What is engrava AGENTS.md?

Repository instructions for coding agents working on engrava, a Python graph-memory database for AI agents. They explain what to read before making commits and how to keep public repository changes safe and consistent.

Use them when editing engrava, preparing commits or pull requests, naming branches, or checking repository-specific testing and contribution requirements.

They give agents the project context and contribution rules before they change code. This helps avoid poorly formatted commits, unsafe public wording, and incorrect branches.

How sovantica/engrava configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to sovantica/engrava. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/sovantica/engrava/dev/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/sovantica/engrava

Made for: Codex, OpenCode.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/sovantica/engrava/agents-md/github.svg)](https://agentmods.dev/instructions/sovantica/engrava/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/sovantica/engrava/agents-md"><img src="https://agentmods.dev/badge/instructions/sovantica/engrava/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.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/sovantica/engrava/agents-md"><img src="https://agentmods.dev/badge/instructions/sovantica/engrava/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 785 This file is loaded in full into every session.

When invoked 785 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00785	$0.00785
Opus 5.5	$0.00314	$0.00314
Sonnet 5.5	$0.00157	$0.00157
Haiku 4.5	$0.00078	$0.00078

Measured 1mo ago against content hash 28281265208e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

engrava 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

engrava-mcp AGENTS.md — 92% identical, 6 lines differ

AGENTS.md · 60 lines

How it starts

The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — engrava

Canonical guidance for AI coding agents (Claude Code, GitHub Copilot, Cursor, Aider, Continue, OpenAI Codex CLI, and others) working in this repository.

Repository context

This is a public repository (engrava) — Graph memory database for AI agents. License: MIT. Primary language: python 3.11+.

Assume every commit message, PR title, PR body, branch name, code comment, and docstring is world-visible. Public-safe by default.

Required reading before generating commits

CLAUDE.md — full context for this repo (quality bar, testing conventions, commit format, branching).
CONTRIBUTING.md — contribution flow.
.github/copilot-instructions.md — architecture, naming patterns, scope reference.
BRANCHING.md — branch naming + flow.

Commit hygiene

Conventional Commits 1.0.0 — <type>(<scope>): <description>. Types in CLAUDE.md.
Public release tags (vX.Y.Z) and this repo's GitHub issue/PR numbers (#N) are your durable identifiers.
Locally-documented ADRs (docs/adr/ADR-NNN-*.md) may be referenced once the file exists in this repo.
Generic feature descriptions and Conventional Commit headers are always welcome.

A commit-message hook is installed locally to give you a fast feedback loop on commit-message hygiene. Run git commit and it fires on the patterns it checks for. It is a pattern check, not a judge of whether a message reads well for a public project - what it does not check is still yours and the reviewer's to get right.

Branch hygiene

Branch names: <type>/<kebab-description>. Plain English. No internal identifiers. ≤ 50 chars.

Examples:

feature/priority-signal-hybrid-search
fix/empty-count-on-mindql
docs/quickstart-update

Self-check before every commit

Before finalising a commit message, ask:

Could this message, branch name, or referenced symbol reveal information about a workflow that should stay private?
Am I using only durable public identifiers (release tags, this repo's issue/PR numbers, locally-documented ADRs)?
Is the message format Conventional Commits?
Is the branch name plain English in <type>/<kebab-description> form?

Read the full file on GitHub · 60 lines

Changes

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 · +1 lines · +62 tokens per session 28281265208e
2mo ago First seen · 59 lines · 723 tokens per session scan A 6bf53da7a3ea

Subscribe to this mod's changes

engrava AGENTS.md is an instructions file published in the GitHub repository sovantica/engrava (12 stars, last pushed 4d ago), licensed MIT. It adds 785 tokens to every session, about $0.0031 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 2026-08-31.

Autonomous Agents agent-memory ai-agents durable-memory graph-database graph-memory

engrava AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
engrava AGENTS.mdsovantica/engrava	Instructions file	12	4d ago	MIT	A	785	Codex, OpenCode
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	today	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	yesterday	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot
deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness	Instructions file	274k	2d ago	MIT	A	4,313	Codex, OpenCode

engrava: Instructions file for Codex