toefl-prep AGENTS.md

toefl-prep AGENTS.md is an instructions file for Codex, OpenCode from epicsagas/toefl-prep. It costs 1,035 tokens per session, scanned A, original, MIT.

Project instructions for a TOEFL preparation add-on, including its responsibilities, required software, study schedule, and script locations. TOEFL is an English-language test with reading, listening, speaking, and writing sections.

In plain words
What is it for?
Use them when handling TOEFL requests, calculating the current study week or daily schedule, and finding the add-on's scripts, rubrics, and configuration.
Why use it?
They give coding agents a shared source of instructions and explain which tools must already be installed before the add-on can work.

Instructions file for CodexOpenCode

Installs and runs on its own, but its text points at files inside the plugin that ships it — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed.

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/epicsagas/toefl-prep/agents-md
Clone the repo
git clone --depth 1 https://github.com/epicsagas/toefl-prep

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.

agentmods badge for toefl-prep AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/epicsagas/toefl-prep/agents-md.svg)](https://agentmods.dev/instructions/epicsagas/toefl-prep/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/epicsagas/toefl-prep/agents-md"><img src="https://agentmods.dev/badge/instructions/epicsagas/toefl-prep/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,035 This file is loaded in full into every session.
When invoked 1,035 The same file — it is already loaded in full.
Security scan A 1 finding. 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 $0.01035 $0.01035
Opus 5 $0.00517 $0.00517
Sonnet 5 $0.00207 $0.00207
Haiku 4.5 $0.00103 $0.00103

Measured 3d ago against content hash 35230e8f4e37, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

toefl-prep AGENTS.md scanned grade A with 1 finding 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 3d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -L https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin \
AGENTS.md · 51 lines

How it starts

The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — toefl-prep plugin

공유 에이전트 가이드. Claude Code·Codex·agy 세 호스트가 모두 이 파일을 시스템 프롬프트로 로드한다.

역할

TOEFL iBT 4주 집중 학습 플러그인. Reading/Listening/Speaking/Writing 4개 영역을 **로컬 모델(Ollama + whisper.cpp)**로 오프라인 평가한다. 워크플로·루브릭·채점 전략·한계 규칙은 skills/toefl/SKILL.md 가 권위적 문서다. 사용자가 토플 관련 요청("토플", "스피킹 연습", "라이팅 채점", "리딩 문제", "모의고사", "어떤 주차", "점수 확인" 등)을 하면 그 스킬을 따른다.

의존성 (사전 설치 필요)

이 플러그인은 외부 CLI에 의존한다. 자동 설치 훅이 없으므로 사용자가 사전에 설치해야 한다.

  • Ollama (LLM 평가/문제 생성): brew install ollama && ollama serve + ollama pull qwen2.5:7b-instruct (추천, M2 16GB 최적) 또는 ollama pull llama3.1:8b (폴백).
  • whisper.cpp (스피킹 STT): brew install whisper-cpp + 모델 다운로드:
    mkdir -p ~/.local/share/whisper
    curl -L https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin \
      -o ~/.local/share/whisper/ggml-base.en.bin
    
  • ffmpeg (오디오 정규화, 권장): brew install ffmpeg
  • PyYAML (로드맵 계산): pip3 install pyyamlscripts/roadmap.sh가 schedule.yaml 파싱에 사용.

스크립트(scripts/config.sh)가 모델 자동 선택을 시도하지만, 미설치 시 사용자에게 설치 명령을 안내한다.

학습 일정 (사용자 커스텀)

날짜/요일/시간대/목표는 하드코딩되지 않는다. ${TOEFL_DATA_DIR}/schedule.yaml이 단일 진실 원천이며, scripts/roadmap.sh가 현재 주차·D-day·오늘 스케줄을 계산한다. 템플릿은 skills/toefl/schedule.example.yaml. schedule.yaml이 없으면 roadmap.sh가 복사 안내를 출력한다.

스크립트/루브릭 경로

  • 평가 스크립트: ${CLAUDE_PLUGIN_ROOT}/scripts/ 아래.
    • Claude Code → ${CLAUDE_PLUGIN_ROOT}
    • Codex / agy → 각 호스트의 플러그인 루트 환경 변수로 치환. 변수를 모르면 스킬 디렉토리를 먼저 식별한 뒤 절대경로로 실행.
  • 루브릭: ${CLAUDE_PLUGIN_ROOT}/rubrics/{reading,listening,speaking,writing}.md.
  • 데이터 저장: OS 문서 폴더 하위 ~/Documents/toefl-prep/ (macOS/Linux). 환경변수 TOEFL_DATA_DIR로 오버라이드 (레거시 TOEFL_VAULT_DIR 호환). 공개 레포이므로 로컬 경로를 하드코딩하지 않는다.
  • schedule.yaml 자동 생성 금지: roadmap.sh는 schedule.yaml이 없으면 사용자에게 대화형으로 묻고 Y일 때만 템플릿을 복사한다. 자동으로 덮어쓰지 않는다.

호스트별 차이

  • Claude Code: commands/ (5개 슬래시 명령) + SKILL 모두 사용.
  • Codex / agy: commands/ 미지원 → SKILL.md의 "의도 → 액션 매핑" 표를 따라 동일한 워크플로를 스크립트 직접 호출로 수행.

윤리·정직성 (요약 — 전문은 SKILL.md)

Read the full file on GitHub · 51 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. 3d ago First seen · 51 lines · 1,035 tokens per session scan A 35230e8f4e37

Subscribe to this mod's changes

toefl-prep AGENTS.md is an instructions file published in the GitHub repository epicsagas/toefl-prep (1 stars, last pushed yesterday), licensed MIT. It adds 1,035 tokens to every session, about $0.0052 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.