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/myagenthubs/aimemo/claude-mdgit clone --depth 1 https://github.com/MyAgentHubs/aimemoWrote 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/instructions/myagenthubs/aimemo/claude-md)<a href="https://agentmods.dev/instructions/myagenthubs/aimemo/claude-md"><img src="https://agentmods.dev/badge/instructions/myagenthubs/aimemo/claude-md.svg" alt="Measured on agentmods" 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 | $0.00161 | $0.00161 |
| Opus 5 | $0.00081 | $0.00081 |
| Sonnet 5 | $0.00032 | $0.00032 |
| Haiku 4.5 | $0.00016 | $0.00016 |
Grade A, and why
aimemo CLAUDE.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 4d 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
aimemo Memory Instructions
Session Start
At the beginning of every session, call memory_context to load project context before doing any work.
During the Session
Call memory_store (entities mode) when you:
- Learn something new about the codebase architecture or design decisions
- Fix a bug or identify a root cause
- Make a significant implementation choice
Call memory_store (journal mode) when you:
- Complete a meaningful unit of work
- Encounter and resolve a non-obvious problem
Session End
Before the session ends, write a journal entry summarizing what was done:
memory_store({ journal: "..." })
Search Before Asking
Before asking the user to re-explain something, call memory_search first.
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.
- 4d ago First seen · 24 lines · 161 tokens per session scan A d4fcebe8e65f
aimemo CLAUDE.md is an instructions file published in the GitHub repository MyAgentHubs/aimemo (1 stars, last pushed 6mo ago), licensed MIT. It adds 161 tokens to every session, about $0.0008 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
engraphis AGENTS.md
AGENTS.md instructions for Coding-Dev-Tools/engraphis, covering agents.md — engraphis, internal subagent delegation, 0. read this first — two architectures live in one package, 1. commands and ── unified dashboard + memory inspector ──.
shodh-memory CLAUDE.md
Claude Code instructions for varun29ankuS/shodh-memory, covering shodh-memory project instructions, must rules, code standards, persistent memory (shodh-memory mcp) and codebase map.
neurostack CLAUDE.md
Instructions for raphasouthall/neurostack, covering neurostack - claude code guide, quick reference, installation, mcp server (recommended for claude code) and openai-compatible api.
wenlan CLAUDE.md
Claude Code instructions for 7xuanlu/wenlan, a project described as: Wenlan is a knowledge base for the AI-native age. Your AI agents capture what they learn, Wenlan keeps it current and distills it into source-cited wiki pages you can trust.
agentmemory-codex-windows AGENTS.md
Instructions for M-T-D-N/agentmemory-codex-windows, covering agentmemory — agent instructions, architecture, windows/codex downstream profile, consistency rules and code patterns.
cli AGENTS.md
Instructions for konteks/cli, covering agent instructions, project overview, tech stack, repository layout and common commands.