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Session Janitor

面向 OpenClaw 网关的会话维护工具:按轮次或定时修剪过长 transcript,将大型工具输出转存到缓存文件,通过网关聊天补全接口提取结构化记忆,归档孤立记录并清理过期会话;可选 watchdog 检测卡住会话并触发 Slack 告警。

halfdeadcat
halfdeadcat
热度 52.26
最近更新 2026-05-11 17:40:44
分类:自动化依赖:代码执行 / 读写文件 / 第三方 API / 内部调用大模型应用场景:自动化脚本 / 工作流 / 数据处理 / 摘要总结

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add session-janitor
Metadata
name
janitor
description
Automated transcript trimming, LLM memory extraction, and session hygiene for OpenClaw gateways. Keeps transcripts from bloating, extracts structured memories before archiving, and prunes stale sessions.
metadata
{"openclaw":{"requires":{"bins":["python3","jq"]}}}

Session Janitor

Automated transcript and session hygiene for OpenClaw gateways.

What It Does

  • Sidecar offloader — extracts large tool outputs (≥5KB) to .toolcache/ files, replacing inline content with lightweight stubs. Runs before trim on every turn.
  • Trims oversized transcripts — keeps recent exchanges + synthetic compaction summary, archives the rest
  • LLM memory extraction — uses the gateway's chat completions API to extract structured memories (facts, decisions, lessons) from trimmed content before discarding
  • Prunes stale sessions — removes old subagent/cron session entries from sessions.json
  • Archives orphan transcripts — files with no active session after a grace period
  • Cleans old archives — removes pre-trim, reset, and checkpoint files after retention period
  • Cleans orphaned checkpoints — removes *.checkpoint.*.jsonl files left behind by auto-compaction once the parent session no longer has an active transcript

Setup

bash skills/session-janitor/scripts/setup.sh

Setup auto-discovers all gateway installations (~/.openclaw/, ~/.openclaw-*/), generates config.json, installs a cron job, and installs the watcher service (systemd on Linux, launchd on macOS).

macOS Prerequisites

Install fswatch for the per-turn watcher:

brew install fswatch

The cron-based janitor works without it (trimming every 15 min instead of within ~3s of each turn).

For architecture details, trimming mechanics, and token math, see ARCHITECTURE.md.

Configuration

Edit config.json after setup to tune thresholds:

Key Default Description
trimMaxKB 250 Trim transcripts larger than this. Trim always fires when exceeded — there is no minimum pair count.
keepPairs 10 Number of recent user/assistant pairs to keep after trim. If fewer pairs exist than this, all are kept (no skip).
keepFullPairs 2 Most recent N assistant turns that keep full toolResult bodies (older turns are collapsed to summary lines)
minArchivePairs 5 Informational only — no longer blocks trim. Sessions exceeding trimMaxKB are always trimmed.
trimFullThresholdPct 50 Two-stage aggressive reduction when trimmed output still exceeds this % of trimMaxKB: (1) strip all assistant turns (tool args + thinking removed); (2) if still over threshold, drop all toolResult entries entirely. Set to 100 to disable.
archiveRetentionDays 7 Delete old archives after this many days (applies to .reset.*, .deleted.*, .pre-trim.*, .bak-*, .purged.*, .emergency-*)
keepPreTrimFiles 3 Max .pre-trim.* files to keep per session (oldest deleted immediately, regardless of retention period)
orphanGraceMinutes 30 Wait before archiving orphan transcripts
staleSubagentHours 24 Prune subagent session entries older than this
staleCronSessionHours 24 Prune cron session entries older than this
llmExtraction.enabled true Use LLM to extract memories from trimmed content
llmExtraction.model openclaw Model identifier to use for extraction calls
llmExtraction.maxInputChars 20000 Max characters of archived content sent to LLM
llmExtraction.timeoutSecs 60 LLM API call timeout in seconds
llmExtraction.maxMemories 15 Max memories to accept from a single LLM extraction
llmExtraction.minArchived 3 Minimum archived messages required before running LLM extraction
llmExtraction.maxPerRun 1 Max LLM extractions per cron cycle (cost control)
memCli.enabled false Store extracted memories via mem CLI (requires mem)
cronSchedule */15 * * * * How often to run
sidecar.enabled true Offload large toolResult entries to .toolcache/ files
sidecar.minEntryBytes 5120 Minimum toolResult content size (bytes) to trigger offload
extractOnTrim.enabled false Fire async LLM memory extraction after each watcher-triggered trim
extractOnTrim.minArchivedPairs 3 Minimum archived message pairs required before running extraction
extractOnTrim.scene auto Memory scene tag to use (auto lets the LLM infer from context)
extractOnTrim.salience 0.5 Default salience for extracted memories (0.1–1.0)
watchdog.enabled false Run hung-session detector after each janitor pass
watchdog.staleMinutes 5 Session updatedAt age threshold to consider stuck
watchdog.alertSlack true Send Slack DM when a stuck session is detected
watchdog.slackTarget — Slack user ID or channel to notify
watchdog.autoRestart false Auto-trigger safe-restart script on detection (use with caution)
watchdog.restartScriptSlack ~/bin/safe-slack-restart.sh Safe restart script path for Slack gateway
watchdog.restartScriptDiscord ~/bin/safe-gateway-restart.sh Safe restart script path for Discord gateway

Gateway Discovery

Setup scans for ~/.openclaw/openclaw.json and ~/.openclaw-*/openclaw.json. Each discovered gateway gets its own entry in config.json with:

  • Port (from gateway.port in config)
  • Auth token (from gateway.auth.token)
  • Sessions directory path

Works with single-gateway installs, multi-gateway (Discord + Slack), or any custom layout.

LLM Extraction Guardrails

  • Lockfile — only one extraction at a time across all gateways
  • Max per run — configurable cap per cron cycle (default: 1)
  • 20K char input cap — truncates middle of very long conversations
  • 60s hard timeout — SIGALRM kills hung API calls
  • Dedup — state file tracks processed trims, never re-runs
  • No context inflation — memories go to mem DB only, never to files that get auto-loaded into session context

Manual Run

bash skills/session-janitor/scripts/janitor.sh

Logs

tail -f /tmp/session-janitor.log

Watcher Service

The watcher fires trim within ~3 seconds of each turn completing (vs. waiting for the next cron cycle). setup.sh installs it automatically as a system service.

Linux (systemd):

systemctl --user status session-janitor-watcher
systemctl --user restart session-janitor-watcher
tail -f /tmp/session-janitor-watcher.log

macOS (launchd):

launchctl list | grep session-janitor
launchctl unload ~/Library/LaunchAgents/ai.openclaw.session-janitor-watcher.plist
launchctl load  ~/Library/LaunchAgents/ai.openclaw.session-janitor-watcher.plist
tail -f /tmp/session-janitor-watcher.log
  • Linux uses inotifywait (from inotify-tools) and watches via inotify kernel events.
  • macOS uses fswatch (via Homebrew) and watches via FSEvents.

Watchdog

The watchdog runs after every janitor pass and checks updatedAt on all active sessions. If any session is stale longer than watchdog.staleMinutes, it fires a Slack alert. Optional autoRestart will trigger the appropriate safe-restart script.

Alert cooldown is 10 minutes per session to prevent spam. State is tracked in the janitor state file.

# Run standalone
bash skills/session-janitor/scripts/watchdog.sh 5 ~/.openclaw/session-janitor-state.json

Sub-Agent Reporting Conventions

Workers spawned via Foreman should use prefixed sessions_send messages to prevent the parent agent from spawning new sub-agents in response to status updates:

# Intermediate status (fire-and-forget — parent relays but does NOT spawn)
sessions_send(sessionKey="{PARENT}", message="STATUS: 🤖 [label]: doing X (60%)", timeoutSeconds=0)

# Errors/failures (normal delivery — parent may intervene)
sessions_send(sessionKey="{PARENT}", message="ERROR: 🤖 [label]: what failed — details")

# Completion (no prefix, normal delivery)
sessions_send(sessionKey="{PARENT}", message="🤖 [label]: ✅ done — summary")
  • STATUS: → relay-only; timeoutSeconds=0 prevents reply-back loops
  • ERROR: → parent receives and considers recovery action
  • No prefix → completion; parent handles and relays to channel

Files

skills/session-janitor/
├── SKILL.md                              # This file
├── ARCHITECTURE.md                       # Deep dive: trimming mechanics, token math, examples
├── config.json                           # Generated by setup (gitignored)
├── config.example.json                   # Reference config
├── session-janitor-watcher.service       # Linux: systemd user service template
├── session-janitor-watcher.plist         # macOS: launchd LaunchAgent template
└── scripts/
    ├── setup.sh           # Discovery + config gen + cron + service install (Linux + macOS)
    ├── janitor.sh         # Main cron entry point
    ├── trim.py            # Transcript trimming (thinking, toolCall args, toolResult collapse)
    ├── sidecar.py         # Large toolResult offloader (→ .toolcache/ files)
    ├── watcher.sh         # Per-turn trigger (sidecar + trim; inotifywait/fswatch)
    ├── extract-llm.py     # LLM memory extraction
    ├── prune-sessions.py  # Stale session pruning
    ├── watchdog.sh        # Hung-session detector + Slack alert
    ├── test-sidecar.py    # Sidecar test suite (8 scenarios, 22 assertions)
    └── test-sidecar.sh    # Shell wrapper for sidecar tests