NornicDB: Instructions file for Codex

AGENTS.md

NornicDB AGENTS.md is an instructions file for Codex, OpenCode from orneryd/NornicDB. It costs 7,263 tokens per session, scanned A, original, MIT.

A development guide for NornicDB, a graph database designed to work with Neo4j-compatible applications. It sets expectations for performance, correctness, compatibility, tests, and documentation.

In plain words
What is it for?
Use it when changing NornicDB code, especially for benchmarking, memory checks, compatibility tests, coverage, API documentation, and test-driven bug fixes.
Why use it?
It gives coding agents project rules for proving changes are useful and avoiding regressions.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions AGENTS.md.

This is orneryd/NornicDB's own configuration. It tells Codex and OpenCode how to work on NornicDB itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything NornicDB configures →

Reuse

Borrowing it

Nothing to install: this file belongs to orneryd/NornicDB. 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/orneryd/NornicDB/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/orneryd/NornicDB

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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Per session 7,263 This file is loaded in full into every session.
When invoked 7,263 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.07263 $0.07263
Opus 5.5 $0.02905 $0.02905
Sonnet 5.5 $0.01453 $0.01453
Haiku 4.5 $0.00726 $0.00726

Measured 4d ago against content hash e7be09a59f3d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

NornicDB 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 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.

AGENTS.md · 940 lines

How it starts

The opening of the file, as written. The whole thing — 940 lines — stays where its author put it; the contents beside it link to each section on GitHub.

NornicDB Development Guide for AI Agents

Version: 1.0.0
Last Updated: 2024-12-01
Target Audience: AI coding agents (Claude, GPT-4, etc.)


Coding and review principles

Read and apply the standing design principles while choosing a solution, writing code, and correcting code. Apply Rule 73 when corrections repeatedly fail or repeat an unsuccessful approach. Explicit user instructions take precedence over repository guidance.

Verification and review

  • Lead proof with the requested product outcome, its supported conclusion, evidence, and practical limits. Verify the complete affected correction, including its public paths and consumers; a helper-only test does not establish that the public path reaches that helper.
  • Establish the approved contract and preserve the original failing evidence. Distinguish an established defect from an unapproved precaution: reproducing an exceptional scenario does not by itself justify adding behavior.
  • Scope regression checks to affected contracts and input boundaries. Do not claim broad correctness from statement coverage, static candidates, or a narrower input population.
  • Review and verify the integrated current source. Related fixes tested in separate branches do not prove their combined implementation works. Evidence from changed source must have its continuing applicability established.
  • Report what was actually checked, including failures, cancellations, cached results, skips and limitations. A canceled or superseded run is incomplete; cached evidence is not a fresh run.
  • Follow the applicable checks and baselines in CONTRIBUTING.md. Do not weaken assertions, waive regressions, or substitute an unrelated benchmark to obtain a passing result.
  • When a failure recurs, reassess the causal owner, approach and verification that missed it. Complete the integrated correction and its required review and proof before declaring the issue resolved.

Read the full file on GitHub · 940 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.

  1. 4d ago Changed · +62 lines · +818 tokens per session e7be09a59f3d
  2. 5d ago Changed · +20 lines · +445 tokens per session e20ce091b21a
  3. 1mo ago Changed · +16 lines · +43 tokens per session 3f6691417e10
  4. 1mo ago First seen · 842 lines · 5,957 tokens per session scan A d99a2b788f94

Subscribe to this mod's changes

NornicDB AGENTS.md is an instructions file published in the GitHub repository orneryd/NornicDB (912 stars, last pushed today), licensed MIT. It adds 7,263 tokens to every session, about $0.0291 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.

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