remember

remember is a skill for Claude Code, Codex from Ramsbaby/jarvis. It costs 114 tokens per session (1,158 once invoked), scanned A, original, MIT.

A skill for saving confirmed facts, decisions, preferences, and important project context in the Jarvis wiki. The same stored information can be shared across its different interfaces.

In plain words
What is it for?
Use it when the user explicitly asks the system to remember something or when a durable project fact, preference, or safeguard has been confirmed.
Why use it?
It prevents useful decisions and constraints from being lost between conversations or tools.

Skill for Claude CodeCodex

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 skills/ramsbaby/jarvis/remember
Any agent
npx skills add Ramsbaby/jarvis --skill remember
Clone the repo
git clone --depth 1 https://github.com/Ramsbaby/jarvis

Made for: Claude Code, Codex.

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 remember

README.md
[![agentmods](https://agentmods.dev/badge/skills/ramsbaby/jarvis/remember.svg)](https://agentmods.dev/skills/ramsbaby/jarvis/remember)
Your own site
<a href="https://agentmods.dev/skills/ramsbaby/jarvis/remember"><img src="https://agentmods.dev/badge/skills/ramsbaby/jarvis/remember.svg" alt="Measured on agentmods" height="20"></a>
Per session 114 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,158 The whole file, excluding the scripts and references it only reads on demand.
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 $0.00114 $0.01158
Opus 5 $0.00057 $0.00579
Sonnet 5 $0.00023 $0.00232
Haiku 4.5 $0.00011 $0.00116

Measured 4d ago against content hash 3f81516d5e07, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

remember 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 4d 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.

.claude/skills/remember/SKILL.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

🧠 /remember — 표면 통합 기억 주입

핵심: 자비스는 뇌 하나다. 디스코드/CLI/macOS 앱은 그 뇌의 여러 입·출력 단말일 뿐. 이 스킬은 쓰기(write) 대칭을 담당한다. 읽기는 이미 rag_search / get_memory / get_wiki_context 등으로 표면 무관하게 동일.


사용 모드

모드 A — 명시적 사실 ($ARGUMENTS 있음)

/remember 2026-04-15 PR #24 머지 — 표면 통합 메모리 Phase 1 완료
  1. $ARGUMENTSfact로 그대로 취해 mcp__nexus__wiki_add_fact MCP 도구를 호출한다.
  2. 파라미터 구성:
    • fact: $ARGUMENTS (trim 후 5~500자 범위, 필요 시 분할 요청)
    • source: "claude-code-remember" (명시적 플러시 구분 태그)
    • domain: 명시 금지 (wiki-engine의 키워드 기반 자동 감지를 신뢰)
  3. 도구 응답의 domain 필드를 오너에게 1줄로 확인 응답:
    ✅ 위키 `{domain}` 도메인에 기록 완료.
    
  4. 호출 실패 시 에러 메시지를 투명하게 전달하고 재시도는 1회만.

모드 B — 최근 대화 자동 추출 ($ARGUMENTS 빈 문자열)

  1. 직전 35턴의 사용자·어시스턴트 메시지에서 미래 세션에 유용한 사실만 15개로 압축 추출한다.
  2. 각 사실에 대해 mcp__nexus__wiki_add_fact를 개별 호출 (병렬 금지 — 순차).
  3. 종료 후 요약 보고:
    ✅ 위키에 {N}개 주입:
    - {domain1}: {n1}개
    - {domain2}: {n2}개
    

추출 기준 (모드 B):

주입 스킵
✅ 구체적 기술 결정 + 왜 ❌ "~를 했다" 식 행동 요약 (git log 중복)
✅ 프로젝트 구조 확정 사실 ❌ diff / 코드 라인 / 변수명
✅ 오너 선호·규칙·금지사항 ❌ 일반 상식 / 프로그래밍 기초
✅ 재발 방지용 제약·주의사항 ❌ 임시 디버깅 출력 / 스택트레이스
✅ 진행 중 작업의 중요 맥락 ❌ 150자 넘는 긴 문장 (분할)

표면별 동작 보장

이 스킬은 MCP wiki_add_fact 도구를 통하기 때문에 MCP 클라이언트가 nexus를 로드한 환경에서만 동작한다:

표면 동작 비고
Claude Code CLI (이 repo) ~/.mcp.json에 nexus 등록됨 Phase 1 자동 수렴 + Phase 2 수동 주입 모두 가능
Claude macOS 앱 ~/Library/Application Support/Claude/claude_desktop_config.json에 nexus 등록 필요 유일한 기억 입금 창구 (Phase 1 자동 경로 불가)
디스코드 봇 ✅ 이미 claude-runner.jswikiAddFact 래퍼로 자동 주입 중 이 스킬 호출 불필요 (예외: 봇이 세션 중 명시적으로 쓰고 싶을 때)

nexus 미로드 환경이면 이 스킬은 에러를 반환하고 대안 경로를 제시하지 않는다 — fallback은 약속할 수 없는 기능을 약속하는 땜질이기 때문 (오너가 나중에 "왜 안 쌓였지?" 배신감).


실패 처리

  • MCP 도구 wiki_add_fact 호출 실패 → 오너에게 에러 메시지 그대로 전달, 재시도 1회, 2회 실패 시 abort
  • fact 길이 검증(5~500자) 실패 → 오너에게 분할 요청 (예: "사실이 너무 김 — 3개로 분할해주세요")
  • 중복 사실 (addFactToWiki가 내부에서 중복 감지하여 silent skip) → "이미 기록됨" 안내

Read the full file on GitHub · 81 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. 4d ago First seen · 81 lines · 114 tokens per session scan A 3f81516d5e07

Subscribe to this mod's changes

remember is a skill published in the GitHub repository Ramsbaby/jarvis (16 stars, last pushed 12d ago), licensed MIT. It adds 114 tokens to every session and 1,158 once invoked, about $0.0006 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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