unanswered-messages
# Unanswered Messages (File-Based)
Tracks messages sent to Heleni that haven't been replied to yet.
**No DB required** — uses `/opt/ocana/openclaw/workspace/inbox/pending.json`.
---
## File Structure
`/opt/ocana/openclaw/workspace/inbox/pending.json`:
```json
{
"version": 1,
"messages": [
{
"id": "MSG_ID",
"ts": "2026-04-01T14:30:00Z",
"chat_id": "+972XXXXXXXXX",
"chat_name": "Netanel",
"chat_type": "direct",
"sender_name": "Netanel",
"sender_phone": "+972XXXXXXXXX",
"body": "message text...",
"answered": false,
"answered_at": null
}
]
}
```
---
## 1. Log an Incoming Message
When a message arrives that needs a response, add it to the file:
```python
import json, datetime
INBOX = "/opt/ocana/openclaw/workspace/inbox/pending.json"
with open(INBOX) as f:
data = json.load(f)
data["messages"].append({
"id": "<message_id>",
"ts": datetime.datetime.utcnow().isoformat() + "Z",
"chat_id": "<chat_id>",
"chat_name": "<chat_name>",
"chat_type": "direct", # or "group"
"sender_name": "<sender_name>",
"sender_phone": "<sender_phone>",
"body": "<message body, max 300 chars>",
"answered": False,
"answered_at": None
})
with open(INBOX, "w") as f:
json.dump(data, f, indent=2)
```
---
## 2. Mark a Message as Answered
After replying, mark it done:
```python
import json, datetime
INBOX = "/opt/ocana/openclaw/workspace/inbox/pending.json"
with open(INBOX) as f:
data = json.load(f)
for msg in data["messages"]:
if msg["id"] == "<message_id>":
msg["answered"] = True
msg["answered_at"] = datetime.datetime.utcnow().isoformat() + "Z"
with open(INBOX, "w") as f:
json.dump(data, f, indent=2)
```
---
## 3. Find Unanswered Messages
```python
import json
from datetime import datetime, timedelta, timezone
INBOX = "/opt/ocana/openclaw/workspace/inbox/pending.json"
MAX_AGE_HOURS = 24 # ignore very old messages
with open(INBOX) as f:
data = json.load(f)
cutoff = datetime.now(timezone.utc) - timedelta(hours=MAX_AGE_HOURS)
unanswered = [
m for m in data["messages"]
if not m["answered"]
and datetime.fromisoformat(m["ts"].replace("Z", "+00:00")) > cutoff
]
for m in sorted(unanswered, key=lambda x: x["ts"]):
ts = datetime.fromisoformat(m["ts"].replace("Z", "+00:00")).strftime("%d/%m %H:%M")
print(f"📩 {m['sender_name']} | {m['chat_name']} | {ts}")
print(f" > {m['body'][:100]}")
print(f" Message ID: {m['id']}")
```
---
## 4. Cleanup — Remove Old Answered Messages
Run periodically (e.g. weekly via heartbeat) to keep the file small:
```python
import json
from datetime import datetime, timedelta, timezone
INBOX = "/opt/ocana/openclaw/workspace/inbox/pending.json"
with open(INBOX) as f:
data = json.load(f)
cutoff = datetime.now(timezone.utc) - timedelta(days=7)
data["messages"] = [
m for m in data["messages"]
if not m["answered"]
or datetime.fromisoformat(m["ts"].replace("Z", "+00:00")) > cutoff
]
with open(INBOX, "w") as f:
json.dump(data, f, indent=2)
print(f"Kept {len(data['messages'])} messages")
```
---
## Heartbeat Integration
During heartbeat, check for unanswered messages from the last 2 hours:
```python
import json
from datetime import datetime, timedelta, timezone
INBOX = "/opt/ocana/openclaw/workspace/inbox/pending.json"
with open(INBOX) as f:
data = json.load(f)
cutoff = datetime.now(timezone.utc) - timedelta(hours=2)
unanswered = [
m for m in data["messages"]
if not m["answered"]
and datetime.fromisoformat(m["ts"].replace("Z", "+00:00")) > cutoff
]
if unanswered:
# Alert Netanel or handle inline
for m in unanswered:
print(f"⚠️ לא ענינו ל-{m['sender_name']}: {m['body'][:80]}")
```
Add this check to `HEARTBEAT.md` under "Heartbeat Checks".
---
## Output Format
Report unanswered messages as:
- 📩 **[sender_name]** | [chat_name] | [DD/MM HH:MM]
> [body preview, max 100 chars]
> Message ID: [message_id]
Group by chat if multiple from same conversation.
---
## Notes
- ❌ No DB, no tunnel, no psql — pure file I/O
- ✅ Works offline, works on AWS without Mac tunnel
- Inbox file: `/opt/ocana/openclaw/workspace/inbox/pending.json`
- Currently: messages are logged manually when Heleni decides to track them
- Future: hook into inbound message handler to auto-log
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skill
ai
