據 AlphaMoat 統計,截至 2026-09,Vestige 累計下載 4,064 次、獲 3 個星標,在全部 5,078 個 AI 技能中排名第 2,498 位,在「知識管理」分類(442 個)中排名第 231 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 132 | 3883 | 3 | - |
| SkillHub ↗ | 246 | 4064 | 3 | — |
各平台的計數口徑不同,統計時間不一致。
使用間隔複習和關聯啟用管理跨會話記憶,支援持續回憶並在本地執行。記憶內容會隨時間變化;記錄個人資訊前應確認範圍,並允許使用者糾正或刪除不準確內容。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 4064 | — | 3 |
| 2026-08 | 3755 | +2.4% | 3 |
| 2026-07 | 3666 | — | 3 |
| 2026-05 | 3391 | — | 3 |
| 2026-03 | 2982 | — | 3 |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。
--- name: vestige description: Cognitive memory system using FSRS-6 spaced repetition. Memories fade naturally like human memory. Use for persistent recall across sessions. --- # Vestige Memory Skill Cognitive memory system based on 130 years of memory research. FSRS-6 spaced repetition, spreading activation, synaptic tagging—all running 100% local. ## Binary Location
```
~/bin/vestige-mcp
~/bin/vestige
~/bin/vestige-restore
```
## When to Use
- **Persistent memory** across sessions
- **User preferences** ("I prefer TypeScript", "I always use dark mode")
- **Bug fixes** and solutions worth remembering
- **Project patterns** and architectural decisions
- **Reminders** and future triggers
## Quick Commands
### Search Memory
```bash
echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search","arguments":{"query":"user preferences"}}}' | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text // .error.message'
```
### Save Memory (Smart Ingest)
```bash
echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"smart_ingest","arguments":{"content":"User prefers Swiss Modern design style for presentations","tags":["preference","design"]}}}' | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text // .error.message'
```
### Simple Ingest
```bash
echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"ingest","arguments":{"content":"TKPay Offline project: POC 2 months, MVP 2 months, budget 250K DH","tags":["project","tkpay"]}}}' | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text // .error.message'
```
### Check Stats
```bash
~/bin/vestige stats
```
### Health Check
```bash
~/bin/vestige health
```
## MCP Tools Available
| Tool | Description |
|------|-------------|
| `search` | Unified search (keyword + semantic + hybrid) |
| `smart_ingest` | Intelligent ingestion with duplicate detection |
| `ingest` | Simple memory storage |
| `memory` | Get, delete, or check memory state |
| `codebase` | Remember patterns and architectural decisions |
| `intention` | Set reminders and future triggers |
| `promote_memory` | Mark memory as helpful (strengthens) |
| `demote_memory` | Mark memory as wrong (weakens) |
## Trigger Words
| User Says | Action |
|-----------|--------|
| "Remember this" | `smart_ingest` immediately |
| "Don't forget" | `smart_ingest` with high priority |
| "I always..." / "I never..." | Save as preference |
| "I prefer..." / "I like..." | Save as preference |
| "This is important" | `smart_ingest` + `promote_memory` |
| "Remind me..." | Create `intention` |
## Session Start Routine
At the start of conversations, search for relevant context:
```bash
# Search user preferences
echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search","arguments":{"query":"user preferences instructions"}}}' | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text'
# Search project context
echo '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search","arguments":{"query":"current project context"}}}' | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text'
```
## Helper Script
For easier usage, create `~/bin/vmem`:
```bash
#!/bin/bash
# Vestige Memory Helper
ACTION=$1
shift
case $ACTION in
search)
echo "{\"jsonrpc\":\"2.0\",\"id\":1,\"method\":\"tools/call\",\"params\":{\"name\":\"search\",\"arguments\":{\"query\":\"$*\"}}}" | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text // .error.message'
;;
save)
echo "{\"jsonrpc\":\"2.0\",\"id\":1,\"method\":\"tools/call\",\"params\":{\"name\":\"smart_ingest\",\"arguments\":{\"content\":\"$*\"}}}" | ~/bin/vestige-mcp 2>/dev/null | jq -r '.result.content[0].text // .error.message'
;;
stats)
~/bin/vestige stats
;;
*)
echo "Usage: vmem [search|save|stats] [content]"
;;
esac
```
## Data Location
- **macOS**: `~/Library/Application Support/com.vestige.core/`
- **Linux**: `~/.local/share/vestige/`
- **Embedding cache**: `~/Library/Caches/com.vestige.core/fastembed/`
## Integration Notes
Vestige complements the existing `memory/` folder system:
- **memory/*.md** = Human-readable daily logs
- **MEMORY.md** = Curated long-term notes
- **Vestige** = Semantic search + automatic decay + spaced repetition
Use Vestige for:
- Things you want to recall semantically (not just keyword search)
- Preferences that should persist indefinitely
- Solutions worth remembering (with automatic decay if unused)
把長文字、文件與網頁內容壓縮成要點和關鍵詞的摘要工具。
透過 IMA OpenAPI 管理筆記與知識庫內容。
規定如何為網頁請求選擇合適工具的必讀指引。
呼叫百度 AI 搜尋介面做網頁檢索的技能。
用 uvx 直接呼叫 markitdown,把各類檔案轉成 Markdown。
面向 OpenClaw 的預設網頁搜尋,即時檢索多個引擎。
用 DuckDuckGo 介面做網頁、新聞、圖片與影片檢索的技能。
檢索並發現可用 OpenClaw 技能的技能。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。