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whatsapp-memoryWhatsApp 记忆

Agent Skill

whatsapp-memory 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:whatsapp-memory(WhatsApp 记忆)
来源仓库:https://github.com/netanel-abergel/whatsapp-memory
安装命令:
openclaw skills install whatsapp-memory
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install whatsapp-memory

简介

用于查找、检索和筛选相关信息,维护对话上下文记忆。

  • 适用于跟踪特定人员讨论内容和群组私信 (DM) 场景。
  • 为每个 WhatsApp 对话维护独立的内存上下文。
  • 安装前需确认数据存储权限和隐私合规性。whatsapp-memory 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 建议核实原始文档中的上下文清理机制和容量限制。

SKILL.md

name
whatsapp-memory
description
Maintain separate memory contexts per WhatsApp conversation — both groups and direct messages (DMs). Use when: tracking what was discussed with a specific person or in a specific group, recalling past context before responding, logging decisions or key facts from a conversation, or preventing context bleed between different chats.

WhatsApp Memory Skill

Minimum Model

Any model. Memory management is file-based. No reasoning required. Use a medium+ model only when deciding *what* is worth logging.


Why This Matters

Without conversation memory, context from one chat bleeds into another and you can't recall past decisions per group or person. This skill gives every group and DM its own context file.


Directory Structure

memory/
  whatsapp/
    groups/
      120363408613668489-g-us/    ← sanitized JID
        meta.json                 ← group name, JID, participants
        context.md                ← running conversation context
        decisions.md              ← key decisions
        people.md                 ← who participates and their role
    dms/
      972XXXXXXXXX/               ← sanitized phone number
        meta.json                 ← name, phone, relationship
        context.md                ← running DM context
        notes.md                  ← tasks, preferences, important facts

Setup

init_whatsapp_memory() {
  TYPE="$1"       # "group" or "dm"
  ID="$2"         # JID or phone number
  NAME="$3"       # Human-readable name

  # Sanitize the ID for use as a directory name
  SAFE_ID=$(echo "$ID" | tr '@.+' '---')

  if [ "$TYPE" = "group" ]; then
    DIR="$HOME/.openclaw/workspace/memory/whatsapp/groups/$SAFE_ID"
    mkdir -p "$DIR"
    # Write metadata file
    cat > "$DIR/meta.json" << EOF
{"type": "group", "jid": "$ID", "name": "$NAME", "created": "$(date -u +%Y-%m-%dT%H:%M:%SZ)"}
EOF
    # Create empty log files
    touch "$DIR/context.md" "$DIR/decisions.md" "$DIR/people.md"
  else
    DIR="$HOME/.openclaw/workspace/memory/whatsapp/dms/$SAFE_ID"
    mkdir -p "$DIR"
    # Write metadata file
    cat > "$DIR/meta.json" << EOF
{"type": "dm", "phone": "$ID", "name": "$NAME", "created": "$(date -u +%Y-%m-%dT%H:%M:%SZ)"}
EOF
    # Create empty log files
    touch "$DIR/context.md" "$DIR/notes.md"
  fi

  echo "Initialized WhatsApp memory: $NAME"
}

# Examples:
# init_whatsapp_memory "group" "120363422865795623@g.us" "PA Team"
# init_whatsapp_memory "dm" "+PHONE_NUMBER" "Contact Name"

Writing Memory

wa_log() {
  TYPE="$1"                        # "group" or "dm"
  ID="$2"                          # JID or phone
  CONTENT="$3"                     # what to log
  FILE_NAME="${4:-context.md}"     # context.md / decisions.md / notes.md

  # Sanitize ID
  SAFE_ID=$(echo "$ID" | tr '@.+' '---')
  BASE="$HOME/.openclaw/workspace/memory/whatsapp"

  # Pick the right directory
  if [ "$TYPE" = "group" ]; then
    FILE="$BASE/groups/$SAFE_ID/$FILE_NAME"
  else
    FILE="$BASE/dms/$SAFE_ID/$FILE_NAME"
  fi

  # Create file if missing
  if [ ! -f "$FILE" ]; then
    mkdir -p "$(dirname "$FILE")"
    touch "$FILE"
  fi

  # Append timestamped entry
  echo "[$(date -u +%Y-%m-%d\ %H:%M)] $CONTENT" >> "$FILE"
}

# Usage:
# wa_log "group" "XXXXXXXXXXX@g.us" "PA name: calendar connected ✅"
# wa_log "dm" "+PHONE_NUMBER" "Agreed to reschedule to Thursday" "notes.md"

Reading Memory

Get context for a conversation

wa_context() {
  TYPE="$1"
  ID="$2"
  LINES="${3:-20}"

  # Sanitize ID
  SAFE_ID=$(echo "$ID" | tr '@.+' '---')
  BASE="$HOME/.openclaw/workspace/memory/whatsapp"

  # Pick directory
  if [ "$TYPE" = "group" ]; then
    DIR="$BASE/groups/$SAFE_ID"
  else
    DIR="$BASE/dms/$SAFE_ID"
  fi

  # Check if memory exists
  if [ ! -d "$DIR" ]; then
    echo "No memory for this conversation yet."
    return
  fi

  # Read the conversation name from meta.json
  NAME=$(python3 -c "
import json
with open('$DIR/meta.json') as f:
    print(json.load(f).get('name', '?'))
" 2>/dev/null || echo "?")

  echo "=== $NAME ==="
  echo "--- Recent ---"
  tail -"$LINES" "$DIR/context.md" 2>/dev/null || echo "(empty)"
  echo "--- Notes/Decisions ---"
  cat "$DIR/notes.md" "$DIR/decisions.md" 2>/dev/null | tail -10 || echo "(none)"
}

Search across all WhatsApp memory

wa_search() {
  QUERY="$1"
  BASE="$HOME/.openclaw/workspace/memory/whatsapp"

  echo "Searching WhatsApp memory for: '$QUERY'"

  # Find all markdown files containing the query
  grep -r "$QUERY" "$BASE" --include="*.md" -l 2>/dev/null | while read file; do
    DIR=$(dirname "$file")

    # Get conversation name from meta.json
    NAME=$(python3 -c "
import json
with open('$DIR/meta.json') as f:
    print(json.load(f).get('name', '?'))
" 2>/dev/null || echo "?")

    echo "Found in: $NAME"
    # Show matching lines with line numbers
    grep -n "$QUERY" "$file" | head -3
    echo ""
  done
}

What to Log

Decision rules — log if ANY of these apply:

  • A decision was made → decisions.md
  • A task was assigned to someone → context.md
  • A new person was introduced → people.md
  • Owner gave you a task or preference → notes.md
  • A problem or resolution was reported → context.md

Never log:

  • Casual greetings or reactions
  • Duplicate information already recorded
  • Secrets or credentials

Quick reference by file:

FileUse for
context.mdOngoing conversation events
decisions.mdAgreed outcomes, group decisions
people.mdWho's in the group, their role/style
notes.mdDM tasks, owner preferences, follow-ups

Before Responding — Inject Context

On every incoming message:

1. Extract JID or phone from inbound metadata
2. If group: run wa_context "group" "$JID" 10
   If DM:    run wa_context "dm" "$PHONE" 10
3. Use context to inform your response
4. After responding: log anything worth remembering

Loop Prevention Rules (CRITICAL)

These rules prevent message loops and duplicate sends — learned from multi-PA group scenarios.

1. Echo Prevention

Before responding to ANY message, check sender_id from inbound metadata.

  • If sender is your own agent/number → NO_REPLY immediately. Do not process.
  • This prevents echo loops where your outbound message comes back as inbound.

2. No Duplicate Sends

Before sending any message to a group or DM:

  • Check if an identical or near-identical message was already sent in this session
  • If yes → skip. Do not send again.

3. Multi-PA Coordination

When multiple PA agents are active in the same group:

  • Only ONE PA should respond to each message
  • Default rule: the PA whose owner is most relevant to the topic responds
  • If another PA already responded → stay silent (NO_REPLY)
  • Do not echo or acknowledge the other PA's response unless asked

4. No Silent Proxying

If another PA cannot send a message (pairing issues, gateway errors):

  • Do NOT send the message on their behalf silently
  • Either explicitly state you're sending on their behalf, or let them handle it
  • Never impersonate another PA without disclosure

5. Patience

Before explaining, stepping in, or answering on behalf of another PA:

  • Wait. If the other PA hasn't responded yet, that doesn't mean she won't.
  • Give her a moment before intervening.
  • Intervene only if it's clearly blocking progress or she explicitly asks.

Weekly Digest

wa_weekly_digest() {
  BASE="$HOME/.openclaw/workspace/memory/whatsapp"

  # Get date from 7 days ago (works on Linux and macOS)
  WEEK_AGO=$(date -u -d '7 days ago' +%Y-%m-%d 2>/dev/null \
    || date -u -v-7d +%Y-%m-%d)

  echo "# WhatsApp Memory Digest — Week of $WEEK_AGO"

  # Loop over all group and DM directories
  for dir in "$BASE"/groups/*/ "$BASE"/dms/*/; do
    [ -d "$dir" ] || continue

    # Get the name
    NAME=$(python3 -c "
import json
with open('${dir}meta.json') as f:
    print(json.load(f).get('name', '?'))
" 2>/dev/null || echo "?")

    # Show recent entries from this week
    RECENT=$(grep "$WEEK_AGO\|$(date -u +%Y-%m-%d)" \
      "${dir}context.md" "${dir}notes.md" 2>/dev/null | tail -5)

    if [ -n "$RECENT" ]; then
      echo "### $NAME"
      echo "$RECENT"
      echo ""
    fi
  done
}

Integration

  • Before each response → load context for that conversation
  • After important exchanges → log to context.md or notes.md
  • With git-backup → push after every memory update
  • With owner-briefing → include DM follow-ups in morning briefing

Cost Tips

  • Very cheap: All memory operations are file reads/writes — no LLM tokens used
  • Small model OK: Reading, writing, and searching memory requires no reasoning
  • Use medium+ model only for: deciding *what* is worth logging vs. skipping
  • Batch: Log multiple events in one session before pushing backup, not one write per message
  • Avoid: Don't re-read full context files on every message — use tail -10 to limit tokens

适合场景

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02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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能力概览

能力 1

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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