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 instructions/drewmauldin/ai-cloud-memory/agents-mdgit clone --depth 1 https://github.com/DrewMauldin/AI-Cloud-MemoryWhat 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 | $0.00129 | $0.00129 |
| Opus 5 | $0.00064 | $0.00064 |
| Sonnet 5 | $0.00026 | $0.00026 |
| Haiku 4.5 | $0.00013 | $0.00013 |
Grade A, and why
AI-Cloud-Memory AGENTS.md 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 yesterday.
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
Repository agent rules
- Treat D1 as canonical and all vectors, exports and Markdown as rebuildable projections.
- Keep every read and mutation owner-scoped by the authenticated numeric GitHub ID.
- Never commit credentials, private memory content, real adopter identifiers or deployment URLs.
- Preserve lexical-only operation when optional AI services are disabled.
- Add tests for behavioural changes and run
npm run checkbefore merge. - Keep n8n, WebDAV, Obsidian, GitHub export and semantic search optional.
- Do not add Codex automated code review to the product. Maintainers configure Codex Cloud externally at repository level.
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.
- yesterday First seen · 10 lines · 129 tokens per session scan A 4184a79874ac
AI-Cloud-Memory AGENTS.md is an instructions file published in the GitHub repository DrewMauldin/AI-Cloud-Memory (0 stars, last pushed 2d ago), licensed MIT. It adds 129 tokens to every session, about $0.0006 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 2026-08-31.
Other instructions, from other repositories
TideMind AGENTS.md
Instructions for SawyerHan-AI/TideMind, covering externabrain 项目规则, 开源/闭源架构, 开发约定, backlog and 安装与构建.
mcp-better-vibe-kanban CLAUDE.md
Claude Code instructions for yigitkonur/mcp-better-vibe-kanban, covering claude.md, what this is, build & run, http transport (default port 3000) and environment variables.
kaneo CLAUDE.md
Claude Code instructions for usekaneo/kaneo, a project described as: 🎯 All you need. Nothing you don't. Open source project management that works for you, not against you.
flux AGENTS.md
Instructions for sirsjg/flux, covering agents.md, project overview, dogfooding, common commands and development.
BITE AGENTS.md
Instructions for RipeMangoBox/BITE, covering agent guide, working surface, local pipeline, branch sync policy and rules.
collattice CLAUDE.md
Instructions for MrBildo/collattice, covering collattice, repository rules — hard, tech stack, build & run and prerequisites.