* fix(ai): replace stale OpenRouter Llama 4 Maverick test model
- Switch OpenRouter Meta test model from `meta-llama/llama-4-maverick` to `meta-llama/llama-4-scout` in AI tests.
- CI failure body:
- packages/ai/test/context-overflow.test.ts(531,41): error TS2345: Argument of type "meta-llama/llama-4-maverick" is not assignable to parameter of type "...".
- packages/ai/test/total-tokens.test.ts(520,40): error TS2345: Argument of type "meta-llama/llama-4-maverick" is not assignable to parameter of type "...".
* chore(ai): add changelog entry for OpenRouter test model swap
- Add Unreleased Fixed entry for switching OpenRouter Meta test model to llama-4-scout
- Reference PR #3421 attribution
When model.maxTokens is 0 (unset/unknown), omit maxTokens from the
Bedrock ConverseStream inferenceConfig instead of sending 0.
Bedrock's inferenceConfig.maxTokens is optional — when omitted, the
model uses its own internal default. This is optimal for Bedrock's
token quota management:
- At request start, Bedrock reserves input_tokens + max_tokens from
your TPM quota
- For Claude 3.7+ models, output tokens have a 5x burndown rate
- Sending an unnecessarily high maxTokens wastes TPM capacity during
the reservation window, reducing concurrent request throughput
- Omitting it lets Bedrock use the model default (~4096 for Claude),
matching expected output sizes and maximizing quota utilization
Also applies the same conditional pattern to temperature — only
include it in inferenceConfig when explicitly set.
Changes:
- simple-options.ts: Use ?? instead of || so explicit 0 is preserved;
return undefined when model.maxTokens is 0 (unset)
- amazon-bedrock.ts: Spread maxTokens and temperature into
inferenceConfig only when defined
Fixes#3399
BedrockRuntimeClient was constructed without the endpoint option,
causing model.baseUrl to be silently ignored. This meant custom
Bedrock endpoints (VPC endpoints, proxy setups, custom routing)
were never used — requests always went to the default regional
endpoint.
Pass model.baseUrl as the endpoint config when set. When not set
(the default), the SDK falls back to the standard regional endpoint
constructed from the region config, preserving existing behavior.
Fixesopenclaw/openclaw#47899
Some models (Opus 4.6, GLM-5.1) send the edits parameter as a JSON
string instead of a parsed array. This fails AJV validation with
'must be array' and models fall back to sed/python.
Parse stringified edits in prepareEditArguments before validation.
* feat(agent,coding-agent): add per-tool executionMode field to AgentTool and ToolDefinition
Add optional executionMode?: ToolExecutionMode to AgentTool and
ToolDefinition interfaces. Propagate through wrapToolDefinition and
createToolDefinitionFromAgentTool. No behavioral change yet — agent
loop will read this field in a follow-up.
* feat(agent): support per-tool executionMode override for sequential execution
When a tool defines executionMode='sequential', the agent loop
forces sequential execution of all tool calls in that batch,
even if the global config is parallel.
* feat(coding-agent): re-export ToolExecutionMode from @mariozechner/pi-agent-core
Makes the type available to extensions that want to set
executionMode on tool definitions.
* feat(coding-agent): add tic-tac-toe extension example with executionMode: sequential
Demonstrates per-tool executionMode: the agent plays via move/play
tool calls that share a cursor. Without sequential execution, play
can resolve before earlier moves finish, landing on the wrong cell.
