Borrowing it
Nothing to install: this file belongs to Coding-Dev-Tools/engraphis. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Coding-Dev-Tools/engraphis/main/AGENTS.mdgit clone --depth 1 https://github.com/Coding-Dev-Tools/engraphisWrote 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/coding-dev-tools/engraphis/agents-md)<a href="https://agentmods.dev/instructions/coding-dev-tools/engraphis/agents-md"><img src="https://agentmods.dev/badge/instructions/coding-dev-tools/engraphis/agents-md/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/instructions/coding-dev-tools/engraphis/agents-md"><img src="https://agentmods.dev/badge/instructions/coding-dev-tools/engraphis/agents-md.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 | $0.04947 | $0.04947 |
| Opus 5.5 | $0.01979 | $0.01979 |
| Sonnet 5.5 | $0.00989 | $0.00989 |
| Haiku 4.5 | $0.00495 | $0.00495 |
Grade A, and why
engraphis 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 305 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Engraphis
Engraphis is a local-first, open AI memory engine for agents — Ebbinghaus decay,
interaction-aware reinforcement, bi-temporal facts, hybrid recall, and a native
workspace → repo → session → memory hierarchy. Python 3.9+ for the core (Python 3.10+
for the server/MCP stack), FastAPI, SQLite, and local embeddings; the external LLM is optional
and pluggable.
This is the canonical operating manual for any AI agent working in this repo. CLAUDE.md
imports it. Read §0 before editing anything.
Internal subagent delegation
When parallel delegation is appropriate for ChatGPT/Codex tasks, use exactly four bounded subagents inside the current task and chat. Keep delegation at one level: workers return bounded results and the parent performs the sole integration. Subagents must never be sent to Orca, Orca orchestration, or separate user-visible threads. Before finalizing, verify that all four workers returned and that no forbidden routing or descendant delegation occurred.
0. Read this first — two architectures live in one package
There are two parallel codebases under engraphis/. Confusing them is the single
most common mistake here.
| v2 — current architecture (build here) | v1 — legacy reference server | |
|---|---|---|
| Status | Primary scoped, bi-temporal, interface-driven implementation. | Compatibility/reference implementation with flat namespaces. |
| Model | Scoped + bi-temporal + typed; interface-driven. | Single flat namespace string per memory. |
| Code | engraphis/core/, engraphis/backends/, eval/, tests/, scripts/migrate_to_v2.py |
engraphis/app.py, config.py, models.py, routes/, stores/, engines/, llm/, static/ |
| Data | new v2 schema (SCHEMA_VERSION = 18) |
engraphis_v1.db |
| Entry | engraphis.MemoryEngine.create() / engraphis.create_memory_engine() → engraphis/factory.py → core/engine.py |
Internal reference only; never a public launcher |
Rule: build new capability on v2 (core/ + backends/) behind the interfaces.
Only touch the v1 server for compatibility fixes or to keep the reference running. When a
task is ambiguous, decide which side it belongs to before editing.
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.
- 1mo ago Changed 98f073418382
- 1mo ago Changed 77571f62390e
- 1mo ago Changed · +8 lines · +96 tokens per session 8652885ced34
- 1mo ago First seen · 297 lines · 4,851 tokens per session scan A 3dc629864c59
engraphis AGENTS.md is an instructions file published in the GitHub repository Coding-Dev-Tools/engraphis (180 stars, last pushed today), licensed Apache-2.0. It adds 4,947 tokens to every session, about $0.0198 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).