- Add userToken and userTokenReadOnly (default: true) config fields
- Implement token routing: reads prefer user token, writes use bot token
- Add tests for token routing logic
- Update documentation with required OAuth scopes
User tokens enable reading DMs and private channels without requiring
bot membership. The userTokenReadOnly flag (true by default) ensures
the user token can only be used for reads, preventing accidental
sends as the user.
Required user token scopes:
- channels:history, channels:read
- groups:history, groups:read
- im:history, im:read
- mpim:history, mpim:read
- users:read, reactions:read, pins:read, emoji:read, search:read
Telegram General topic (id=1) has inconsistent API behavior:
- sendMessage: rejects explicit message_thread_id=1
- sendChatAction: requires message_thread_id=1 for typing to show
Split into two helper functions:
- buildTelegramThreadParams: excludes General topic for messages
- buildTypingThreadParams: includes General topic for typing
* feat(whatsapp): add debounceMs for batching rapid messages
Add a `debounceMs` configuration option to WhatsApp channel settings
that batches rapid consecutive messages from the same sender into a
single response. This prevents triggering separate agent runs for
each message when a user sends multiple short messages in quick
succession (e.g., "Hey!", "how are you?", "I was wondering...").
Changes:
- Add `debounceMs` config to WhatsAppConfig and WhatsAppAccountConfig
- Implement message buffering in `monitorWebInbox` with:
- Map-based buffer keyed by sender (DM) or chat ID (groups)
- Debounce timer that resets on each new message
- Message combination with newline separator
- Single message optimization (no modification if only one message)
- Wire `debounceMs` through account resolution and monitor tuning
- Add UI hints and schema documentation
Usage example:
{
"channels": {
"whatsapp": {
"debounceMs": 5000 // 5 second window
}
}
}
Default behavior: `debounceMs: 0` (disabled by default)
Verified: All existing tests pass (3204 tests), TypeScript compilation
succeeds with no errors.
Implemented with assistance from AI coding tools.
Closes#967
* chore: wip inbound debounce
* fix: debounce inbound messages across channels (#971) (thanks @juanpablodlc)
---------
Co-authored-by: Peter Steinberger <steipete@gmail.com>
* fix(model-picker): list each provider/model combo separately
Previously, /model grouped models by name and showed all providers
that offer the same model (e.g. 'claude-sonnet-4-5 — anthropic, google-antigravity').
This was confusing because:
1. Users couldn't tell which provider would be used when selecting by number
2. The display implied choice between providers but selection was automatic
Now each provider/model combination is listed separately so users
can explicitly select the exact provider they want.
- Remove model grouping in buildModelPickerItems
- Display format changed from 'model — providers' to 'provider/model'
- pickProviderForModel now returns the single provider directly
- Updated tests to reflect new behavior
* fix: simplify model picker entries (#970) (thanks @mcinteerj)
---------
Co-authored-by: Keith the Silly Goose <keith@42bolton.macnet.nz>
Co-authored-by: Peter Steinberger <steipete@gmail.com>
Add option to disable automatic read receipts for WhatsApp messages.
When set to false, Clawdbot will not mark messages as read (blue ticks).
Closes#344
Changes:
- Add sendReadReceipts to WhatsAppConfig and WhatsAppAccountConfig types
- Add sendReadReceipts to zod schemas for validation
- Add sendReadReceipts to ResolvedWhatsAppAccount with fallback chain
- Pass sendReadReceipts through to monitorWebInbox
- Gate sock.readMessages() call based on config option
Default behavior (true) is preserved - only explicitly setting false
will disable read receipts.
When replaying conversation history to Gemini, tool calls without
thought_signature are downgraded to text blocks like [Tool Call: ...].
This leaked internal technical info into user-facing chat messages.
Added stripDowngradedToolCallText filter alongside existing Minimax
filter to remove these text representations before extraction.
