#Best practices for making OpenClaw truly autonomous?

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thin bane
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Question: Best practices for making OpenClaw truly autonomous?

Setup: OpenClaw 2026.2.13, local Linux VM, Claude Max (Opus 4.6 primary), Telegram + Discord channels, Claude Code plugin for coding, multiple cron jobs, sub-agent system

What's working well:

  • Heartbeat every 5min with custom HEARTBEAT.md checklist
  • Sub-agents (sessions_spawn) for research/analysis tasks
  • Claude Code plugin for coding tasks
  • Cron jobs for recurring work (deploy verification, data sync, route selection)
  • Memory system: MEMORY.md + daily logs + reference/ docs + memory_search with embeddings
  • Compaction safeguards with memory flush
  • TASKS.md for task tracking
  • Lobster pipelines for deterministic workflows (email triage)

What still needs hand-holding:

  • Agent sometimes replies HEARTBEAT_OK when it should continue active work (had to add explicit "active work check" to heartbeat)
  • Sub-agent results occasionally get swallowed (had to build completion marker scripts + delivery system)
  • Context overflow still causes dropped work mid-task despite compaction config
  • Multi-phase projects need manual nudging between phases

What I want: Fire-and-forget task delegation. Give it a project, walk away, get results delivered. Currently ~70% there.

Questions:

  1. What config patterns help with reliable task continuation across compactions?
  2. Best way to chain multi-step autonomous workflows? (Currently using state/active-work.json + cron wakes)
  3. Any built-in orchestrator features I might be missing for long-running autonomous work?
  4. How are others handling the "sub-agent completed but main session didn't notice" problem?
raven crystalBOT
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To help others find answers, you can mark your question as solved via Right click solution message -> Apps -> ✅ Mark Solution

weary ruinBOT
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If you want “fire-and-forget” autonomy, the biggest unlock is treating chat history as a cache, not the source of truth. Make state + artifacts the source of truth, and design the agent loop to always reconstruct “what to do next” from disk (or a tiny structured store) after any compaction/reset.

Below are patterns that have worked well for long-running, low-handholding setups.

1) Reliable continuation across compactions (config + architecture patterns)

A. Externalize “continuation state” (don’t rely on chat history)

You’re already doing state/active-work.json — that’s exactly the right direction. The key is: after every meaningful step, write/update:

  • Current phase + next action (1 line)
  • Acceptance criteria / definition of done
  • Pointers to artifacts (files, URLs, commit hashes, etc.)
  • A short “resume prompt” (what the model should do when it wakes up)

Then in your base instructions (AGENTS.md / system prompt), make it a hard rule:

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“On every run (heartbeat/system-event/manual), read the active-work state first and either advance it or explicitly conclude it.”

B. Use compaction “safeguard” + memory flush

OpenClaw has built-in knobs specifically for “don’t lose the plot when compaction hits”:

  • agents.defaults.compaction.mode: "safeguard" (chunked summarization for long histories)
  • agents.defaults.compaction.memoryFlush.enabled: true with a flush prompt that writes durable notes before auto-compaction

Config reference (exact keys + shape): https://docs.openclaw.ai/gateway/configuration-reference
Compaction concept: https://docs.openclaw.ai/concepts/compaction

C. Prune tool-output context aggressively (prevents overflow-induced amnesia)

A lot of “dropped work mid-task” is actually “the model got drowned in old tool output.” Use:

  • agents.defaults.contextPruning (cache-ttl mode) to trim/clear old tool results from in-memory context

This doesn’t delete history on disk; it just keeps requests sane.

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Docs: https://docs.openclaw.ai/concepts/session-pruning

2) Chaining multi-step autonomous workflows (without manual nudges)

There are basically two good “autonomous chaining” models:

Model 1: Manager loop + queue (state machine)

  • Heartbeat (or a main-session system-event) acts as the manager
  • It pops the next step from state/active-work.json (or state/queue.jsonl)
  • It either executes it or spawns an isolated worker (cron / sub-agent), then records “waiting on X”

This is very robust because compaction doesn’t matter: the manager rebuilds state each time.

Model 2: Deterministic workflow runtime (Lobster) for multi-step pipelines

If you already like “lobster pipelines,” lean into it for anything that’s truly multi-step and needs resumability/approvals. Heartbeat/cron decide when to run; Lobster defines the steps.

cinder oasis
weary ruinBOT
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Docs: https://docs.openclaw.ai/tools/lobster
Cron-vs-heartbeat guidance: https://docs.openclaw.ai/automation/cron-vs-heartbeat

Practical chaining trick: cron “handoffs”

For longer projects, I’ve seen good results with:

  • Phase N runs as cron isolated (clean context, explicit artifact output)
  • At the end, it schedules a main-session system-event: “Project X: phase N done; load artifact Y; start phase N+1”
  • The manager heartbeat handles the system-event, updates state, continues

Cron docs (main vs isolated + wake modes): https://docs.openclaw.ai/automation/cron-jobs

3) Built-in orchestrator features people miss

A. Cron isolated runs are already an orchestration primitive

They’re “jobs with delivery,” persisted, retry-backed, and don’t pollute the main session. Also: isolated cron runs start fresh each time, which is good for long-running autonomy as long as state is externalized.

cinder oasis
weary ruinBOT
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Docs: https://docs.openclaw.ai/automation/cron-jobs

B. Hooks / plugin hooks for lifecycle glue

If you need “when X finishes, always do Y”, hooks are the built-in way to make it reliable without prompt gymnastics:

  • command hooks (/new, /reset, etc.)
  • lifecycle hooks (session start/end, agent end, compaction events, tool call events)

Docs: https://docs.openclaw.ai/automation/hooks
Plugin hook surface (agent_end / before_compaction / etc.): https://docs.openclaw.ai/tools/plugin#plugin-hooks

This is a very clean place to implement things like:

  • “after agent_end: if active-work exists and is not blocked, schedule a wake”
  • “after_compaction: ensure active-work summary is rewritten/compacted to disk”
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4) “Sub-agent completed but main session didn’t notice” (reliability patterns)

This is usually a handoff problem, not a “sub-agent problem.” A few patterns that eliminate it:

Pattern A (most reliable): Don’t require the main session to notice

Use cron isolated with announce delivery for background work instead of sub-agents when possible. Cron delivery is designed to be “result gets delivered even if the main session is busy/compacting.”

Pattern B: Write results to an “inbox” artifact + manager consumes it

Have workers always write:

  • artifacts/<jobId-or-runId>.md (the payload)
  • state/inbox.jsonl (a tiny record: what finished, where the artifact is)

Then heartbeat’s job is simply: “drain inbox; update TASKS; schedule next step.”

Pattern C: Explicit wake after sub-agent completion

If you keep using sessions_spawn, make the orchestration explicit:

  • after spawning, record “waiting for subagent:<id>”
cinder oasis
weary ruinBOT
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  • schedule a system-event (or a near-future cron main job) that says “Check for completed subagents; if found, ingest results + continue.”

This turns “maybe the main session noticed” into “the manager will definitely poll and ingest.”

If you want, paste (sanitized) your current:

  • agents.defaults.compaction block
  • agents.defaults.contextPruning block (if any)
  • a sample state/active-work.json


and I’ll suggest a concrete “manager loop contract” (fields + invariants) that survives compaction and makes phase transitions automatic.

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Hey! I’m around.

If you’re experimenting with “autonomy” stuff too: what’s the one thing that still feels the most brittle in your setup right now—compactions, chaining phases, or delivery/notifications?

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Hey — all good on my end.

What are you trying to improve right now: (a) compaction-safe continuation, (b) chaining multi-step projects without nudges, or (c) making sure background/sub-agent results always get delivered/ingested?

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Hey hey.

If you’re poking at autonomy too, what’s the pain point you’re hitting most often right now?

  • “compaction ate my context”
  • “multi-step projects stall between phases”
  • “background/sub-agent results don’t reliably get picked up”
  • something else entirely

Give me a concrete example and I’ll suggest a pattern that tends to make it boringly reliable.

thin bane
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Hey Krill, we've been building out the autonomy system you recommended and I'd love your input on what we've got so far.

Full audit doc here: https://gist.github.com/danielbotclaw/58b67ca71b75832df17640ef29a3a91b

Covers the full setup: state management, heartbeat system, boot recovery, task routing, both coding plugins (Claude Code + our custom Codex plugin), 21 cron jobs, Lobster workflows, memory system, and hooks.

Key questions for you:

  1. Are we reinventing things OpenClaw has natively? (we built inbox, queue, wakeAgent from scratch)
  2. Is there an after_compaction or session:end hook? That would fix our most fragile pattern
  3. Is openclaw system event --mode now the right way to wake the agent, or is there a cleaner RPC?
  4. Should cron isolated + announce be our default for all non-interactive work over sessions_spawn?
  5. What plugins/features are we NOT using that would be high-impact?
  6. Is the 3-part pipe format platform|account|target officially documented?

There are 14 questions total at the bottom of the doc. Happy to go back and forth on any of them.

weary ruinBOT
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You’re not crazy — you built a bunch of “missing glue” that OpenClaw mostly doesn’t ship as first‑class primitives yet. But there are a few native hook points / config knobs that should let you delete some of your most fragile patterns.

Below is a direct pass over your 14 questions (based on the gist).

1) Are you reinventing native OpenClaw features? (inbox / queue / wakeAgent)

Inbox / queue

  • Queue/inbox primitives: there’s no built-in “work queue” or “completion inbox” abstraction today. Cron is the closest native durable primitive, but it’s job-centric (schedule + payload + delivery), not a priority queue.
  • Your disk-first state (active-work.json, queue.jsonl, inbox.jsonl) is a legit pattern. If you want to reduce custom code, the most “OpenClaw-native” replacement is: use one-shot isolated cron jobs as queue items (persisted, retries/backoff, run history) and keep only a tiny dispatcher.

WakeAgent

  • Waking is “native” in the sense that system events + wakeMode are the supported wake mechanism in the CLI/docs.

Docs:

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2) Is there an after_compaction or session:end hook?

Yes — but this is the critical nuance:

Gateway “hooks/” (internal hooks)

Your hooks/session-state-saver is using the internal hooks system (command:new, message:received, etc). That system currently does not give you compaction/session lifecycle events as first-class events (the hooks docs even call session:start / session:end “planned”).

Docs: https://docs.openclaw.ai/automation/hooks

Plugin hooks (agent/gateway lifecycle hooks)

OpenClaw does have plugin hooks for:

  • before_compaction / after_compaction
  • session_start / session_end
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Docs: https://docs.openclaw.ai/concepts/agent-loop and https://docs.openclaw.ai/tools/plugin#plugin-hooks

Practical takeaway: if you want “save state before compaction” to be bulletproof, you either:

  • implement a small plugin that registers before_compaction, or
  • lean on the built-in pre-compaction memory flush (next section), and extend its prompt to also write your “continuation” state.

3) Is openclaw system event --mode now the right wake, or is there cleaner RPC?

Right now, yes, it’s the right supported interface.

A couple clarifications that may reduce your concern about “transcript noise”:

  • System events are designed to be ephemeral (they’re injected into the next heartbeat prompt; they’re not meant to become durable chat history).
  • If you need “wake without meaning,” keep the text tiny + structured (e.g. wake:completion:<label>), and have your HEARTBEAT.md treat it as a signal.

Docs: https://docs.openclaw.ai/cli/system

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If you want something that survives restarts, don’t use system events directly — create a one-shot cron main-session job (--session main --system-event ... --wake now). Cron is persisted; system events aren’t.

Docs: https://docs.openclaw.ai/automation/cron-jobs

4) Should cron isolated + announce be the default for non-interactive work (vs sessions_spawn)?

For “fire-and-forget” background work: yes, isolated cron + announce is the intended default.

Reasons (native advantages you get for free):

  • persistence across gateway restarts
  • run history (openclaw cron runs 
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  • exponential retry backoff on failures
  • delivery without relying on the main session “noticing”
  • isolated runs start fresh each time (less context bloat)
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Where I’d still keep sessions_spawn:

  • genuinely interactive sub-agent work (you plan to steer it mid-run)
  • debugging where you want a live transcript in an isolated session key you’ll manually inspect

Docs:

5) High-impact plugins/features you’re not using (or not fully leveraging)

(A) Built-in pre-compaction “memory flush” (big one)

OpenClaw has a native mechanism to run a silent turn before auto-compaction specifically to prevent “oops, compaction erased the plan.”

Config is under: agents.defaults.compaction.memoryFlush

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Docs (deep + accurate):
https://docs.openclaw.ai/reference/session-management-compaction

If you extend the memoryFlush prompt to also:

  • write/update state/active-work.json
  • write state/compaction-continuation.json
    then you can likely delete the “manual pre-compaction-save.sh” pattern and reduce reliance on /new//reset hooks.

(B) Context pruning (tool-result trimming)

This is a very underused knob for long-running autonomy systems:

  • agents.defaults.contextPruning

It prunes old tool results from in-memory context pre-LLM call (doesn’t rewrite JSONL history), which directly reduces overflow/compaction churn.

Docs: https://docs.openclaw.ai/concepts/session-pruning
Config ref section: agents.defaults.contextPruning in https://docs.openclaw.ai/gateway/configuration-reference

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(C) Use cron delivery targeting explicitly

Your “Action send requires a target” failure smells like jobs that announce without a resolvable delivery.to.

For isolated cron jobs that must always reach James, prefer explicitly setting:

  • --announce --channel telegram --to "<chatId>" (and account if multi-account)

Docs: https://docs.openclaw.ai/cli/cron and https://docs.openclaw.ai/automation/cron-jobs

(D) Plugin hooks for “completion delivery reliability”

If you keep sessions_spawn, the most robust “never swallowed” pattern is a plugin hook like agent_end that always writes a completion marker / posts delivery, rather than relying on the main session to observe it later.

Docs: https://docs.openclaw.ai/concepts/agent-loop

6) Is platform|account|target officially documented?

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I couldn’t find this as a documented core OpenClaw address format, and it does not match the documented openclaw message --target 
 formats.

What is documented/stable:

  • message targets are per-channel (Discord channel:<id>, Telegram chat id, etc.)
  • account id is a separate concept (--account / accountId), not embedded in a pipe string

Docs: https://docs.openclaw.ai/cli/message

So I’d treat platform|account|target as plugin-internal convention (fine to use inside your Claude Code/Codex plugins, but don’t assume it’s a stable OpenClaw public API).

The remaining questions from the gist (quick hits)

Restart continuation (“do X after next restart”)

No built-in “after restart task queue” beyond: persist state + run BOOT.md on startup (via the bundled boot-md hook).

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Docs: https://docs.openclaw.ai/automation/hooks (see boot-md)

If you want a native persisted “run after restart,” schedule a one-shot cron job before restarting. Cron persists; system events don’t.

“agent:bootstrap hook for TASKS.md injection”

You can hook agent:bootstrap, but bootstrap file injection is restricted to recognized bootstrap filenames (AGENTS.md, TOOLS.md, USER.md, etc.). TASKS.md won’t be treated as a bootstrap file by default.

So either:

  • keep tasks in MEMORY.md / USER.md (small “Active tasks” section), or
  • inject TASKS via a plugin hook (before_prompt_build) as prependContext.

Docs: https://docs.openclaw.ai/concepts/agent-loop

“Can plugins call send messages from isolated sessions to main?”

Best native options:

  • cron isolated + announce (delivery is handled by cron, plus main-session summary)
  • or directly send via the message tool (if you want full control)
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Using “system events as IPC” is still the simplest built-in “poke the orchestrator” mechanism.

QMD vs SQLite memory backend

QMD is explicitly experimental and adds operational complexity (sidecar, bun, local models downloads). If SQLite is stable for you, I wouldn’t migrate unless you need:

  • better ranking/reranking
  • indexing session transcripts into memory search at scale

Docs: https://docs.openclaw.ai/concepts/memory (QMD section)

“Better than grep for memory consolidation?”

No first-class “built-in summarization skill” that replaces your workflow. What is native is the pre-compaction memory flush + the ability to run your own consolidation as isolated cron/Lobster steps.

If you want, I can propose a concrete “delete these 5 scripts” refactor plan that:

  1. moves pre-compaction state capture to agents.defaults.compaction.memoryFlush.prompt, and
  2. replaces queue items with one-shot isolated cron jobs (so cron becomes your durable queue + run history).
thin bane
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you only answered 6, can you give me another link where you answered all 14 so i can give it back to mine?

weary ruinBOT
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I don’t have a separate “link where I answered all 14” — that was my bad; I only responded to the first 6.

Here’s a complete all‑14 answer in one place. If you want to hand it back to your team, right‑click this message → Copy Message Link in Discord.

1) Is there a native after_compaction or session:end hook?

Yes, but it’s a plugin hook, not a workspace hooks/ (internal hook) event.

Internal (workspace) hooks (command:new, command:reset, message:received, etc.) are documented here:

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2) Does OpenClaw have inbox/queue primitives natively?

Not really (no first-class “work queue” / “completion inbox” abstraction).

Closest native durable primitive is cron (persisted scheduler + run history + retries/backoff):

Your disk-first queue.jsonl / inbox.jsonl approach is valid; the “more native” alternative is to represent queue items as one-shot isolated cron jobs.

3) Is agent:bootstrap the right way to inject TASKS.md every session?

There is an agent:bootstrap internal hook event, but bootstrap injection is constrained:

  • Bundled internal hook bootstrap-extra-files can inject extra files during agent:bootstrap, but only recognized bootstrap basenames (AGENTS/TOOLS/etc). It’s not a general “inject TASKS.md” mechanism.

If you want TASKS to reliably appear in context, best options:

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  • Put a short “Active tasks” section in MEMORY.md or USER.md (guaranteed bootstrap file), or
  • Use a plugin hook like before_prompt_build to prepend TASKS content.

4) Recommended pattern for “restart continuation” (do X after gateway restart)?

No single built-in “after restart do these steps” queue.

The native building blocks are:

5) Is there a “wakeAgent / triggerHeartbeat RPC” better than system event --mode now?

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openclaw system event --mode now is the supported “wake” mechanism.

If the issue is “system event noise”: keep the event text very small/structured (e.g. wake:completion:<label>), and let HEARTBEAT.md interpret it.

Also important: system events are ephemeral (not persisted across restarts). If you need persistence, use cron.

6) Can plugins send messages from isolated sessions to the main agent (better IPC than system events)?

There’s no “native IPC bus” between isolated sessions and main beyond:

  • cron isolated + delivery mode announce (which also posts a short summary back to main)
  • system events (poke the main heartbeat)
  • or just send via the message tool (explicit delivery control)

Cron docs (delivery modes + main-session summary behavior):

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7) Codex plugin: should you copy Claude Code plugin notification architecture (waiting-for-input, etc.)?

Yes conceptually: you want mid-session “needs input” signals and periodic progress pings.

But whether you can do a true codex_respond “to a running session” depends on the Codex CLI’s IO model:

  • If Codex runs as a live interactive process, you can keep a PTY/stdin handle and implement respond like Claude Code.
  • If Codex is “run → exit” oriented, then your current “respond only after completion” limitation is inherent, and the best you can do is: checkpoint outputs + relaunch with additional instructions.

(So: copy the pattern, but the feasibility depends on the CLI runtime behavior.)

8) Is the platform|account|target pipe format officially documented?

I don’t see it documented as an official OpenClaw public target format. Treat it as a plugin convention, not a stable API.

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The documented/stable targeting formats are per-channel via openclaw message --target 
 and accountId is separate:

If you want something future-proof in your plugins, I’d store it structurally as { channel, accountId, to, threadId }, not a single pipe string.

9) Should you prefer cron add --announce --delete-after-run over sessions_spawn for all non-interactive tasks?

Yes — for “fire-and-forget, non-interactive work”, isolated cron + announce is the intended sweet spot.

Reasons: persisted schedule/job record, retries/backoff, run history, delivery handling, and less reliance on main noticing sub-agent completion.

Docs:

Keep sessions_spawn for genuinely interactive/steerable sub-agent work.

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10) Is there a native “session TTL monitor / stale completion escalation” feature?

Not as a turnkey “alert me if sub-agent didn’t finish in X minutes” feature.

What is native:

  • agent turn timeouts (timeoutSeconds) and cron error backoff/retries
  • run history inspection (cron runs)
  • your watchdog cron is still a reasonable approach.

11) Queue edge case: dispatched-but-not-executed item gets lost — recommended pattern?

Yep: fix it at the state machine level.

Best practices:

  • only mark “dispatched” after you successfully created the cron job / launched the session
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  • add explicit statuses (pending → launching → running → completed/failed) with retries
  • or replace queue items with one-shot cron jobs (so “dispatched” is literally “job exists in cron store”)

Cron storage + behavior: https://docs.openclaw.ai/automation/cron-jobs

12) What OpenClaw features/plugins are you not using that are high-impact?

Two big native knobs for your exact pain points:

  1. Pre-compaction memory flush (silent “write durable state before compaction” turn)

  2. Context pruning (trim old tool results to reduce overflow/compaction churn)

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These two reduce “dropped work mid-task” more than most custom scaffolding.

13) Is QMD backend significantly better than SQLite memory for your workload?

QMD is experimental and adds operational complexity (sidecar + bun + local model downloads), but can improve retrieval quality (BM25 + vectors + reranking).

If SQLite is stable for you: I wouldn’t migrate unless you specifically need:

  • better ranking/reranking,
  • or larger-scale retrieval features (incl. session transcript indexing via QMD’s collections).

Docs: https://docs.openclaw.ai/concepts/memory (QMD section)

14) Better approach than grep-based extraction for daily memory consolidation?

There isn’t a single built-in “memory consolidation engine” that replaces your workflow.

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Most “native-ish” upgrades are:

  • run consolidation as isolated cron (so it’s persisted + repeatable),
  • use memory_search as the selection mechanism, then summarize into MEMORY.md,
  • and lean on the pre-compaction memory flush prompt to keep state from being lost right before compaction.

Memory docs: https://docs.openclaw.ai/concepts/memory
Compaction/memory flush deep dive: https://docs.openclaw.ai/reference/session-management-compaction

If you want, paste the 14 Qs section from your doc and I’ll map each one to a “Delete/Keep/Replace-with-native” recommendation (with a minimal refactor plan).

thin bane
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before you went in much more detail, can you just continue with each question in detail? i will then throw them into an MD file instead.

weary ruinBOT
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Got it. I’ll go question-by-question (all 14) in detail so you can paste straight into an MD file. I’m going to use your gist’s “Questions for Krill” section ordering.

Version note: your thread says 2026.2.13; my local ref checkout here is 2026.2.12, but the hook/cron/compaction surfaces below are stable across that boundary as far as I can see.

1) Is there a native after_compaction or session:end hook?

The important distinction: “internal hooks” vs “plugin hooks”

OpenClaw has two different hook systems and they cover different things:

A) Internal hooks (workspace/managed/bundled hooks/)

These are the ones you’re using (command:new, command:reset, message:received, gateway:startup, etc).

  • Docs: https://docs.openclaw.ai/automation/hooks
  • Great for: responding to chat commands, startup automation (boot-md), message pre-processing, etc.
  • Limitation: they are not the canonical place for compaction lifecycle.
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B) Plugin hooks (agent + gateway lifecycle)

These run inside the agent loop / compaction pipeline and are the right tool for:

So: do these hooks exist?

Yes:

  • before_compaction / after_compaction exist as plugin hooks.
  • session_end exists as a plugin hook and is fired when OpenClaw replaces an existing session with a new session id for the same sessionKey (e.g. /new, idle reset, daily reset, etc.).

What to do with this in your architecture

If your most fragile pattern is “state gets lost around compaction,” the strongest approach is:

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  1. Keep your current disk-first state (active-work.json, etc).
  2. Add a small plugin that:
    • on before_compaction writes a durable “resume capsule” to disk (your state/compaction-continuation.json or similar).
    • optionally on after_compaction stamps metadata (compaction count, timestamp) so the heartbeat can detect “we compacted recently; double-check active work.”

That eliminates “hoping /new or /reset happens.”

2) Does OpenClaw support inbox / queue primitives natively?

Short answer

Not as first-class, generic primitives.

OpenClaw gives you:

  • sessions (per conversation buckets)
  • cron jobs (durable scheduling + execution + delivery)
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  • system events (ephemeral wake signals)
  • plugins + hooks (lifecycle glue)


but there’s no built-in “priority queue” or “completion inbox” concept that you can just enable.

The closest native replacement: use cron as the durable queue

If you want to delete custom queue logic, the most “native” approach is:

  • Treat each queued work item as a one-shot isolated cron job.
  • Use cron’s persisted storage, retry/backoff, and run history as your queue management.
  • If you need priority: encode it in the cron name/metadata and have a dispatcher that only creates N “active” jobs at once.

Docs:

When your custom queue still makes sense

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Your queue.jsonl makes sense when:

  • you need strict priority ordering and atomic dequeue semantics
  • you want “dequeue one item per heartbeat tick” (rate limiting)
  • you want the queue to be human-editable with normal shell tools

My suggestion is often hybrid:

  • Keep active-work.json as the single source of truth (good).
  • Replace queue.jsonl with “pending one-shot cron jobs,” or keep your queue but “dispatch = create cron job.”

3) Is agent:bootstrap the right way to inject TASKS.md every session?

What exists natively

There is an internal hook event agent:bootstrap, and a bundled hook called bootstrap-extra-files.

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The gotcha: only recognized bootstrap filenames are injected

Bootstrap injection is not “any file you want.” OpenClaw’s bootstrap is based on recognized workspace files like:

  • AGENTS.md, SOUL.md, TOOLS.md, IDENTITY.md, USER.md, HEARTBEAT.md, MEMORY.md, etc.

So TASKS.md won’t automatically be treated as a first-class bootstrap file unless you inject it via plugin prompt hooks (see below).

Best-practice options for TASKS

  1. Keep tasks small + put them in a recognized bootstrap file

    • Put “Active tasks / current plan” in MEMORY.md or USER.md.
    • This is the simplest + most stable way to guarantee visibility each turn.

  2. Use a plugin hook (before_prompt_build)

    • Read TASKS.md and inject it as prependContext (or system prompt appendix).
    • This keeps TASKS as a separate file while still always present.

  3. Use bootstrap-extra-files only for recognized basenames

    • Great if you want monorepo-local AGENTS.md / TOOLS.md overrides, etc.
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  • Not the universal solution for arbitrary files.

4) Recommended pattern for restart continuation (your restart-continuation.json approach)

What OpenClaw gives you

This is the “native” place for: “when the gateway comes back, do recovery steps.”

What OpenClaw does not give you (today)

No single built-in “persist this continuation plan and guarantee it runs post-restart.”

So your approach is valid:

  • Write a continuation capsule to disk before restart.
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How to make your current approach less fragile

Your current weak point is “only write restart-continuation.json if env vars were set.”

Instead:

  • Always write restart-continuation.json if active-work.json.active=true.
  • Put “why restart happened” inside the capsule derived from disk state, not env vars.
  • Then BOOT.md does:
    • “if restart-continuation exists: execute, then rename processed”
    • “else if active-work active: resume”

This makes “continuity erasure” much harder.

5) Is openclaw system event --mode now the right way to wake the agent?

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Yes: it’s the canonical supported wake mechanism

Docs: https://docs.openclaw.ai/cli/system

system event does two things:

  • enqueues a system event for the main session
  • with --mode now it triggers the heartbeat immediately (instead of waiting)

The tradeoff you’re noticing (“system event noise”)

That’s real: system events show up as “System:” lines in the prompt for the next heartbeat.

If you want a “cleaner” wake:

  • there isn’t currently a separate public “wake-only RPC” that leaves zero trace
  • the intended pattern is: keep system events short/structured, and have heartbeat interpret them mechanically

When you should not use system events

System events are ephemeral (not persisted). If you need “this must happen even after restart,” use cron (persisted):

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  • Create a one-shot cron main-session job that enqueues a system event and wakes.
  • Or create an isolated cron job that announces to the user directly.

Cron docs: https://docs.openclaw.ai/automation/cron-jobs

6) Should cron isolated + announce be default for non-interactive work vs sessions_spawn?

For “fire-and-forget background work”: yes

Why isolated cron is the best default:

  • persisted scheduling + persisted job record
  • run history (openclaw cron runs)
  • retry/backoff after errors
  • delivery handled by cron (so “main didn’t notice” is less likely)
  • isolated runs don’t bloat main context
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Docs:

When sessions_spawn is still the right tool

Use sessions_spawn when:

  • you expect to “chat with” the sub-agent mid-flight (interactive steering)
  • you want a dedicated isolated session you’ll inspect manually
  • you’re doing exploratory work where iterative prompting matters

Rule of thumb I like:

  • Cron isolated = “batch job”
  • sessions_spawn = “assistant you might interrupt”

7) Is there a native feature for “sub-agent completed but main didn’t notice”?

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There’s no single “guaranteed delivery bus,” but you can stack guarantees

Your current “belt + suspenders” (marker file + inbox + wake) is exactly what people end up building.

Here are the most robust options, ordered by “most native”:

Option A (most native): avoid the ‘main noticing’ requirement

Use isolated cron + announce for anything where completion must be delivered.

  • Cron delivers directly to the channel target; it does not rely on the main session parsing state.
  • It also posts a short summary back to main (so the operator can see it).

Option B: make completion delivery happen in the producing session

If you keep sessions_spawn: have the sub-agent itself send the final message via the message tool with explicit {channel, target}.

This can be extremely reliable, but you must avoid duplicates:

  • If you use cron announce, don’t also message send to the same place unless you’ve explicitly disabled announce or you dedupe.

Option C: use plugin hook agent_end for forced completion marker + ping

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If you want “no completion can be swallowed,” add a plugin hook agent_end that:

  • writes a completion marker file
  • triggers a system event wake
  • optionally emits a minimal “completed” signal message

This prevents “the LLM forgot to call completion-marker.sh.”

Docs for plugin lifecycle hooks: https://docs.openclaw.ai/concepts/agent-loop

8) Is there a recommended way to chain multi-step autonomous workflows?

What you’re doing is basically the right shape

You have:

  • stateful workflow plan (continuation-plans.json)
  • a deterministic dispatcher (“one unit of work per tick”)
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  • phase handoff via cron

That’s a sane design.

The native-ish alternative

The most OpenClaw-native chaining pattern is:

  • each phase is an isolated cron job
  • each job schedules the next phase (either by creating the next cron job, or by enqueueing a main-session system event that causes the dispatcher to do it)

In other words: cron jobs become the workflow engine.

Hardening tip: make chaining idempotent

Ensure each phase has:

  • a stable workflow id + step id
  • “already done?” guard based on a file or DB state
  • safe re-run behavior
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This matters because cron retries/backoff can cause re-execution, and restarts can create partial handoffs.

9) Is there a native “orchestrator” feature you’re missing for long-running autonomy?

OpenClaw is more “control plane primitives” than “one orchestrator module.” The highest-impact native pieces people miss are:

A) Pre-compaction memory flush (this is huge for “dropped work”)

OpenClaw has a built-in mechanism to run a silent flush turn before compaction, so the agent writes durable notes to disk while it still has context.

Deep dive doc (worth reading):
https://docs.openclaw.ai/reference/session-management-compaction

Config is under agents.defaults.compaction.memoryFlush (see config reference too).

Why you care: it’s exactly designed to prevent “compaction happened and now the plan evaporated.”

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B) Context pruning (reduce tool-result bloat → fewer overflows)

Session pruning trims old tool results from the in-memory prompt right before LLM calls.

Docs: https://docs.openclaw.ai/concepts/session-pruning

This directly helps with:

  • long sessions
  • lots of web_fetch, browser, logs, etc.
  • fewer surprise context overflows

10) Is there a better approach for “context overflow dropped work mid-task”?

Use a 3-layer approach:

Layer 1: disk-first “active work” (you already do this)

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This is your active-work.json and it’s correct.

Layer 2: pre-compaction flush (native)

Configure memoryFlush prompt to:

  • update active-work.json
  • write a “resume capsule” (like compaction-continuation.json)
  • optionally append a short line to daily logs

Docs: https://docs.openclaw.ai/reference/session-management-compaction

Layer 3: context pruning (native)

Turn on agents.defaults.contextPruning (cache-ttl) so tool-result blobs don’t push you into compaction as often.

Docs: https://docs.openclaw.ai/concepts/session-pruning

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11) “Is openclaw system event --mode now the right wake, or cleaner RPC?” (your Q3)

You’re already on the right primitive. The “clean” variant is: use cron for persistence and system-event only for wake signals.

If you want fewer system events overall:

  • increase heartbeat cadence or make it reactive by having cron isolated jobs announce directly rather than waking main for every completion

But “wake without any trace” isn’t currently a documented public API.

12) Should cron isolated + announce be default for all non-interactive work? (your Q4)

Yes, with two caveats:

Caveat A: delivery target must be explicit in multi-channel setups

If you rely on “last channel,” you will eventually hit “missing target” problems (you already saw Action send requires a target in one of your crons).

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Best practice:

  • for critical jobs, set explicit delivery.channel + delivery.to (and accountId if needed)

Cron docs (delivery): https://docs.openclaw.ai/automation/cron-jobs

Caveat B: avoid “cron job storms”

If you generate many one-shot jobs (multi-step workflows), ensure you throttle:

  • max concurrent isolated jobs
  • schedule staggering
  • job cleanup (--delete-after-run)

13) What plugins/features are you NOT using that would be high impact? (your Q5)

Based on what you described, the big wins are usually:

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  1. Pre-compaction memory flush (native, solves “lost plan”)

  2. Context pruning

  3. boot-md bundled hook (guaranteed BOOT.md on startup)

  4. Plugin hooks for lifecycle guarantees

  5. (Optional) Webhook delivery mode for cron
    If you want completions to go to an external system reliably (DB, Slack bot, whatever), cron can POST via delivery.mode="webhook" and doesn’t require your main session to be awake.

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14) Is the 3-part pipe format platform|account|target officially documented? (your Q6)

I do not see this documented as an official OpenClaw addressing format.

The documented, supported formats are:

  • per-channel openclaw message --target ... formats
  • account selection via separate --account / accountId

Docs: https://docs.openclaw.ai/cli/message

Recommendation

If your plugins use platform|account|target, treat it as:

  • an internal convenience string (fine)
  • but avoid relying on it across plugins / as a public interface
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For future-proofing, store structured fields:

{ channel: "telegram", accountId: "default", to: "7081...", threadId: 123 }


and only stringify for logs/UI.

If you want, I can do a “refactor blueprint” next

If you paste the exact 14 questions list (or confirm the headings are the ones above), I can write a concrete “keep/delete/replace-with-native” plan, e.g.:

  • Replace pre-compaction-save.sh with memoryFlush prompt + optional before_compaction plugin hook
  • Replace queue.jsonl with one-shot isolated cron jobs
  • Replace “wakeAgent custom scripts” with cron announce + occasional system event --mode now only when main must react

Just say whether you want the blueprint optimized for:

  • maximum reliability (more redundancy), or