terms-kr: Instructions file for Codex

AGENTS.md

terms-kr AGENTS.md is an instructions file for Codex, OpenCode from PyTorchKR/terms-kr. It costs 1,243 tokens per session, scanned A, original, MIT.

Repository instructions for an open-source Korean glossary of artificial-intelligence and machine-learning terms, built with React and TypeScript.

In plain words
What is it for?
Use them when editing the glossary, running its development or build commands, checking lint, or changing its pages and JSON data.
Why use it?
They give coding agents the project context, commands, architecture, and data layout needed to make changes safely.

Instructions file for CodexOpenCode

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

This is PyTorchKR/terms-kr's own configuration. It tells Codex and OpenCode how to work on terms-kr 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 terms-kr configures →

Reuse

Borrowing it

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

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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README.md
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Per session 1,243 This file is loaded in full into every session.
When invoked 1,243 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 $0.01243 $0.01243
Opus 5.5 $0.00497 $0.00497
Sonnet 5.5 $0.00249 $0.00249
Haiku 4.5 $0.00124 $0.00124

Measured 1mo ago against content hash af69fc827959, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

terms-kr 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.

AGENTS.md · 109 lines

How it starts

The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file provides guidance to AI coding agents working in this repository.

Project Context

AI/ML 용어집 - 빠르게 변화하는 AI/ML 분야의 용어를 표준화하여 사람과 AI 번역 도구 모두가 일관된 한국어 번역을 사용할 수 있도록 하는 오픈소스 프로젝트. 파이토치 한국 사용자 모임(PyTorchKR) 운영. 현재 PoC 단계이며, 수록된 용어 데이터는 AI 생성 초안.

Repository: PyTorchKR/terms-kr (branch: main)

Commands

npm install        # Install dependencies
npm run dev        # Dev server (http://localhost:5173), auto-copies data/ to public/data/
npm run build      # TypeScript check + Vite production build
npm run lint       # ESLint
npm run preview    # Preview production build

No test framework is configured. Validation runs in CI via inline Node script in .github/workflows/deploy.yml.

Architecture

Static SPA for AI/ML Korean terminology glossary. No backend; all data is JSON fetched at runtime.

Stack: React 19 + TypeScript + Vite + MUI v7, deployed to GitHub Pages (terms.kr).

Routing (App.tsx): HashRouter with lazy-loaded pages.

  • / -> SearchPage (search + alphabet filter)
  • /term/:termId -> TermDetailPage (accordion per meaning, related terms)
  • /about -> AboutPage

Data flow: data/index.json lists alphabet JSON files (a.json..w.json). At build time, prebuild copies data/ -> public/data/. At runtime, loadTerms.ts fetches all files in parallel via Promise.all, flattens, and sorts. The useTerms hook caches this; useSearch debounces (200ms) and filters across term, korean, synonyms.

Homepage: SearchPage embeds HeroSection (stats) + AlphabetNavigation (A-Z chips) + TermCard grid. The Layout component wraps non-home pages with AppBar + footer; home page hides AppBar.

Data Model

Defined in src/types/term.ts:

interface TermExample { en: string; ko: string; source?: string }
interface TermMeaning {
  korean: string              // Required
  definition: string          // Required
  examples: (string | TermExample)[]  // Union type for backward compat
  synonyms: string[]
}
interface Term {
  term: string
  meanings: TermMeaning[]
  issueNumber?: number       // GitHub Issue number for traceability
  notes?: string             // Editorial notes (why this translation was chosen)
}

Read the full file on GitHub · 109 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. 1mo ago Changed · -17 tokens per session af69fc827959
  2. 1mo ago First seen · 109 lines · 1,260 tokens per session scan A f28e7a830899

Subscribe to this mod's changes

terms-kr AGENTS.md is an instructions file published in the GitHub repository PyTorchKR/terms-kr (6 stars, last pushed today), licensed MIT. It adds 1,243 tokens to every session, about $0.0050 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.

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