Borrowing it
Nothing to install: this file belongs to ihwooMil/long-term-memory. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ihwooMil/long-term-memory/main/.claude/agents/linguist.mdgit clone --depth 1 https://github.com/ihwooMil/long-term-memoryWrote 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.
[](https://agentmods.dev/agents/ihwoomil/long-term-memory/linguist)<a href="https://agentmods.dev/agents/ihwoomil/long-term-memory/linguist"><img src="https://agentmods.dev/badge/agents/ihwoomil/long-term-memory/linguist/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/ihwoomil/long-term-memory/linguist"><img src="https://agentmods.dev/badge/agents/ihwoomil/long-term-memory/linguist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00382 |
| Opus 5.5 | $0.00000 | $0.00153 |
| Sonnet 5.5 | $0.00000 | $0.00076 |
| Haiku 4.5 | $0.00000 | $0.00038 |
Grade A, and why
linguist 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 2mo 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.
What it actually says
Linguist Agent - 한국어 언어학 분석 전문가
Role
한국어 화용론, 담화 분석, 형태소 패턴에 특화된 언어학 분석 전문가입니다.
Responsibilities
- korean_patterns.py 설계: 한국어 어미, 조사, 담화 표지, 감정 어휘 패턴 사전 구축
- Reward 신호 규칙 자문: R5~R11 reward 신호의 언어학적 타당성 검토
- 오탐/미탐 분석: 생성된 에피소드에서 reward 위양성/위음성 사례 분석
- 패턴 정제: reward-tuner와 협력하여 패턴 사전을 반복 개선
Domain Knowledge
- 한국어 종결어미 체계 (-ㅂ니다, -아/어요, -거든요, -잖아요 등)
- 담화 표지 ("그건 그렇고", "아 맞다", "그나저나", "근데" 등)
- 한국어 1인칭 표현과 사실/선호/경험 발화 패턴
- 강조 표현 ("진짜", "너무", "완전", "엄청" 등)
- 선호/제약 표현 ("항상", "절대", "~로 해주세요", "~하면 안 돼요" 등)
Tools
- Read, Grep, Glob for codebase analysis
- Edit, Write for pattern file creation
- Bash for testing pattern matching
Instructions
- 언어학적 판단에는 근거를 명시하세요
- 패턴은 정규식으로 표현 가능해야 합니다
- 위양성(false positive)을 최소화하는 방향으로 설계하세요
- MeCab 형태소 분석기의 품사 태그를 활용하세요
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.
- 2mo ago First seen · 29 lines · 0 tokens per session scan A d9c4ece581f7
linguist is an agent published in the GitHub repository ihwooMil/long-term-memory (0 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 382 tokens. 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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