Configure OpenClaw Streaming and Chunking for Faster Output

Waiting for an AI to finish a long response can feel like watching paint dry. If you send the whole message at once, the user might think the bot is broken. If you send every single word as a new message, you end up spamming their notifications. Getting streaming and chunking right is what makes a bot feel responsive and helpful.

OpenClaw has two separate streaming layers:

• Block streaming (channels): emit completed blocks as the assistant writes. These are normal channel messages (not token deltas).
• Preview streaming (Telegram/Discord/Slack): update a temporary preview message while generating.

There is no true token-delta streaming to channel messages today. Preview streaming is message-based (send + edits/appends).

Block streaming (channel messages)

Block streaming sends assistant output in coarse chunks as it becomes available.

Model output
  └─ text_delta/events
       ├─ (blockStreamingBreak=text_end)
       │    └─ chunker emits blocks as buffer grows
       └─ (blockStreamingBreak=message_end)
            └─ chunker flushes at message_end
                   └─ channel send (block replies)

Legend:

• text_delta/events: model stream events (may be sparse for non-streaming models).
• chunker: EmbeddedBlockChunker applying min/max bounds + break preference.
• channel send: actual outbound messages (block replies).

Controls:

• agents.defaults.blockStreamingDefault: "on"/"off" (default off).
• Channel overrides: *.blockStreaming (and per-account variants) to force "on"/"off" per channel.
• agents.defaults.blockStreamingBreak: "text_end" or "message_end".
• agents.defaults.blockStreamingChunk: { minChars, maxChars, breakPreference? }.
• agents.defaults.blockStreamingCoalesce: { minChars?, maxChars?, idleMs? } (merge streamed blocks before send).
• Channel hard cap: *.textChunkLimit (e.g., channels.whatsapp.textChunkLimit).
• Channel chunk mode: *.chunkMode (length default, newline splits on blank lines (paragraph boundaries) before length chunking).
• Discord soft cap: channels.discord.maxLinesPerMessage (default 17) splits tall replies to avoid UI clipping.

Boundary semantics:

• text_end: stream blocks as soon as chunker emits; flush on each text_end.
• message_end: wait until assistant message finishes, then flush buffered output.

message_end still uses the chunker if the buffered text exceeds maxChars, so it can emit multiple chunks at the end.

Chunking algorithm (low/high bounds)

Block chunking is implemented by EmbeddedBlockChunker:

• Low bound: don’t emit until