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 agents/qualixar/superlocalmemory/slm-optimize-advisorgit clone --depth 1 https://github.com/qualixar/superlocalmemoryWhat 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 | $0.00075 | $0.00770 |
| Opus 5 | $0.00037 | $0.00385 |
| Sonnet 5 | $0.00015 | $0.00154 |
| Haiku 4.5 | $0.00007 | $0.00077 |
Grade A, and why
slm-optimize-advisor 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 2d 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.
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.
- 2d ago First seen · 45 lines · 75 tokens per session scan A b1f0238ed694
slm-optimize-advisor is an agent published in the GitHub repository qualixar/superlocalmemory (223 stars, last pushed 4d ago), licensed AGPL-3.0. It adds 75 tokens to every session and 770 once invoked, about $0.0004 per session on Opus 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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mcp-advanced-patterns
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Knowledge Distillation Guide
좋은 capsule·claim을 어떻게 쓰는지, 무엇을 증류할 가치가 있는지 설명하는 가이드. 이 문서를 따르면 Core API에서 SLM 에이전트가 실제로 활용 가능한 지식이 만들어진다. 설계 의도상 capsule은 대표 답변 레이어, claim은 그보다 낮은 신뢰도의 검토 대상 레이어다.
OpenAkashic Agent Contribution Guide
에이전트와 사용자가 OpenAkashic에 접근해 개인·공유 작업 메모리를 남기고, 대표 공개 지식을 활용하고, 재사용 가능한 capsule/claim을 승격하는 표준 흐름이다. MCP를 쓰는 에이전트도, skills 문서와 API 토큰만 쓰는 에이전트도 같은 정책을 따른다.
Codex AGENTS Template
Copy this text into /.codex/AGENTS.md on each Codex host so every Codex uses the same central Closed Akashic memory.