# Send Git-Based Knowledge Graph Memory System for Claude Code to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
## Suggested prompts
### New install

```text
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
```
### Upgrade existing

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
```json
{
  "schemaVersion": "1.0",
  "item": {
    "slug": "git-notes-memory",
    "name": "Git-Based Knowledge Graph Memory System for Claude Code",
    "source": "tencent",
    "type": "skill",
    "category": "开发工具",
    "sourceUrl": "https://clawhub.ai/mourad-ghafiri/git-notes-memory",
    "canonicalUrl": "https://clawhub.ai/mourad-ghafiri/git-notes-memory",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadUrl": "/downloads/git-notes-memory",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=git-notes-memory",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "packageFormat": "ZIP package",
    "primaryDoc": "SKILL.md",
    "includedAssets": [
      "memory.py",
      "README.md",
      "SKILL.md"
    ],
    "downloadMode": "redirect",
    "sourceHealth": {
      "source": "tencent",
      "slug": "git-notes-memory",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-05-03T16:31:41.117Z",
      "expiresAt": "2026-05-10T16:31:41.117Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=git-notes-memory",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=git-notes-memory",
        "contentDisposition": "attachment; filename=\"git-notes-memory-1.0.0.zip\"",
        "redirectLocation": null,
        "bodySnippet": null,
        "slug": "git-notes-memory"
      },
      "scope": "item",
      "summary": "Item download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this item.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/git-notes-memory"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    }
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/git-notes-memory",
    "downloadUrl": "https://openagent3.xyz/downloads/git-notes-memory",
    "agentUrl": "https://openagent3.xyz/skills/git-notes-memory/agent",
    "manifestUrl": "https://openagent3.xyz/skills/git-notes-memory/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/git-notes-memory/agent.md"
  }
}
```
## Documentation

### CRITICAL: SILENT OPERATION RULES

These rules are ABSOLUTE and must NEVER be violated:

NEVER ask "should I remember?" or "want me to save?"
NEVER announce "I'll remember this" or "saving to memory"
NEVER show memory command output to users
NEVER mention memory system unless user explicitly asks about it
JUST DO IT - silently in the background

### Quick Reference

# Replace $SKILL_PATH with actual path to memory.py
# Replace $DIR with the project directory path

python3 $SKILL_PATH/memory.py -p $DIR <command>

### Essential Commands

CommandWhen to Usesync --startALWAYS at session startsync --end '{"summary":"..."}'At session end (optional but recommended)remember '{"..."}' -t tags -i hStore important informationget <topic>Retrieve context about a topicsearch "<query>"Full-text search across all memoriesrecall -i <id>Get full details of a specific memory

### Importance Flags

FlagLevelWhen to Use-i cCriticalUser says "always remember", "never forget", explicit preferences-i hHighDecisions, architecture choices, user corrections, preferences-i nNormalGeneral information (default)-i lLowTemporary notes, might be pruned

### 1. Session Start (MANDATORY)

Always run sync --start at the beginning of every session:

python3 $SKILL_PATH/memory.py -p $DIR sync --start

Output explains:

{
  "b": "main",           // Current git branch
  "t": {"api": 5, "auth": 3},  // Top topics with memory counts
  "c": [...],            // Critical memories (always review these)
  "n": 42,               // Total memory count
  "h": [...]             // High-importance recent memories
}

Use this context to:

Understand what the user has been working on
Reference previous decisions
Maintain continuity across sessions

### 2. During Session

Silently remember when user:

Makes a decision: "Let's use PostgreSQL" → remember with -i h
States a preference: "I prefer tabs over spaces" → remember with -i h or -i c
Learns something: "Oh, so that's how async works" → remember with -i n
Sets a task: "We need to fix the login bug" → remember with -i n
Shares important context: Project requirements, constraints, goals

Retrieve context when:

User asks about something previously discussed → get <topic>
You need to recall a specific decision → search "<keywords>"
User references "what we decided" → check relevant memories

### 3. Session End (Recommended)

python3 $SKILL_PATH/memory.py -p $DIR sync --end '{"summary": "Brief session summary"}'

### Good Memory Structure

For decisions:

{"decision": "Use React for frontend", "reason": "Team expertise", "alternatives": ["Vue", "Angular"]}

For preferences:

{"preference": "Detailed explanations", "context": "User prefers thorough explanations over brief answers"}

For learnings:

{"topic": "Authentication", "learned": "OAuth2 flow requires redirect URI configuration"}

For tasks:

{"task": "Implement user dashboard", "status": "in progress", "blockers": ["API not ready"]}

For notes:

{"subject": "Project Architecture", "note": "Microservices pattern with API gateway"}

### Tags

Use tags to categorize memories for better retrieval:

-t architecture,backend - Technical categories
-t urgent,bug - Priority/type markers
-t meeting,requirements - Source context

### Core Commands

sync --start

Initialize session, get context overview.

python3 $SKILL_PATH/memory.py -p $DIR sync --start

sync --end

End session with summary (triggers maintenance).

python3 $SKILL_PATH/memory.py -p $DIR sync --end '{"summary": "Implemented auth flow"}'

remember

Store a new memory.

python3 $SKILL_PATH/memory.py -p $DIR remember '{"key": "value"}' -t tag1,tag2 -i h

get

Get memories related to a topic (searches entities, tags, and content).

python3 $SKILL_PATH/memory.py -p $DIR get authentication

search

Full-text search across all memories.

python3 $SKILL_PATH/memory.py -p $DIR search "database migration"

recall

Retrieve memories by various criteria.

# Get full memory by ID
python3 $SKILL_PATH/memory.py -p $DIR recall -i abc123

# Get memories by tag
python3 $SKILL_PATH/memory.py -p $DIR recall -t architecture

# Get last N memories
python3 $SKILL_PATH/memory.py -p $DIR recall --last 5

# Overview of all memories
python3 $SKILL_PATH/memory.py -p $DIR recall

### Update Commands

update

Modify an existing memory.

# Replace content
python3 $SKILL_PATH/memory.py -p $DIR update <id> '{"new": "content"}'

# Merge content (add to existing)
python3 $SKILL_PATH/memory.py -p $DIR update <id> '{"extra": "field"}' -m

# Change importance
python3 $SKILL_PATH/memory.py -p $DIR update <id> -i c

# Update tags
python3 $SKILL_PATH/memory.py -p $DIR update <id> -t newtag1,newtag2

evolve

Add an evolution note to track changes over time.

python3 $SKILL_PATH/memory.py -p $DIR evolve <id> "User changed preference to dark mode"

forget

Delete a memory (use sparingly).

python3 $SKILL_PATH/memory.py -p $DIR forget <id>

### Entity Commands

entities

List all extracted entities with counts.

python3 $SKILL_PATH/memory.py -p $DIR entities

entity

Get details about a specific entity.

python3 $SKILL_PATH/memory.py -p $DIR entity authentication

### Branch Commands

branches

List all branches with memory counts.

python3 $SKILL_PATH/memory.py -p $DIR branches

merge-branch

Merge memories from another branch (run after git merge).

python3 $SKILL_PATH/memory.py -p $DIR merge-branch feature-auth

### How It Works

Each git branch has isolated memory storage
New branches automatically inherit from main/master
After git merge, run merge-branch to combine memories

### Branch Workflow

1. User on main branch → memories stored in refs/notes/mem-main
2. User creates feature branch → auto-inherits main's memories
3. User works on feature → new memories stored in refs/notes/mem-feature-xxx
4. After git merge → run merge-branch to combine memories

### Memory Types (Auto-Detected)

The system automatically classifies memories based on content:

TypeTrigger Wordsdecisiondecided, chose, picked, selected, opted, going withpreferenceprefer, favorite, like best, rather, better tolearninglearned, studied, understood, realized, discoveredtasktodo, task, need to, plan to, next step, going toquestionwondering, curious, research, investigate, find outnotenoticed, observed, important, remember thatprogresscompleted, finished, done, achieved, milestoneinfo(default for unclassified content)

### Entity Extraction

Entities are automatically extracted for intelligent retrieval:

Explicit fields: topic, subject, name, category, area, project
Hashtags: #cooking, #urgent, #v2
Quoted phrases: "machine learning", "user authentication"
Capitalized words: React, PostgreSQL, Monday
Key terms: Meaningful words (common words filtered out)

### What to Remember

DO remember:

User decisions and their rationale
Stated preferences (coding style, communication style, tools)
Project architecture and constraints
Important context that affects future work
Tasks, blockers, and progress
Corrections ("actually, I meant..." → high importance)
Explicit requests to remember something → critical importance

DON'T remember:

Trivial conversation
Information easily derivable from code
Secrets, passwords, API keys
One-time questions with no future relevance
Duplicate information already stored

### Tier 0: sync --start

{
  "b": "feature-auth",                    // Current branch
  "t": {"auth": 5, "api": 3, "db": 2},   // Topics with counts
  "c": [{"id": "x", "s": "summary", "t": "preference"}],  // Critical
  "n": 15,                                // Total count
  "h": [{"id": "y", "s": "summary"}]     // High importance
}

### Tier 1: get/search

{
  "topic": "auth",
  "mem": [
    {"id": "abc", "s": "decided OAuth2", "t": "decision", "i": "h", "b": "main"}
  ]
}

### Tier 2: recall -i <id>

{
  "d": {"decision": "Use OAuth2"},  // Full data
  "e": ["auth", "oauth2"],          // Entities
  "t": "decision",                   // Type
  "g": ["architecture"],             // Tags
  "i": "h",                          // Importance
  "b": "main",                       // Branch
  "c": "2024-01-15T10:30:00",       // Created
  "u": "2024-01-15T10:30:00",       // Updated
  "a": 3,                            // Access count
  "ev": [{"n": "note", "t": "..."}] // Evolution notes (if any)
}

### Example Silent Flow

User: "Let's build a REST API with Python"
Claude: [silently: remember '{"decision": "REST API", "language": "Python"}' -t architecture -i h]
        [responds about REST API setup WITHOUT mentioning memory]

User: "I prefer FastAPI over Flask"
Claude: [silently: remember '{"preference": "FastAPI over Flask", "reason": "user preference"}' -i h]
        [continues discussion using FastAPI WITHOUT saying "I'll remember"]

User: "What did we decide about the API?"
Claude: [silently: get api]
        [uses retrieved context to answer accurately]

User: "Actually, let's use Flask instead"
Claude: [silently: remember '{"decision": "Changed to Flask", "previous": "FastAPI"}' -i h]
        [silently: evolve <fastapi-memory-id> "User changed preference to Flask"]
        [acknowledges change WITHOUT mentioning memory update]

### Troubleshooting

Memory not found:

Use search with different keywords
Check entities to see what's indexed
Use recall --last 10 to see recent memories

Context seems stale:

Always run sync --start at session beginning
Check current branch with branches

After git operations:

After git merge: run merge-branch <source-branch>
After git checkout: sync --start will load correct branch context
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: mourad-ghafiri
- Version: 1.0.0
## Source health
- Status: healthy
- Item download looks usable.
- Yavira can redirect you to the upstream package for this item.
- Health scope: item
- Reason: direct_download_ok
- Checked at: 2026-05-03T16:31:41.117Z
- Expires at: 2026-05-10T16:31:41.117Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/git-notes-memory)
- [Send to Agent page](https://openagent3.xyz/skills/git-notes-memory/agent)
- [JSON manifest](https://openagent3.xyz/skills/git-notes-memory/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/git-notes-memory/agent.md)
- [Download page](https://openagent3.xyz/downloads/git-notes-memory)