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Memory

  • 349 installs
  • 24 repo stars
  • Updated December 19, 2025
  • johnlindquist/claude

memory is an agent skill that stores and retrieves project knowledge across sessions using the basic-memory CLI and semantic search for developers who need coding agents to recall facts, preferences, and decisions.

About

memory is an agent skill from johnlindquist/claude that provides persistent knowledge storage across coding sessions using the basic-memory CLI. After pip install basic-memory, agents write notes with basic-memory tool write-note—including title, markdown content, and optional tags—and retrieve them via semantic search to rebuild topic context between sessions. Developers reach for memory when project facts, architectural decisions, or preferences must survive session boundaries without re-prompting from scratch each time. The skill supports folder-targeted notes, tagged retrieval, and topic-based context building for long-running repositories where volatile context windows lose institutional knowledge. memory complements file-based planning skills by storing unstructured recall policies and searchable knowledge rather than phased task plans.

  • Session vs long-term memory
  • Retrieval and ranking
  • Write/update policies
  • Privacy and scope boundaries
  • Conflict resolution

Memory by the numbers

  • 349 all-time installs (skills.sh)
  • +5 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #2,139 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 2, 2026 (Skillselion catalog sync)
npx skills add https://github.com/johnlindquist/claude --skill memory

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Listed on Skillselion
Installs349
repo stars24
Last updatedDecember 19, 2025
Repositoryjohnlindquist/claude

How do you give coding agents persistent memory across sessions?

Design persistent memory stores and recall policies so coding agents retain project facts, preferences, and decisions across sessions.

Who is it for?

Developers who want coding agents to retain project facts, preferences, and decisions across sessions using basic-memory semantic search instead of re-explaining context.

Skip if: Developers who only need phased task tracking with status gates—use planning-with-files for structured multi-step plans instead of unstructured recall.

When should I use this skill?

Project facts, preferences, or decisions must be saved or semantically searched across multiple coding agent sessions.

What you get

Tagged markdown notes in basic-memory stores and semantically retrieved context bundles for future agent sessions.

  • tagged knowledge notes
  • semantic search results

Files

SKILL.mdMarkdownGitHub ↗

Memory - Persistent Knowledge Storage

Store and retrieve knowledge across sessions using semantic search.

Prerequisites

Install basic-memory:

pip install basic-memory

CLI Reference

Write a Note

# Basic note
basic-memory tool write-note --title "Note Title" --content "Note content in markdown"

# With tags
basic-memory tool write-note --title "React Patterns" --content "# Content here" --tags "react,patterns,frontend"

# To specific folder
basic-memory tool write-note --title "Meeting Notes" --content "# Notes" --folder "meetings"

# With specific project
basic-memory tool write-note --title "Project Notes" --content "# Notes" --project myproject

Read a Note

# By identifier/permalink
basic-memory tool read-note "note-title"

# From specific project
basic-memory tool read-note "note-title" --project myproject

Search Memories

# Semantic search (query is positional)
basic-memory tool search-notes "your search query"

# Limit results
basic-memory tool search-notes "react hooks" --page-size 10

# Search by permalink
basic-memory tool search-notes "pattern" --permalink

# Search by title
basic-memory tool search-notes "meeting" --title

# Filter by date
basic-memory tool search-notes "feature" --after_date "7d"

# With specific project
basic-memory tool search-notes "authentication" --project myproject

Build Context for a Topic

# Get related notes for a URL/topic (URL is positional)
basic-memory tool build-context "memory://topic/authentication"

# With depth and timeframe
basic-memory tool build-context "memory://note/my-note" --depth 2 --timeframe 30d

# With specific project
basic-memory tool build-context "memory://topic/api" --project myproject

List Recent Activity

# Default (depth 1, 7 days)
basic-memory tool recent-activity

# With depth
basic-memory tool recent-activity --depth 3

# With timeframe
basic-memory tool recent-activity --timeframe 30d

# Combined
basic-memory tool recent-activity --depth 3 --timeframe 14d

Continue Conversation

# Get prompt to continue previous work
basic-memory tool continue-conversation "previous topic or context"

Sync Database

basic-memory sync

Check Status

basic-memory status

Note Format

Notes are stored as markdown with YAML frontmatter:

---
title: My Note
tags: [tag1, tag2]
created: 2024-01-15
---

# My Note

Content here in markdown format.

## Sections

More content...

Workflow Patterns

Save Learning

When you discover something useful:

basic-memory tool write-note \
  --title "TypeScript Utility Types" \
  --content "# Utility Types\n\n- Partial<T> - Makes all properties optional\n- Required<T> - Makes all properties required\n- Pick<T, K> - Picks specific properties" \
  --tags "typescript,types,reference"

Save Decision

When making an architectural decision:

basic-memory tool write-note \
  --title "Auth Strategy Decision" \
  --content "# Decision: Use JWT for API auth\n\n## Context\n...\n\n## Decision\n...\n\n## Consequences\n..." \
  --tags "architecture,auth,decision" \
  --folder "decisions"

Retrieve Context

Before starting related work:

# Search for relevant notes
basic-memory tool search-notes "authentication jwt tokens"

# Or build comprehensive context
basic-memory tool build-context "memory://topic/api-authentication"

Review Recent Work

basic-memory tool recent-activity --depth 5 --timeframe 7d

Use Cases

Personal Wiki

  • Store code snippets and patterns
  • Document project decisions
  • Keep reference material

Learning Log

  • Record things you learn
  • Tag by topic for later retrieval
  • Build knowledge over time

Project Context

  • Save project-specific knowledge
  • Retrieve relevant context at session start
  • Share knowledge across sessions

Best Practices

1. Use meaningful titles - They become permalinks 2. Add tags - Improves search and organization 3. Use markdown - Full markdown support in content 4. Organize with folders - Group related notes 5. Search before writing - Check if knowledge already exists 6. Keep notes focused - One topic per note 7. Update, don't duplicate - Revise existing notes

Integration Pattern

Session Start

# Get context for today's work
basic-memory tool build-context "memory://topic/feature-youre-building"

During Work

# Save discoveries
basic-memory tool write-note --title "Discovery Title" --content "What I learned"

Session End

# Sync to ensure persistence
basic-memory sync

Related skills

FAQ

What CLI does the memory skill use?

memory uses the basic-memory CLI installed via pip install basic-memory. Agents write notes with basic-memory tool write-note (title, markdown content, optional tags) and retrieve knowledge through semantic search across sessions.

How is memory different from planning-with-files?

memory stores unstructured project knowledge and recall policies via basic-memory semantic search. planning-with-files maintains structured phased plans in task_plan.md, findings.md, and progress.md with completion gates.

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