The Telegram channel adapter listed no 'poll' action, so agents could
not create polls via the unified action interface. The underlying
sendPollTelegram function was already implemented but unreachable.
Changes:
- telegram.ts: add 'poll' to listActions (enabled by default via gate),
add handleAction branch that reads pollQuestion/pollOption params and
delegates to handleTelegramAction with action 'sendPoll'.
- telegram-actions.ts: add 'sendPoll' handler that validates question,
options (≥2), and forwards to sendPollTelegram with threading, silent,
and anonymous options.
- actions.test.ts: add test verifying poll action routes correctly.
Fixes#16977
When a depth-2 subagent (Birdie) completes and its parent (Newton) is a
depth-1 subagent, the announce should go to Newton, not bypass to the
grandparent (Jaris).
Previously, isSubagentSessionRunActive(Newton) returned false because
Newton's agent turn completed after spawning Birdie. This triggered the
fallback to grandparent even though Newton's SESSION was still alive and
waiting for child results.
Now we only fallback to grandparent if the parent SESSION is actually
deleted (no sessionId in session store). If the parent session exists,
we inject into it even if the current run has ended — this starts a new
agent turn to process the child result.
Fixes#18037
Test Plan:
- Added regression test: routes to parent when run ended but session alive
- Added regression test: falls back to grandparent only when session deleted
- Add readWorkspaceContextForSummary() to extract Session Startup + Red Lines from AGENTS.md
- Inject workspace context into compaction summary (limited to 2000 chars)
- Export extractSections() from post-compaction-context.ts for reuse
- Ensures compaction summary includes core rules needed for recovery
Part 1 of post-compaction context injection feature.
recordAssistantUsage accumulated cacheRead across the entire multi-turn
run, and totalTokens was clamped to contextTokens. This caused
session_status to report 100% context usage regardless of actual load.
Changes:
- run.ts: capture lastTurnTotal from the most recent model call and
inject it into the normalized usage before it reaches agentMeta.
- usage-reporting.test.ts: verify usage.total reflects current turn,
not accumulated total.
Fixes#17016
When a model API call hangs indefinitely (e.g. Anthropic quota exceeded
mid-call), the gateway acquires a session .jsonl.lock but the promise
never resolves, so the try/finally block never reaches release(). Since
the owning PID is the gateway itself, stale detection cannot help —
isPidAlive() always returns true.
This commit adds four layers of defense:
1. **In-process lock watchdog** (session-write-lock.ts)
- Track acquiredAt timestamp on each held lock
- 60-second interval timer checks all held locks
- Auto-releases any lock held longer than maxHoldMs (default 5 min)
- Catches the hung-API-call case that try/finally cannot
2. **Gateway startup cleanup** (server-startup.ts)
- On boot, scan all agent session directories for *.jsonl.lock files
- Remove locks with dead PIDs or older than staleMs (30 min)
- Log each cleaned lock for diagnostics
3. **openclaw doctor stale lock detection** (doctor-session-locks.ts)
- New health check scans for .jsonl.lock files
- Reports PID status and age of each lock found
- In --fix mode, removes stale locks automatically
4. **Transcript error entry on API failure** (attempt.ts)
- When promptError is set, write an error marker to the session
transcript before releasing the lock
- Preserves conversation history even on model API failures
Closes#18060
Add support for Z.AI's native tool_stream parameter to enable real-time
visibility into model reasoning and tool call execution.
- Automatically inject tool_stream=true for zai/z-ai providers
- Allow disabling via params.tool_stream: false in model config
- Follows existing pattern of OpenRouter and OpenAI wrappers
This enables Z.AI API features described in:
https://docs.z.ai/api-reference#streaming
AI-assisted: Claude (OpenClaw agent) helped write this implementation.
Testing: lightly tested (code review + pattern matching existing wrappers)
Closes#18135
Synchronous hook that lets plugins inspect and optionally block messages
before they are written to the session JSONL file. Primary use case is
private mode... when enabled, the plugin returns { block: true } and the
message never gets persisted.
The hook runs on the hot path (synchronous, like tool_result_persist).
Handlers execute sequentially in priority order. If any handler returns
{ block: true }, the write is skipped immediately. Handlers can also
return a modified message to write instead of the original.
Changes:
- src/plugins/types.ts: add hook name, event/result types, handler map entry
- src/plugins/hooks.ts: add runBeforeMessageWrite() following tool_result_persist pattern
- src/agents/session-tool-result-guard.ts: invoke hook before every originalAppend() call
- src/agents/session-tool-result-guard-wrapper.ts: wire hook runner to the guard
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Treat normal process exits (even with non-zero codes) as completed tool results.
This prevents standard exit codes (like grep exit 1) from being surfaced
as 'Tool Failure' warnings in the UI. The exit code is still appended
to the tool output for assistant awareness.
Qwen 3 (and potentially other reasoning-capable models served via Ollama)
returns its final answer in a `reasoning` field with an empty `content`
field. This causes blank/empty responses since OpenClaw only reads `content`.
Changes:
- Add `reasoning?` to OllamaChatResponse message type
- Fall back to `reasoning` when `content` is empty in buildAssistantMessage
- Accumulate `reasoning` chunks during streaming when `content` is empty
This allows Qwen 3 to work correctly both with and without /no_think mode.
downgradeOpenAIReasoningBlocks was only called on model change, but
orphaned reasoning items (e.g. from an aborted stream) can exist without
a model switch and cause a 400 from the OpenAI Responses API.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The global `agents.defaults.thinkingDefault` forces a single thinking
level for all models. Users running multiple models with different
reasoning capabilities (e.g. Claude with extended thinking, GPT-4o
without, Gemini Flash with lightweight reasoning) cannot optimise the
thinking level per model.
Add an optional `thinkingDefault` field to `AgentModelEntryConfig` so
each entry under `agents.defaults.models` can declare its own default.
Resolution priority: per-model → global → catalog auto-detect.
Example config:
"models": {
"anthropic/claude-sonnet-4-20250514": { "thinkingDefault": "high" },
"openai/gpt-4o": { "thinkingDefault": "off" }
}
Co-authored-by: Cursor <cursoragent@cursor.com>
