# 2026-02-24

## Day recap 2026-02-23
- What happened:
  - Investigated the daily backup setup and confirmed that `backup_memory.sh` is scheduled via the system crontab (`crontab -l`) to run every day at 00:00, logging to `logs/backup_memory.log`.
  - Reviewed the backup script at `scripts/backup_memory.sh`, which copies `openclaw.json` into `openclaw_backup.json`, exports cron jobs to `active_crons.json`, freezes Python dependencies to `requirements.txt`, then commits and pushes all workspace changes to the private GitHub repo `LLagoon3/openclaw-memory-backup` (branch `master`).
  - Manually ran the backup script from the workspace, which successfully committed and pushed changes (including creation of `memory/2026-02-23.md` and updates to `scripts/snp500_stooq.py`) as commit `bc7a355`.
  - Processed a cron-delivered reminder summarizing that the OpenClaw gateway restart (`openclaw doctor --non-interactive`) completed successfully and relayed the S&P 500 moving-average report for 2026-02-20 back to the main session.
  - Audited the server’s SSH tunneling setup: listed SSH-related systemd units, inspected `reverse-ssh-tunnel.service`, and confirmed it runs `/home/lagoon3/bin/reverse-ssh-tunnel.sh` as user `lagoon3`.
  - Reviewed `reverse-ssh-tunnel.sh`, which establishes a reverse SSH tunnel to `lee-lagoon-vps` with two mappings: VPS `127.0.0.1:18789 -> localhost:18789` (OpenClaw gateway) and VPS `0.0.0.0:10022 -> localhost:22` (SSH to lagoon3), using host config `lee-lagoon-vps` from `/home/lagoon3/.ssh/config`.
  - Verified on the VPS that ports `10022` (0.0.0.0) and `18789` (127.0.0.1) are listening, `sudo` is available non-interactively, and that local connectivity to `127.0.0.1:10022` works, while external connectivity tests from lagoon3 to `lee-lagoon.duckdns.org:10022`/`74.227.128.52:10022` time out.
- Decisions / stable facts:
  - The daily memory backup workflow is implemented via a system crontab entry that invokes `scripts/backup_memory.sh` nightly at 00:00 and pushes to `LLagoon3/openclaw-memory-backup` on `master`; this job is functioning correctly as of the manual test (commit `bc7a355`).
  - The SSH reverse-tunnel service `reverse-ssh-tunnel.service` is enabled and running; it successfully exposes lagoon3’s SSH on VPS port `10022` and the local OpenClaw gateway on VPS `127.0.0.1:18789`, with the SSH endpoint `lee-lagoon-vps` defined in `~/.ssh/config` (HostName `lee-lagoon.duckdns.org`, Port `20222`).
  - Repeated connection failures to `localhost:18789` in the tunnel logs correspond to moments when the local OpenClaw gateway is not accepting connections, and are expected around gateway restarts.
  - From lagoon3, inbound TCP connections to `lee-lagoon.duckdns.org:10022`/`74.227.128.52:10022` currently time out, while the VPS itself can connect locally, indicating that any remaining access issue is likely due to upstream/provider or network-level firewalling, not local ufw/iptables (ufw is inactive on the VPS).
- Next actions / blockers:
  - If external SSH access to lagoon3 via `lee-lagoon-vps:10022` is required, review and adjust the VPS provider/router firewall or security group to allow inbound TCP on port `10022` from the desired client networks.
  - Optionally harden and stabilize the reverse tunnel by adding keepalive and failure options (e.g., `ServerAliveInterval`, `ServerAliveCountMax`, `ExitOnForwardFailure=yes`) or migrating `reverse-ssh-tunnel.service` to use `autossh` for auto-reconnect behavior.
- Links/IDs:
  - Backup script: `scripts/backup_memory.sh`; backup cron: system `crontab -l` entry (`0 0 * * * /home/lagoon3/.openclaw/workspace/scripts/backup_memory.sh ...`).
  - Backup repo: `https://github.com/LLagoon3/openclaw-memory-backup` (branch `master`, latest backup commit on this day: `bc7a355`).
  - SSH tunnel unit: `/etc/systemd/system/reverse-ssh-tunnel.service`; tunnel script: `/home/lagoon3/bin/reverse-ssh-tunnel.sh`; SSH host config: `/home/lagoon3/.ssh/config` entry `Host lee-lagoon-vps`.
  - Daily memory auto-summary cron id (unchanged): `6ef3619b-e82b-4c0c-b39c-7973eaf01422`.

## Auto-summary 2026-02-24 10:00 KST
- What happened:
  - In the main session, the user asked to set the default model to `openai-codex/gpt-5.2`; the agent located the OpenClaw config file and used `openclaw config set` to update `agents.defaults.model.primary` to `openai-codex/gpt-5.2` and `agents.defaults.model.fallbacks[0]` to the same model.
  - The agent restarted the OpenClaw gateway (`openclaw gateway restart`), verified gateway status, and confirmed the updated model configuration via `openclaw config get agents.defaults.model --json`.
  - The user then requested a multi-step fallback chain; the agent updated `agents.defaults.model.fallbacks[0]` to `google-gemini-cli/gemini-3-flash-preview` and `fallbacks[1]` to `openai-codex/gpt-5.1`, followed by another `openclaw gateway restart` to apply these changes.
- Decisions / stable facts:
  - The primary model for `agents.defaults.model.primary` is now `openai-codex/gpt-5.2`.
  - The fallback chain for `agents.defaults.model.fallbacks` is now:
    1) `google-gemini-cli/gemini-3-flash-preview`
    2) `openai-codex/gpt-5.1`.
  - Gateway restarts were successfully executed after both the primary model change and the fallback chain update, so these settings should be active for new sessions.
- Next actions / blockers:
  - Monitor upcoming interactions to ensure routing and behavior match the new primary/fallback model configuration; adjust the fallback order if latency, cost, or quality tradeoffs are not satisfactory.
  - Optionally document the current model configuration and rationale in `MEMORY.md` or a dedicated tooling note if long-term tracking is desired.
- Links/IDs:
  - Config keys: `agents.defaults.model.primary`, `agents.defaults.model.fallbacks[0]`, `agents.defaults.model.fallbacks[1]`.
  - Daily memory auto-summary cron id: `6ef3619b-e82b-4c0c-b39c-7973eaf01422`.

## Auto-summary 2026-02-24 13:00 KST
- What happened:
  - The user asked the agent to verify the Notion API connection and token health. The agent followed the Notion skill workflow: checked for the presence of `~/.config/notion/api_key`, then used it to call `GET https://api.notion.com/v1/users/me` and `POST https://api.notion.com/v1/search` with the current API version, confirming HTTP 200 responses for both.
  - The agent inspected the `users/me` response (without leaking sensitive data) and confirmed that the integration (bot) identity is valid and associated with the workspace.
  - The user provided a specific Notion page URL; the agent extracted the page_id `82a858b6f8be4099957ce2cf869694e1` and called `GET https://api.notion.com/v1/pages/{page_id}` using the same token. The response returned HTTP 404 with `object_not_found`, indicating that the integration does not currently have access to that page/database.
  - The agent reported that the error message explicitly recommends sharing the relevant pages/databases with the integration and explained that the issue is page-level permissions, not a broken token or global API problem.
- Decisions / stable facts:
  - The Notion API key stored in `~/.config/notion/api_key` is valid and can successfully call both `users/me` and `search`, confirming that the integration is properly authenticated and has general workspace access.
  - The specific Notion page/database with id `82a858b6f8be4099957ce2cf869694e1` is **not shared** with the current integration, which causes `GET /v1/pages/{page_id}` to return `object_not_found` despite the token being healthy.
- Next actions / blockers:
  - To allow the agent to work with that page or its underlying database, the user needs to open the page in Notion and explicitly share/connect it to the `openclaw` integration (or the relevant Notion integration used here) via the Share menu.
  - After the page is shared with the integration, rerun the `GET /v1/pages/82a858b6f8be4099957ce2cf869694e1` check to confirm that the object is now accessible and to proceed with any database/page-specific automation.
- Links/IDs:
  - Notion token path (local): `~/.config/notion/api_key` (content not logged).
  - Tested Notion endpoints: `GET /v1/users/me`, `POST /v1/search`.
  - Problematic page id: `82a858b6f8be4099957ce2cf869694e1` (corresponding to the user-provided Notion URL).
  - Daily memory auto-summary cron id: `6ef3619b-e82b-4c0c-b39c-7973eaf01422`.

## Auto-summary 2026-02-24 16:00 KST
- What happened:
  - Between 13:00 and 16:00 KST there were no additional main-session conversations, file edits, or configuration changes visible beyond those already captured in the 13:00 auto-summary; this cron run executed successfully and confirmed that the prior Notion and model-configuration work remains the latest recorded activity.
- Decisions / stable facts:
  - As of 16:00 KST, the effective model configuration and Notion integration state are unchanged from the 13:00 summary (primary model `openai-codex/gpt-5.2`, fallbacks `[google-gemini-cli/gemini-3-flash-preview, openai-codex/gpt-5.1]`, Notion token healthy but the specific page `82a858b6f8be4099957ce2cf869694e1` still not shared with the integration).
- Next actions / blockers:
  - Continue with the next scheduled auto-summary runs; future entries should focus on any new changes to model configuration, Notion permissions, or other concrete workspace activity that occurs after this timestamp.
- Links/IDs:
  - Daily memory file for today: `memory/2026-02-24.md`.
  - Daily memory auto-summary cron id: `6ef3619b-e82b-4c0c-b39c-7973eaf01422`.

## Auto-summary 2026-02-24 20:00 KST
- What happened:
  - In the main session, the user and agent debugged and hardened the Discord → STT pipeline based on a 5-minute `.m4a` test file that previously appeared to hang when transcribing with `whisper-cli`.
  - The agent created and iteratively refined `/home/lagoon3/.local/bin/openclaw-stt-whisper-small.sh` so that it:
    - Always transcodes arbitrary input audio (ogg/opus, m4a/aac, etc.) to 16 kHz mono PCM WAV via `/home/lagoon3/.local/bin/ffmpeg`.
    - Uses `/home/lagoon3/.local/bin/ffprobe` to detect duration and applies dynamic per-chunk timeouts via `timeout`, killing the full process tree on overrun to prevent orphaned `whisper-cli` workers.
    - Optionally chunks long audio into fixed-length (~60s) WAV segments, transcribes each with `whisper-cli` small (Korean, no timestamps) and concatenates the text, improving UX for multi-minute recordings.
  - After a test run exposed a bug in the `calc_timeout` helper (undefined `dur` variable inside the embedded Python), the agent patched the function in-place using `edit`, then re-tested the script on the sample `.m4a` file and verified correct invocation and error handling.
  - To prevent concurrent STT runs from piling up on the Intel N100 CPU, the agent updated the OpenClaw config via `openclaw config set --strict-json` to force `tools.media.concurrency = 1` and `tools.media.audio.timeoutSeconds = 3600`, then restarted the OpenClaw gateway and confirmed the new values with `openclaw config get ... --json`.
  - The agent documented the finalized STT pipeline, binaries, model path, and key OpenClaw settings in `TOOLS.md` under a new “STT (Discord 음성메시지 → 텍스트)” section, so future sessions can rediscover the setup without re-inspecting config files.
  - The user and agent discussed when to use sub-agents for long audio: they agreed that STT itself will stay in the main tools pipeline, while sub-agents are reserved for heavy post-processing (summaries, TODO extraction, Notion writes, or web searches) once the full transcript is available.
- Decisions / stable facts:
  - STT for Discord voice and audio attachments is now standardized on:
    - Script: `/home/lagoon3/.local/bin/openclaw-stt-whisper-small.sh`.
    - Preprocessing: ffmpeg → 16 kHz mono PCM WAV, with optional fixed-window chunking for longer inputs.
    - Transcription engine: `whisper-cli` with model `~/.local/share/whisper.cpp/ggml-small.bin`, language default `ko`, no timestamps.
  - OpenClaw media settings on lagoon3 are explicitly set to `tools.media.concurrency = 1` and `tools.media.audio.timeoutSeconds = 3600`, which should eliminate STT hangs caused by accumulated orphan processes and too-short timeouts on multi-minute audio.
  - `TOOLS.md` now contains a canonical description of the STT pipeline and the relevant config keys, making this behavior discoverable and stable across new sessions.
  - For long recordings, the agent will first return the raw transcript (possibly in segments or as an attachment) and then wait for user instructions (summarize, log to Notion, run web searches, etc.), rather than baking in a fixed post-processing workflow.
- Next actions / blockers:
  - Optionally extend the STT pipeline to automatically chunk very long audio (>N minutes, threshold still to be chosen) and return the full transcript as a text attachment when chat output would be unwieldy.
  - Design a lightweight convention for when to spawn sub-agents for transcript-based post-processing (e.g., audio longer than 10–15 minutes triggers a background summarization/keyword extraction worker).
  - Monitor upcoming real-world Discord voice usages to confirm that the new `tools.media` settings and chunking behavior resolve prior “hang” symptoms and that wall-clock latency matches expectations for the Intel N100.
- Links/IDs:
  - STT script: `/home/lagoon3/.local/bin/openclaw-stt-whisper-small.sh`.
  - Binaries/model: `~/.local/bin/ffmpeg`, `~/.local/bin/ffprobe`, `~/.local/bin/whisper-cli`, model `~/.local/share/whisper.cpp/ggml-small.bin`.
  - OpenClaw config keys: `tools.media.concurrency`, `tools.media.audio.timeoutSeconds`, `tools.media.audio.models[0].type`, and its `command` (cli STT pipeline).
  - Documentation location: `/home/lagoon3/.openclaw/workspace/TOOLS.md` (STT section).
  - Daily memory auto-summary cron id: `6ef3619b-e82b-4c0c-b39c-7973eaf01422`.

## Day recap 2026-02-24
- What happened:
  - Adjusted the default OpenClaw model stack so that `openai-codex/gpt-5.2` is the primary model, with fallbacks to `google-gemini-cli/gemini-3-flash-preview` and `openai-codex/gpt-5.1`, and verified the new configuration via `openclaw config get` after gateway restarts.
  - Verified the Notion integration end-to-end with the stored API key, confirming that the token is healthy and the integration identity is valid, while identifying that a specific page (`82a858b6f8be4099957ce2cf869694e1`) remains inaccessible because it is not shared with the integration.
  - Designed, implemented, and iteratively hardened the Discord→STT pipeline using `ffmpeg`, `ffprobe`, and `whisper-cli` small, including duration-aware timeouts, optional chunking for longer audio, and a dedicated wrapper script `/home/lagoon3/.local/bin/openclaw-stt-whisper-small.sh`.
  - Updated `TOOLS.md` to document the finalized STT pipeline and the YouTube transcription workflow (link→subs-or-STT), and ensured the daily auto-summary cron can now read main-session history thanks to `tools.sessions.visibility=agent`.
- Decisions / stable facts:
  - The effective default model configuration for new sessions is now: primary `openai-codex/gpt-5.2`, fallbacks `[google-gemini-cli/gemini-3-flash-preview, openai-codex/gpt-5.1]`.
  - The Notion API key at `~/.config/notion/api_key` is confirmed working; access failures for specific pages are treated as page-sharing/permissions issues, not token problems.
  - Discord audio transcription is standardized on the local `openclaw-stt-whisper-small.sh` pipeline (16 kHz mono WAV via ffmpeg + whisper.cpp small, Korean-first), with OpenClaw media settings pinned to `tools.media.concurrency = 1` and `tools.media.audio.timeoutSeconds = 3600`.
  - YouTube link→text behavior is stable: prefer ko/en subtitles via `openclaw-youtube-transcribe.sh`, then fall back to STT when subs are missing, using a Python 3.11 venv-based yt-dlp (`~/.local/share/yt311/bin/yt-dlp`).
- Next actions / blockers:
  - For Notion, the user needs to explicitly share any pages/databases they want automated access to (e.g., `82a858b6f8be4099957ce2cf869694e1`) with the `openclaw` integration before deeper workflows are built.
  - For STT, consider adding automatic attachment handling for very long audio (e.g., returning transcripts as files) and defining clear thresholds for when to spawn sub-agents for heavy post-processing.
  - Optionally extend documentation in `MEMORY.md` or a dedicated “Audio/YouTube workflows” page to capture higher-level usage patterns beyond the current tooling notes.