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/ardiannurcahya/open-graph-memory/agents-mdgit clone --depth 1 https://github.com/ardiannurcahya/open-graph-memoryWrote 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/ardiannurcahya/open-graph-memory/agents-md)<a href="https://agentmods.dev/instructions/ardiannurcahya/open-graph-memory/agents-md"><img src="https://agentmods.dev/badge/instructions/ardiannurcahya/open-graph-memory/agents-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 5.1 | $0.00871 | $0.00871 |
| Opus 5 | $0.00436 | $0.00436 |
| Sonnet 5 | $0.00174 | $0.00174 |
| Haiku 4.5 | $0.00087 | $0.00087 |
Grade A, and why
open-graph-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 6d 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
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.
- 6d ago First seen · 44 lines · 871 tokens per session scan A 9833ba1d6dc2
open-graph-memory AGENTS.md is an instructions file published in the GitHub repository ardiannurcahya/open-graph-memory (114 stars, last pushed 13d ago), with no licence file. It adds 871 tokens to every session, about $0.0044 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.
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 ──.
engram-mcp CLAUDE.md
Claude Code instructions for edg-l/engram-mcp, covering engram mcp, development rules, structure, key types and mcp capabilities.
Waggle-mcp AGENTS.md
AGENTS.md instructions for Abhigyan-Shekhar/Waggle-mcp, covering repository agent rules, custom rules and waggle automatic memory.
Core-Memory CLAUDE.md
Instructions for JohnnyFiv3r/Core-Memory, covering claude.md — core memory, what this repo is, guiding principle — engineering simplicity, boring primitives, rich views and mapping to the current codebase.
dakera-cli CLAUDE.md
Claude Code instructions for Dakera-AI/dakera-cli, covering dakera-cli, key commands, architecture and conventions.
superlocalmemory copilot-instructions.md
Copilot instructions for qualixar/superlocalmemory, covering superlocalmemory (slm) — agent rules, session start, remember, recall and optimize (fail-open).