type: custom

customType: model-snapshot

provider: zai

modelApi: openai-completions


type: message

role: user

type: text

text:
[cron:47554b42-6db0-424d-b74e-cd3f51d8a212 grant-heartbeat-30m-qwen] Run heartbeat check (read HEARTBEAT.md). If actionable tasks are found, execute them. If nothing to do, reply with NO_REPLY. Do NOT say HEARTBEAT_OK.
Current time: Saturday, March 7th, 2026 — 4:51 PM (UTC)

Return your summary as plain text; it will be delivered automatically. If the task explicitly calls for messaging a specific external recipient, note who/where it should go instead of sending it yourself.


role: assistant

type: thinking

thinking:
I need to read HEARTBEAT.md to check for actionable tasks. This is a cron-triggered heartbeat check.

The user is asking me to:
1. Read HEARTBEAT.md
2. Execute any actionable tasks found
3. If nothing to do, reply with NO_REPLY (NOT HEARTBEAT_OK)

Let me read the HEARTBEAT.md file first.

read

type: toolCall

api: openai-completions

stopReason: toolUse


role: toolResult

toolName: read

text:
# Weekly Memory Maintenance
Check claw-compactor benchmark: python3 /home/crogers2287/claw-compactor/scripts/mem_compress.py /home/crogers2287/.openclaw/agents/grant benchmark
If savings > 10% OR session transcripts > 100: run full compression
Review observations/ folder for outdated entries

## Email Check
Check `/opt/agentmail/queue/` for new `*_grant.json` files
If found, read the email and respond appropriately via email reply
After handling, move to `/opt/agentmail/processed/`

## Cleanup Threshold
Archive observations older than 90 days to /home/crogers2287/.openclaw/agents/grant/memory/observations/archive/


thinking:
I need to check these tasks:

1. **Weekly Memory Maintenance** - Check claw-compactor benchmark
2. **Email Check** - Check for new emails in `/opt/agentmail/queue/`
3. **Cleanup Threshold** - Archive old observations

Let me start by checking for emails first since that's the most time-sensitive, then check the compression benchmark, and finally check for old observations.

exec

command: ls -la /opt/agentmail/queue/*_grant.json 2>/dev/null | head -20

command: python3 /home/crogers2287/claw-compactor/scripts/mem_compress.py /home/crogers2287/.openclaw/agents/grant benchmark 2>&1 | tail -20

command: find /home/crogers2287/.openclaw/agents/grant/memory/observations -type f -name "*.md" -mtime +90 2>/dev/null | wc -l


toolName: exec

text: (no output)

status: completed


text:
Date: 2026-03-07
Engine: tiktoken
Files: 40

Step                   |   Before |    After |  Saved |      %
----------------------------------------------------------
Rule Engine            |   18,402 |   17,519 |    883 |   4.8%
Dictionary Compress    |   17,519 |   17,492 |     27 |   0.2%
RLE Patterns           |   17,492 |   17,454 |     38 |   0.2%
Tokenizer Optimize     |   17,454 |   17,360 |     94 |   0.5%
----------------------------------------------------------
TOTAL (memory)         |   18,402 |   17,360 |  1,042 |   5.7%

💰 Total savings: 1,042 tokens (5.7%)

Session Transcripts: 2330 files found

Recommendations:
  - Run 'compress' to apply rule engine savings
  - Run 'observe' to compress 2330 session transcript(s)


thinking:
Results:

1. **Email Check** - No emails found (no output = no files)

2. **Compression Benchmark** -
   - Memory savings: 5.7% (below the 10% threshold)
   - Session transcripts: 2330 files (this is > 100, so I should run transcript compression)
   - Recommendation says to run 'compress' and 'observe'

3. **Cleanup Threshold** - 0 observations older than 90 days (nothing to archive)

The heartbeat says: "If savings > 10% OR session transcripts > 100: run full compression"

Session transcripts = 2330 > 100, so I should run compression. I should run the observe command for session transcripts.

Let me run the compression for session transcripts.

command: python3 /home/crogers2287/claw-compactor/scripts/mem_compress.py /home/crogers2287/.openclaw/agents/grant observe 2>&1


text: Processed 3 new session(s), 698 total tracked.


thinking:
The observe command only processed 3 new sessions out of 2330 total files. That seems like it might have only processed recent ones. Let me check if there's a way to process all transcripts. Let me also run the compress command for the memory files since there was a 5.7% savings available.

Actually, looking at the output again - "Processed 3 new session(s), 698 total tracked" - it seems like it only processed 3 new ones and has 698 total tracked. The 2330 files found might be all historical session files, but only some are new/unprocessed.

Let me run the compress command for memory files as well to apply the 5.7% savings.

command: python3 /home/crogers2287/claw-compactor/scripts/mem_compress.py /home/crogers2287/.openclaw/agents/grant compress 2>&1 | tail -20


text:
/home/crogers2287/.openclaw/agents/grant/memory/observations/fe12b882-41f2-445f-a758-09bb04f687c3.md: 31 → 31 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/memory/observations/fe8cb831-8792-497f-8480-404d73f82acf.md: 31 → 31 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/memory/observations/fed77f13-8ac9-4383-a62d-06e75c02ed40.md: 347 → 347 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/memory/observations/ff05ac66-a52a-4c6f-a2af-2f33f5107b9c.md: 31 → 31 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/memory/observations/ff0a88f7-6dc7-4aa8-aa83-8e04f8386c39.md: 360 → 360 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/memory/observations/ff2b3166-05f8-4d3a-94be-3e2cde0bd52a.md: 31 → 31 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/memory/observations/ff2b78a3-d1a4-4aa0-9c27-b203a6569b4e.md: 179 → 179 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/memory/observations/ff95ff1a-4535-466b-a339-9522b5f4266c.md: 31 → 31 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/memory/reference/tools/media-server.md: 272 → 272 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/memory/reference/tools/ssh-hosts.md: 71 → 71 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/memory/reference/tools/vision-models.md: 129 → 129 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/observations/2026-02-28.md: 318 → 318 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/observations/2026-03-01.md: 140 → 140 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/observations/2026-03-06.md: 148 → 148 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/projects/workout-buddy/PROJECT.md: 1820 → 1820 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/projects/workout-buddy/README.md: 1321 → 1321 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/projects/workout-buddy/SETUP.md: 1566 → 1566 tokens (saved 0)
/home/crogers2287/.openclaw/agents/grant/quick_reference.md: 1301 → 1301 tokens (saved 0)

Total: 146586 → 144270 tokens (saved 2316)


thinking:
The compression ran successfully:
- Memory files compressed: 146,586 → 144,270 tokens (saved 2,316 tokens)
- Session transcripts: Processed 3 new sessions, 698 total tracked

The benchmark showed 5.7% savings potential but the actual compress saved more (2,316 tokens from 146,586 = ~1.6%). The difference is likely because the benchmark was showing potential savings from all steps, but the compress only applies the rule engine.

Now let me summarize what was done:
1. Email check: No new emails
2. Memory compression: Ran successfully, saved 2,316 tokens
3. Session transcript tracking: 3 new sessions processed
4. Old observations cleanup: 0 files to archive

Heartbeat complete. I should respond with a summary since tasks were executed.

text:
## Heartbeat Complete — Grant

**Email Check:** No new emails in queue.

**Memory Compression:**
- Benchmark: 5.7% savings potential, 2,330 session transcripts
- Ran `observe`: 3 new sessions processed (698 total tracked)
- Ran `compress`: 146,586 → 144,270 tokens (saved 2,316)

**Old Observations:** 0 files older than 90 days — nothing to archive.

**Status:** All maintenance tasks complete. No action items pending.

stopReason: stop