="https://agentmods.dev/badge/skills/jacksonl1/superchat/elite-longterm-memory.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00045 | $0.02940 |
| Opus 5 | $0.00023 | $0.01470 |
| Sonnet 5 | $0.00009 | $0.00588 |
| Haiku 4.5 | $0.00005 | $0.00294 |
Grade C, and why
elite-longterm-memory scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf ~/.openclaw/memory/lancedb/ The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 409 lines · 45 tokens per session scan C 0c462819a00d
elite-longterm-memory is a skill published in the GitHub repository JacksonL1/superChat (2 stars, last pushed 4mo ago), with no licence file. It adds 45 tokens to every session and 2,940 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
elite-longterm-memory-zh
终极 AI Agent 记忆系统，适用于 Cursor、Claude、ChatGPT 和 Copilot。WAL 协议 + 向量搜索 + Git Notes + 云备份。永不丢失上下文，为 Vibe-coding 而生。.
elite-longterm-memory
Ultimate AI agent memory system. Combines bulletproof WAL protocol, vector search, git-based knowledge graphs, cloud backup, and maintenance hygiene. Never lose context again. For Clawdbot, Moltbot, Claude, GPT agents.
tencentdb-agent-memory
面向 Agent 团队的长期记忆基础设施。把"对话、文档、代码"沉淀为四类可复用记忆资产： Chat Memory（L0 对话 → L1 原子 → L2 场景 → L3 人格逐层沉淀）、Skill（带版本/资源/ 触发边界的可复用技能）、LLM-Wiki（文档知识）、CodeGraph（代码图谱）。部署形态为 memory-core + memory-hub + memory-proxy 三件套 + SDK，接入 OpenClaw / Hermes / Claude Code / CodeBuddy 等。当前版本 v2.0.0。.
lesson
Store a lesson learned from the current conversation. Triggered by /lesson command. Use when Master signals that the recent conversation contains a pitfall, fix, or key insight that should be persisted to long-term memory.
mem0-tour
Browses all stored memories grouped by category with full content display. Use when reviewing all project memories, exploring stored knowledge, onboarding to a project, or getting an overview of captured decisions, conventions, and learnings.
mem0-vercel-ai-sdk
Mem0 provider for Vercel AI SDK (@mem0/vercel-ai-provider). TRIGGER when: user mentions "vercel ai sdk", "@mem0/vercel-ai-provider", "createMem0", "retrieveMemories", "addMemories", "getMemories", "searchMemories", "mem0 vercel", "AI SDK provider", "AI SDK memory", or is using generateText/streamText with mem0. Also…