graph-engineer AGENTS.md

A repository guide for the graph-engineer Codex skill, a reusable set of instructions for guiding engineering work. The repository contains the skill and its reference documents, not an application.

In plain words
What is it for?
Use it when maintaining or applying the graph-engineer skill. It helps with its eight-part work cycle, scenario templates, quality checks, review options, and source references.
Why use it?
It explains the repository’s structure, terminology, design rule, and relationship between the main instructions and README, reducing the chance of editing the wrong material.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/ranteck/graph-engineer/agents-md
Clone the repo
git clone --depth 1 https://github.com/Ranteck/graph-engineer

Made for: Codex, OpenCode.

Per session 1,672 This file is loaded in full into every session.
When invoked 1,672 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
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 $0.01672 $0.01672
Opus 5 $0.00836 $0.00836
Sonnet 5 $0.00334 $0.00334
Haiku 4.5 $0.00167 $0.00167

Measured 2d ago against content hash da600a86d70d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

graph-engineer 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 2d 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:

AGENTS.md · 117 lines

How it starts

The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file provides guidance to Codex (Codex.ai/code) when working with code in this repository.

What this repository is

This repo is a single Codex skill package named graph-engineer (plus its README/LICENSE). There is no application code, no build step, no test suite, and no package manifest — the repo's only artifact is the skill definition itself:

skills/graph-engineer/
├── SKILL.md                       # the skill's instructions (source of truth)
└── references/
    ├── goal-templates.md              # ready-to-use /goal templates per scenario
    ├── quality-gate-detection.md      # generic quality-gate command resolver algorithm
    ├── elevated-assurance.md          # optional opt-in multi-lens CRITIQUE variant
    ├── backend-selection.md           # opt-in per-cycle writer/reviewer routing
    └── sources.md                     # provenance: what's official Anthropic/OpenAI vs. not

README.md at the repo root is the human-facing explanation of the same skill and must stay consistent with skills/graph-engineer/SKILL.md — they describe the same 8-node cycle from two angles (marketing/usage vs. operational instructions). When editing one, check whether the other needs a matching update (e.g. node numbering, flag names, the anti-loop cutoff wording).

Working in this repo

There is nothing to build, lint, or test. "Development" here means editing Markdown (SKILL.md, README.md, the reference files) and keeping the following consistent across all of them:

  • The 8-node cycle order and names: PRE-FLIGHT → SPEC → IMPL → QUALITY GATE → CRITIQUE → DEBATE/TRIAGE → REFACTOR → VERIFY.
  • The single entry point claim: every Codex interaction routes through the codex:codex-rescue subagent — no other /codex:* command is invoked programmatically by this skill.
  • The pinned plugin version (openai-codex v1.0.6) that the routing assumptions were verified against. If that version changes, README.md, SKILL.md, and sources.md all reference it and need to move together. Elevated assurance's fan-in barrier specifically depends on this version's --resume-last semantics (see sources.md's Verification method section) — a plugin update that adds resume-by-thread-ID could relax that barrier's requirements, but don't assume it without re-verifying the source.

Read the full file on GitHub · 117 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. 2d ago First seen · 117 lines · 1,672 tokens per session scan A da600a86d70d

Subscribe to this mod's changes

graph-engineer AGENTS.md is an instructions file published in the GitHub repository Ranteck/graph-engineer (101 stars, last pushed 5d ago), licensed MIT. It adds 1,672 tokens to every session, about $0.0084 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.

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