memory
Skill1 starsChanged 7 months agoMITView on GitHub
Save conversation context to persistent memory for cross-session recall. Use this skill when the user says "memory", "保存记忆", "记住", "save memory", or any phrase indicating they want to preserve the current session's important information. Also use at the end of a session when the user is about to leave. This skill writes structured memory files to the project's auto-memory directory so future sessions can recall past context automatically.
99 other projects use a version of this.
Adopted by
Most recently taken up by
- jaydubya818/ClaudeClaw-Mission-Controltheir own version, first seen Nov 8, 2026
- naman10parikh/pennytheir own version, first seen Nov 8, 2026
- NaturNestAI-Labs/beings-protocoltheir own version, first seen Nov 8, 2026
- maxtechera/memorytheir own version, first seen Nov 8, 2026
- wubinKKK/private-ai-workbenchtheir own version, first seen Nov 8, 2026
- shetengteng/skillix-hubtheir own version, first seen Nov 8, 2026
Used with
Projects with it also use ecosystem-reference, fractal-delegation and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
naman10parikhSkillecosystem-reference
Quick-access directory of Claude Code ecosystem repos, skills, plugins, MCPs, and patterns. Use when improving the harness.
Also in 5 projects that use this
naman10parikhSkillfractal-delegation
Also in 5 projects that use this
Maliot100XSkillsend-user-message
Send a proactive message to a paired user via their channel (Discord, Telegram, or WhatsApp). Use when the agent needs to notify, alert, or send an unsolicited message to a user — especially during heartbeat invocations, scheduled tasks, or when the agent wants to reach out without a prior user message in the current conversation. Triggers: 'send message to user', 'notify user', 'alert user', 'message the user on discord/telegram/whatsapp', or any need to proactively communicate with a paired sender.
Also in 4 projects that use this
jh941213Skilldocs-ci
문서 CI(링크·OpenAPI lint·breaking 게이트·mermaid 검증)나 문서 드리프트 감지(docs.yaml 신선도 검사)를 설치하거나 돌릴 때 사용. 문서 내용 작성은 docs-architecture·docs-interfaces·docs-manuals.
Also in 3 projects that use this
jh941213Skilldocs-interfaces
API·이벤트 인터페이스 문서(OpenAPI·swagger·AsyncAPI 명세, 엔드포인트 레퍼런스, API 구성도·시퀀스, API CHANGELOG)를 만들거나 코드와 맞출 때 사용. 시스템 구성도는 docs-architecture, API 설계 원칙은 api-design-principles.
Also in 3 projects that use this
- +6 more from naman10parikh
- +1 more from jh941213
Other versions99 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 99
- google-gemini/gemini-cli★ 109ksame name
- jlia0/tinyclaw★ 3.6ksame name
- TinyAGI/tinyagi★ 3.6ksame name
- TinyAGI/tinyclaw★ 3.6ksame name
- Chachamaru127/claude-code-harness★ 3.2ksame name
- codeaholicguy/ai-devkit★ 1.7ksame name
- Muuuun/luxas★ 1.2ksame name
- shobcoder/shob★ 575same name
- boshu2/agentops★ 453same name
- makushingu/harness-maxxing★ 161same name
89 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repositoryOne other file it gives its agents.
- clean-memorySkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 82 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 14
When the user triggers this skill, extract and persist the key information from the current conversation.
- Distinctive: line 26
Always verify the project slug matches the current working directory before writing.
- Distinctive: line 37
Keep under 200 lines. This file is auto-loaded every session.
- Distinctive: line 97
Update, don't duplicate: If a memory file already exists on a topic, edit it rather than creating a new one.
“Common” is measured: kept by at least 6 in 10 of the 82 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Memory Skill
When the user triggers this skill, extract and persist the key information from the current conversation.
Storage location
Memory files live in the project's auto-memory directory:
.claude/projects/<project-slug>/memory/The <project-slug> is the project path with separators replaced by - (e.g., C--Users-tjm-Desktop-claude-Software-Dog). Find the exact path by checking ~/.claude/projects/ for directories matching the current project.
Always verify the project slug matches the current working directory before writing.
File structure
Two types of files to manage:
MEMORY.md (index file)
A lightweight index. Each entry one line under 150 chars, like:
- [Title](file.md) — one-line description of what this memory is aboutKeep under 200 lines. This file is auto-loaded every session.
Individual memory files (content files)
Each file has YAML frontmatter and markdown body:
---
name: short-name
description: one-line summary used to decide relevance
type: user | feedback | project | reference
---
Memory content. For feedback/project types, structure as:
rule/fact, then **Why:** and **How to apply:** lines.Types:
user— user's role, preferences, tech stack, knowledge levelfeedback— corrections to Claude's behavior, validated approachesproject— project goals, decisions, constraints, deadlinesreference— pointers to external resources (docs, dashboards, etc.)
What to save
Extract from the conversation:
- User facts — role, preferences, tech stack, coding style, language preference
- Project facts — what's being built, current branch, active tasks, constraints
- Decisions — technical choices made, trade-offs discussed
- Feedback — user corrections to Claude's approach (both "don't do X" and "exactly, keep doing Y")
- References — mentioned external links, dashboards, ticket trackers
What NOT to save
- Code patterns derivable from reading the repo
- Git history (use
git loginstead) - One-off bug fixes (the commit has the context)
- Ephemeral task details that won't matter next session
- Anything already documented in CLAUDE.md
Procedure
- Read existing MEMORY.md to understand what's already saved
- Identify new/updated information from the current conversation
- Write or update individual memory files — create new ones or edit existing ones if info has changed
- Update MEMORY.md index — add new entries, remove stale ones, keep under 200 lines
- Tell the user what was saved and where
Examples
User says: "memory" at the end of a coding session
Claude:
- Reads existing MEMORY.md
- Notices: user chose TypeScript over JavaScript, prefers composition over inheritance, project deadline is next Friday
- Creates/updates
user_prefs.md,project_state.md - Updates MEMORY.md index
- Reports: "Saved 3 memories: TypeScript preference, composition pattern, project deadline"
Principles
- Update, don't duplicate. If a memory file already exists on a topic, edit it rather than creating a new one.
- Keep it brief. Memory files should be short and focused. One topic per file.
- Be specific. "User prefers TypeScript" is better than "User has language preferences."
- Decay gracefully. Include dates for time-sensitive info so future Claude can judge relevance.
Does it work?
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

