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.
npx agentmods add skills/itlearning/study-ios/study-summarynpx skills add ITlearning/study-ios --skill study-summarygit clone --depth 1 https://github.com/ITlearning/study-iosWhat 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 | $0.00026 | $0.02302 |
| Opus 5 | $0.00013 | $0.01151 |
| Sonnet 5 | $0.00005 | $0.00460 |
| Haiku 4.5 | $0.00003 | $0.00230 |
Grade A, and why
study-summary 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.
How it starts
The opening of the file, as written. The whole thing — 282 lines — stays where its author put it; the contents beside it link to each section on GitHub.
study-summary - Learning Notes Generator
Learning notes generator with two modes: (두 가지 모드를 지원하는 학습 노트 생성 스킬)
- Classic: concise recap for quick review
- Mastery: detailed record with rules, misconceptions, and seed code history
Instructions
Terminology Policy (초심자 친화 용어 규칙)
Use Korean-first wording in the note where possible, and keep English terms in parentheses when needed. (노트 본문은 가능한 한 한국어 우선으로 쓰고, 필요한 경우 영어 용어를 괄호로 병기한다.)
If a technical term appears for the first time in the note, add a one-line plain explanation. (기술 용어가 처음 나오면 한 줄 쉬운 설명을 덧붙인다.)
Examples: (예시)
격리 경계 (isolation boundary): actor 외부에서 내부 상태를 직접 바꾸지 못하게 하는 경계경합 상태 (data race): 동시에 같은 값을 바꿔서 결과가 꼬이는 문제
Step 0: Language Selection
Ask the user to choose a language at the start using a selection flow, not free-form text input. (스킬 시작 시 자유 입력이 아니라 선택형 방식으로 언어를 받는다)
- 한국어 - 한국어로 노트를 작성합니다
- English - Write notes in English
Use platform-specific selection behavior:
- Codex CLI: use native option selection (
request_user_inputwith 2 options) when available. If unavailable, show numbered choices and ask for1or2. - Claude Code: use native option selection UI when available. If unavailable, show numbered choices.
- Gemini CLI: use native option selection UI when available. If unavailable, show numbered choices.
Choice mapping: 1 → 한국어, 2 → English
Use the selected language for the note content and all communication. Code and Swift keywords stay in English. (선택한 언어로 노트 내용과 소통을 진행한다. 코드와 Swift 키워드는 영어 그대로 유지한다.)
Study Mode Selection
Ask the user to choose a study mode using the same selection pattern: (같은 선택 방식으로 학습 모드를 선택하게 한다)
-
Classic (설명 중심, 추천)
- 핵심 개념 위주로 간결한 노트를 원할 때 적합
- 빠르게 복습할 수 있는 형태로 정리
- 처음 학습한 주제를 가볍게 기록하기 좋음
-
Mastery (훈련 중심)
- 학습자의 규칙/오답/혼동 포인트까지 상세 기록
- Core Loop seed 코드와 gate 결과를 남겨 재학습에 유리
- 취약점 추적과 다음 세션 연계에 적합
Choice mapping: (선택값 매핑)
1-> Classic2-> Mastery
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.
- 2d ago First seen · 282 lines · 26 tokens per session scan A c441baeb0eac
study-summary is a skill published in the GitHub repository ITlearning/study-ios (19 stars, last pushed 6mo ago), licensed MIT. It adds 26 tokens to every session and 2,302 once invoked, about $0.0001 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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