Session Management Deep Dive
Session Management & Compaction (Deep Dive)
Section titled “Session Management & Compaction (Deep Dive)”This document explains how OpenClaw manages sessions end-to-end:
- Session routing (how inbound messages map to a
sessionKey) - Session store (
sessions.json) and what it tracks - Transcript persistence (
*.jsonl) and its structure - Transcript hygiene (provider-specific fixups before runs)
- Context limits (context window vs tracked tokens)
- Compaction (manual + auto-compaction) and where to hook pre-compaction work
- Silent housekeeping (e.g. memory writes that shouldn’t produce user-visible output)
If you want a higher-level overview first, start with:
- /concepts/session
- /concepts/compaction
- /concepts/memory
- /concepts/memory-search
- /concepts/session-pruning
- /reference/transcript-hygiene
Source of truth: the Gateway
Section titled “Source of truth: the Gateway”OpenClaw is designed around a single Gateway process that owns session state.
- UIs (macOS app, web Control UI, TUI) should query the Gateway for session lists and token counts.
- In remote mode, session files are on the remote host; “checking your local Mac files” won’t reflect what the Gateway is using.
Two persistence layers
Section titled “Two persistence layers”OpenClaw persists sessions in two layers:
-
Session store (
sessions.json)- Key/value map:
sessionKey -> SessionEntry - Small, mutable, safe to edit (or delete entries)
- Tracks session metadata (current session id, last activity, toggles, token counters, etc.)
- Key/value map:
-
Transcript (
<sessionId>.jsonl)- Append-only transcript with tree structure (entries have
id+parentId) - Stores the actual conversation + tool calls + compaction summaries
- Used to rebuild the model context for future turns
- Append-only transcript with tree structure (entries have
On-disk locations
Section titled “On-disk locations”Per agent, on the Gateway host:
- Store:
~/.openclaw/agents/<agentId>/sessions/sessions.json - Transcripts:
~/.openclaw/agents/<agentId>/sessions/<sessionId>.jsonl- Telegram topic sessions:
.../<sessionId>-topic-<threadId>.jsonl
- Telegram topic sessions:
OpenClaw resolves these via src/config/sessions.ts.
Store maintenance and disk controls
Section titled “Store maintenance and disk controls”Session persistence has automatic maintenance controls (session.maintenance) for sessions.json and transcript artifacts:
mode:warn(default) orenforcepruneAfter: stale-entry age cutoff (default30d)maxEntries: cap entries insessions.json(default500)rotateBytes: rotatesessions.jsonwhen oversized (default10mb)resetArchiveRetention: retention for*.reset.<timestamp>transcript archives (default: same aspruneAfter;falsedisables cleanup)maxDiskBytes: optional sessions-directory budgethighWaterBytes: optional target after cleanup (default80%ofmaxDiskBytes)
Enforcement order for disk budget cleanup (mode: "enforce"):
- Remove oldest archived or orphan transcript artifacts first.
- If still above the target, evict oldest session entries and their transcript files.
- Keep going until usage is at or below
highWaterBytes.
In mode: "warn", OpenClaw reports potential evictions but does not mutate the store/files.
Run maintenance on demand:
openclaw sessions cleanup --dry-runopenclaw sessions cleanup --enforceCron sessions and run logs
Section titled “Cron sessions and run logs”Isolated cron runs also create session entries/transcripts, and they have dedicated retention controls:
cron.sessionRetention(default24h) prunes old isolated cron run sessions from the session store (falsedisables).cron.runLog.maxBytes+cron.runLog.keepLinesprune~/.openclaw/cron/runs/<jobId>.jsonlfiles (defaults:2_000_000bytes and2000lines).
Session keys (sessionKey)
Section titled “Session keys (sessionKey)”A sessionKey identifies which conversation bucket you’re in (routing + isolation).
Common patterns:
- Main/direct chat (per agent):
agent:<agentId>:<mainKey>(defaultmain) - Group:
agent:<agentId>:<channel>:group:<id> - Room/channel (Discord/Slack):
agent:<agentId>:<channel>:channel:<id>or...:room:<id> - Cron:
cron:<job.id> - Webhook:
hook:<uuid>(unless overridden)
The canonical rules are documented at /concepts/session.
Session ids (sessionId)
Section titled “Session ids (sessionId)”Each sessionKey points at a current sessionId (the transcript file that continues the conversation).
Rules of thumb:
- Reset (
/new,/reset) creates a newsessionIdfor thatsessionKey. - Daily reset (default 4:00 AM local time on the gateway host) creates a new
sessionIdon the next message after the reset boundary. - Idle expiry (
session.reset.idleMinutesor legacysession.idleMinutes) creates a newsessionIdwhen a message arrives after the idle window. When daily + idle are both configured, whichever expires first wins. - Thread parent fork guard (
session.parentForkMaxTokens, default100000) skips parent transcript forking when the parent session is already too large; the new thread starts fresh. Set0to disable.
Implementation detail: the decision happens in initSessionState() in src/auto-reply/reply/session.ts.
Session store schema (sessions.json)
Section titled “Session store schema (sessions.json)”The store’s value type is SessionEntry in src/config/sessions.ts.
Key fields (not exhaustive):
sessionId: current transcript id (filename is derived from this unlesssessionFileis set)updatedAt: last activity timestampsessionFile: optional explicit transcript path overridechatType:direct | group | room(helps UIs and send policy)provider,subject,room,space,displayName: metadata for group/channel labeling- Toggles:
thinkingLevel,verboseLevel,reasoningLevel,elevatedLevelsendPolicy(per-session override)
- Model selection:
providerOverride,modelOverride,authProfileOverride
- Token counters (best-effort / provider-dependent):
inputTokens,outputTokens,totalTokens,contextTokens
compactionCount: how often auto-compaction completed for this session keymemoryFlushAt: timestamp for the last pre-compaction memory flushmemoryFlushCompactionCount: compaction count when the last flush ran
The store is safe to edit, but the Gateway is the authority: it may rewrite or rehydrate entries as sessions run.
Transcript structure (*.jsonl)
Section titled “Transcript structure (*.jsonl)”Transcripts are managed by @mariozechner/pi-coding-agent’s SessionManager.
The file is JSONL:
- First line: session header (
type: "session", includesid,cwd,timestamp, optionalparentSession) - Then: session entries with
id+parentId(tree)
Notable entry types:
message: user/assistant/toolResult messagescustom_message: extension-injected messages that do enter model context (can be hidden from UI)custom: extension state that does not enter model contextcompaction: persisted compaction summary withfirstKeptEntryIdandtokensBeforebranch_summary: persisted summary when navigating a tree branch
OpenClaw intentionally does not “fix up” transcripts; the Gateway uses SessionManager to read/write them.
Context windows vs tracked tokens
Section titled “Context windows vs tracked tokens”Two different concepts matter:
- Model context window: hard cap per model (tokens visible to the model)
- Session store counters: rolling stats written into
sessions.json(used for /status and dashboards)
If you’re tuning limits:
- The context window comes from the model catalog (and can be overridden via config).
contextTokensin the store is a runtime estimate/reporting value; don’t treat it as a strict guarantee.
For more, see /token-use.
Compaction: what it is
Section titled “Compaction: what it is”Compaction summarizes older conversation into a persisted compaction entry in the transcript and keeps recent messages intact.
After compaction, future turns see:
- The compaction summary
- Messages after
firstKeptEntryId
Compaction is persistent (unlike session pruning). See /concepts/session-pruning.
When auto-compaction happens (Pi runtime)
Section titled “When auto-compaction happens (Pi runtime)”In the embedded Pi agent, auto-compaction triggers in two cases:
- Overflow recovery: the model returns a context overflow error → compact → retry.
- Threshold maintenance: after a successful turn, when:
contextTokens > contextWindow - reserveTokens
Where:
contextWindowis the model’s context windowreserveTokensis headroom reserved for prompts + the next model output
These are Pi runtime semantics (OpenClaw consumes the events, but Pi decides when to compact).
Compaction settings (reserveTokens, keepRecentTokens)
Section titled “Compaction settings (reserveTokens, keepRecentTokens)”Pi’s compaction settings live in Pi settings:
{ compaction: { enabled: true, reserveTokens: 16384, keepRecentTokens: 20000, },}OpenClaw also enforces a safety floor for embedded runs:
- If
compaction.reserveTokens < reserveTokensFloor, OpenClaw bumps it. - Default floor is
20000tokens. - Set
agents.defaults.compaction.reserveTokensFloor: 0to disable the floor. - If it’s already higher, OpenClaw leaves it alone.
Why: leave enough headroom for multi-turn “housekeeping” (like memory writes) before compaction becomes unavoidable.
Implementation: ensurePiCompactionReserveTokens() in src/agents/pi-settings.ts
(called from src/agents/pi-embedded-runner.ts).
User-visible surfaces
Section titled “User-visible surfaces”You can observe compaction and session state via:
/status(in any chat session)openclaw status(CLI)openclaw sessions/sessions --json- Verbose mode:
🧹 Auto-compaction complete+ compaction count
Silent housekeeping (NO_REPLY)
Section titled “Silent housekeeping (NO_REPLY)”OpenClaw supports “silent” turns for background tasks where the user should not see intermediate output.
Convention:
- The assistant starts its output with
NO_REPLYto indicate “do not deliver a reply to the user”. - OpenClaw strips/suppresses this in the delivery layer.
As of 2026.1.10, OpenClaw also suppresses draft/typing streaming when a partial chunk begins with NO_REPLY, so silent operations don’t leak partial output mid-turn.
Pre-compaction “memory flush” (implemented)
Section titled “Pre-compaction “memory flush” (implemented)”Goal: before auto-compaction happens, run a silent agentic turn that writes durable
state to disk (e.g. memory/YYYY-MM-DD.md in the agent workspace) so compaction can’t
erase critical context.
OpenClaw uses the pre-threshold flush approach:
- Monitor session context usage.
- When it crosses a “soft threshold” (below Pi’s compaction threshold), run a silent “write memory now” directive to the agent.
- Use
NO_REPLYso the user sees nothing.
Config (agents.defaults.compaction.memoryFlush):
enabled(default:true)softThresholdTokens(default:4000)prompt(user message for the flush turn)systemPrompt(extra system prompt appended for the flush turn)
Notes:
- The default prompt/system prompt include a
NO_REPLYhint to suppress delivery. - The flush runs once per compaction cycle (tracked in
sessions.json). - The flush runs only for embedded Pi sessions (CLI backends skip it).
- The flush is skipped when the session workspace is read-only (
workspaceAccess: "ro"or"none"). - See Memory for the workspace file layout and write patterns.
Pi also exposes a session_before_compact hook in the extension API, but OpenClaw’s
flush logic lives on the Gateway side today.
Troubleshooting checklist
Section titled “Troubleshooting checklist”- Session key wrong? Start with /concepts/session and confirm the
sessionKeyin/status. - Store vs transcript mismatch? Confirm the Gateway host and the store path from
openclaw status. - Compaction spam? Check:
- model context window (too small)
- compaction settings (
reserveTokenstoo high for the model window can cause earlier compaction) - tool-result bloat: enable/tune session pruning
- Silent turns leaking? Confirm the reply starts with
NO_REPLY(exact token) and you’re on a build that includes the streaming suppression fix.