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 qualixar/superlocalmemory --skill slm-loopgit clone --depth 1 https://github.com/qualixar/superlocalmemoryWrote 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/qualixar/superlocalmemory/slm-loop)<a href="https://agentmods.dev/skills/qualixar/superlocalmemory/slm-loop"><img src="https://agentmods.dev/badge/skills/qualixar/superlocalmemory/slm-loop/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/qualixar/superlocalmemory/slm-loop"><img src="https://agentmods.dev/badge/skills/qualixar/superlocalmemory/slm-loop.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 | $0.00178 | $0.02418 |
| Opus 5.5 | $0.00071 | $0.00967 |
| Sonnet 5.5 | $0.00036 | $0.00484 |
| Haiku 4.5 | $0.00018 | $0.00242 |
Grade A, and why
slm-loop 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 today.
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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- today Changed 9ce433b1bc74
- yesterday Changed 666d5cdeb25b
- 2d ago Changed 7d18037e7904
- 3d ago Changed · +1 lines · +5 tokens per session 03955cefcac4
- 4d ago Changed · +20 lines fa9433eba0f4
- 8d ago Changed · +54 lines · +28 tokens per session 7d26a5612bef
- 10d ago Changed b249a084f5c7
- 12d ago Changed 83075ddb93d4
- 14d ago Changed 54e35a76df45
- 1mo ago First seen · 100 lines · 145 tokens per session scan A 198a914173ef
slm-loop is a skill published in the GitHub repository qualixar/superlocalmemory (249 stars, last pushed today), licensed AGPL-3.0. It adds 178 tokens to every session and 2,418 once invoked, about $0.0007 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 2026-08-30.
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