mem0 is memory infrastructure that lets AI agents and applications store and retrieve information across interactions. It supports agents and developers who need persistent context for AI systems.
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 skills add mem0ai/mem0 --skill resumegit clone --depth 1 https://github.com/mem0ai/mem0Wrote 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/mem0ai/mem0/resume)<a href="https://agentmods.dev/skills/mem0ai/mem0/resume"><img src="https://agentmods.dev/badge/skills/mem0ai/mem0/resume/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mem0ai/mem0/resume"><img src="https://agentmods.dev/badge/skills/mem0ai/mem0/resume.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00018 | $0.00112 |
| Opus 5.5 | $0.00007 | $0.00045 |
| Sonnet 5.5 | $0.00004 | $0.00022 |
| Haiku 4.5 | $0.00002 | $0.00011 |
Grade A, and why
resume scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Resume memory capture
Resume memory capture for this machine.
Run:
python3 "${ANTIGRAVITY_PLUGIN_ROOT}/core/memory_cli.py" --harness "antigravity" resume
Confirm to the user that capture is active again. New sessions record evidence and create memories as normal; nothing that happened while paused is retroactively captured.
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.
- 1mo ago Changed 407107a19a45
- 1mo ago First seen · 20 lines · 18 tokens per session scan A 818dfab7b9cf
resume is a skill published in the GitHub repository mem0ai/mem0 (67,242 stars, last pushed yesterday), licensed Apache-2.0. It adds 18 tokens to every session and 112 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-02.
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