Previously, the memory-enriched message (with [Memory context] block
prepended) was saved to per-sender conversation history. On subsequent
turns the LLM saw stale memory fragments with raw keys baked into
prior "user" messages, creating compounding noise.
Save the original msg.content instead. Memory context is still injected
for the current LLM call but no longer persists across turns.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Every user message was auto-saved to memory regardless of length,
flooding the store with trivial entries like "ok", "thanks", "hi".
These noise entries competed with real memories during recall, degrading
relevance — especially with keyword-only search.
Skip auto-saving messages shorter than 20 characters. Applied to both
the channel path (channels/mod.rs) and CLI agent path (agent/loop_.rs).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
build_system_prompt() included a "## Tool Use Protocol" section with
the tag format and usage instructions. build_tool_instructions() then
appended another identical "## Tool Use Protocol" section with full
JSON schemas. This wasted ~1-2K tokens on every API call.
Remove the duplicate protocol block from build_system_prompt(), keeping
only the compact tool name/description list. The complete protocol with
schemas is provided by build_tool_instructions().
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The Channel Capabilities section in build_system_prompt() was hardcoded
to say "You are running as a Discord bot" for ALL channels, including
Telegram. This caused the LLM to misidentify itself and reference
Discord-specific features regardless of the actual channel.
Replace with generic "messaging bot" text. Per-channel delivery
instructions already exist via channel_delivery_instructions().
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Each major subsystem mod.rs now includes a //! doc block explaining the
subsystem purpose, trait-driven architecture, factory registration pattern,
and extension guidance. This improves the generated rustdoc experience for
developers navigating ZeroClaw's modular architecture.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Skill prompts and tool definitions from SKILL.toml were parsed and stored
correctly but never included in the agent's system prompt. Both prompt-building
paths (channels/mod.rs and agent/prompt.rs) only emitted skill metadata (name,
description, location), telling the LLM to "read" the SKILL.toml on demand.
This caused the agent to attempt manual file reads that often failed, leaving
skills effectively ignored.
Now both paths inline <instructions> and <tools> blocks inside each <skill>
XML element, so the agent receives full skill context without extra tool calls.
Closes#877
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add optional thread_ts field to ChannelMessage and SendMessage for
platform-specific threading (e.g. Slack threads, Discord threads).
- ChannelMessage.thread_ts captures incoming thread context
- SendMessage.thread_ts propagates thread context to replies
- SendMessage::in_thread() builder for fluent API
- Slack: send with thread_ts, capture ts from incoming messages
- All reply paths in runtime preserve thread context via in_thread()
- All other channels initialize thread_ts: None (forward-compatible)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The existing iMessage channel relies on AppleScript and only works on macOS.
Linq provides a REST API for iMessage, RCS, and SMS — this gives ZeroClaw
native iMessage support on any platform via webhooks.
Implements LinqChannel following the same patterns as WhatsAppChannel:
- Channel trait impl (send, listen, health_check, typing indicators)
- Webhook handler with HMAC-SHA256 signature verification
- Sender allowlist filtering
- Onboarding wizard step with connection testing
- 18 unit tests covering parsing, auth, and signature verification
Resolves#656 — the prior issue was closed without a merged PR, so this
is the actual implementation.
Add configurable timeout for processing channel messages (LLM + tools).
Default: 300s (optimized for on-device LLMs like Ollama).
Can be overridden in config.toml:
[channels_config]
message_timeout_secs = 600
Add mention_only support for the Mattermost channel, matching the existing
Discord implementation. When enabled, the bot only processes messages that
contain an @-mention of the bot username, reducing noise in busy channels.
- Add mention_only field to MattermostConfig schema (Option<bool>, default false)
- Rename get_bot_user_id() to get_bot_identity() returning (user_id, username)
- Add contains_bot_mention_mm() with case-insensitive word-boundary matching
and metadata.mentions array support
- Add normalize_mattermost_content() to strip @-mentions from processed text
- Wire mention_only through channel and cron factory constructors
- Add 23 new tests covering mention detection, stripping, case-insensitivity,
word boundaries, metadata mentions, empty-after-strip, and disabled passthrough
Adds mention_only config option to Telegram channel, allowing the bot
to only respond to messages that @-mention the bot in group chats.
Direct messages are always processed regardless of this setting.
Behavior:
- When mention_only = true: Bot only responds to group messages containing @botname
- When mention_only = false (default): Bot responds to all allowed messages
- DM/private chats always work regardless of mention_only setting
Implementation:
- Fetch and cache bot username from Telegram API on startup
- Check for @botname mention in group messages
- Strip mention from message content before processing
Config example:
[channels.telegram]
bot_token = "your_token"
mention_only = true
Changes:
- src/config/schema.rs: Add mention_only to TelegramConfig
- src/channels/telegram.rs: Implement mention_only logic + 6 new tests
- src/channels/mod.rs: Update factory calls
- src/cron/scheduler.rs: Update constructor call
- src/onboard/wizard.rs: Update wizard config
- src/daemon/mod.rs: Update test config
- src/integrations/registry.rs: Update test config
- TESTING_TELEGRAM.md: Add mention_only test section
- CHANGELOG.md: Document feature
Risk: medium
Backward compatible: Yes (default: false)
HEARTBEAT.md is only relevant to the heartbeat worker, which reads it
directly from disk. Including it in channel system prompts caused LLMs
to emit spurious 'HEARTBEAT_OK' acknowledgments at the start of
channel responses.
The agent prompt (src/agent/prompt.rs) still includes HEARTBEAT.md,
which is correct for agent and heartbeat contexts.
Add two Mattermost channel enhancements:
1. thread_replies config option (default: false)
- When false, replies go to the channel root instead of threading.
- When true, replies thread on the original post.
- Existing thread replies always stay in-thread regardless of setting.
2. Typing indicator (start_typing/stop_typing)
- Implements the Channel trait's typing methods for Mattermost.
- Fires POST /api/v4/users/me/typing every 4s in a background task.
- Supports parent_id for threaded typing indicators.
- Aborts cleanly on stop_typing via JoinHandle.
Updated all MattermostChannel::new call sites (start_channels, scheduler)
and added 9 unit tests covering thread routing and edge cases.
Channel messages (Telegram, Discord, etc.) previously had no multi-turn
context — each incoming message was processed with a fresh history
containing only the system prompt and the current user message.
This patch:
- Maintains a per-sender conversation history map (Arc<Mutex<HashMap>>)
- Restores prior turns when processing each new message
- Saves user + assistant turns after successful LLM response
- Caps history at 50 messages per sender to bound memory usage
Fixes the channel context continuity issue where the bot would respond
with 'I have no context' to every follow-up question.
Wire the existing provider-layer streaming infrastructure through the
channel trait and agent loop so Telegram users see tokens arrive
progressively via editMessageText, instead of waiting for the full
response.
Changes:
- Add StreamMode enum (off/partial/block) and draft_update_interval_ms
to TelegramConfig (backward-compatible defaults: off, 1000ms)
- Add supports_draft_updates/send_draft/update_draft/finalize_draft to
Channel trait with no-op defaults (zero impact on existing channels)
- Implement draft methods on TelegramChannel using sendMessage +
editMessageText with rate limiting and Markdown fallback
- Add on_delta mpsc::Sender<String> parameter to run_tool_call_loop
(None preserves existing behavior)
- Wire streaming in process_channel_message: when channel supports
drafts, send initial draft, spawn updater task, finalize on completion
Edge cases handled:
- 4096-char limit: finalize draft and fall back to chunked send
- Broken Markdown: use no parse_mode during streaming, apply on finalize
- Edit failures: fall back to sending complete response as new message
- Rate limiting: configurable draft_update_interval_ms (default 1s)
Three fixes for conversation quality issues:
1. loop_.rs and channels now read max_tool_iterations from AgentConfig
instead of using a hardcoded constant of 10, making it configurable.
2. Memory recall now filters entries below a configurable
min_relevance_score threshold (default 0.4), preventing unrelated
memories from bleeding into conversation context.
3. Default hybrid search weights rebalanced from 70/30 vector/keyword
to 40/60, reducing cross-topic semantic bleed.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
run_tool_call_loop used a hardcoded MAX_TOOL_ITERATIONS (10) and
trim_history/auto_compact_history used a hardcoded MAX_HISTORY_MESSAGES (50),
ignoring the user-configurable agent.max_tool_iterations and
agent.max_history_messages values in config.toml.
Meanwhile, agent.rs correctly reads from config — creating an inconsistency
where CLI single-shot mode respected config but the channel runtime and
interactive CLI loop silently ignored it.
Changes:
- Rename constants to DEFAULT_* to clarify they are fallback defaults
- Add max_tool_iterations parameter to run_tool_call_loop
- Add max_history parameter to trim_history and auto_compact_history
- Thread config.agent.max_tool_iterations through ChannelRuntimeContext
- Both CLI code paths now pass config values to run_tool_call_loop
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Refactor the Channel trait to accept a SendMessage struct instead of
separate message and recipient string parameters. This enables passing
additional metadata like email subjects.
Changes:
- Add SendMessage struct with content, recipient, and optional subject
- Update Channel::send() signature to accept &SendMessage
- Update all 12 channel implementations
- Update call sites in channels/mod.rs and gateway/mod.rs
Subject field usage:
- Email: uses subject for email subject line
- DingTalk: uses subject as markdown message title
- All others: ignore subject (no native platform support)
