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 toozuuu/MemoryAI --skill memoryai-securitygit clone --depth 1 https://github.com/toozuuu/MemoryAIWrote 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/toozuuu/memoryai/memoryai-security)<a href="https://agentmods.dev/skills/toozuuu/memoryai/memoryai-security"><img src="https://agentmods.dev/badge/skills/toozuuu/memoryai/memoryai-security/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/toozuuu/memoryai/memoryai-security"><img src="https://agentmods.dev/badge/skills/toozuuu/memoryai/memoryai-security.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 | $0.00037 | $0.00468 |
| Opus 5.5 | $0.00015 | $0.00187 |
| Sonnet 5.5 | $0.00007 | $0.00094 |
| Haiku 4.5 | $0.00004 | $0.00047 |
Grade C, and why
memoryai-security scanned grade C with 2 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.
Instruction-override phrasingmediumPrompt injection
Text telling the model to disregard its earlier instructions or safety rules is the shape of a prompt injection, whoever wrote it.
- High-risk injection tokens (e.g. `IGNORE ALL PREVIOUS INSTRUCTIONS`) are defanged by inserting zero-width non-breaking spaces. Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Cloud metadata endpointmediumServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
- **SSRF Defense:** Outbound URLs to loopback (`127.0.0.1`), RFC1918 private subnets, and cloud metadata (`169.254.169.254`) are strictly blocked. Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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 First seen · 52 lines · 37 tokens per session scan C e2860e1dd5d6
memoryai-security is a skill published in the GitHub repository toozuuu/MemoryAI (0 stars, last pushed 1mo ago), with no licence file. It adds 37 tokens to every session and 468 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it C with 2 findings (instruction-override phrasing, cloud metadata endpoint). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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Open OwnMem Console, the local dashboard for this repository's memory. Use when the user asks to open the dashboard, see memory metrics, check recall quality, or set up the optional embedding lane. Requires a repository initialized with the dashboard layer.
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