MALFORMED_FUNCTION_CALL seems to be easily triggered by the model (Gemini) due to writing todo.

[XinyueZ]

Currently, I have found that the frequency of this issue occurring on write todo is quite high.

│   │   AIMessage(
│   │   │   content='',
│   │   │   additional_kwargs={},
│   │   │   response_metadata={
│   │   │   │   'is_blocked': False,
│   │   │   │   'safety_ratings': [],
│   │   │   │   'usage_metadata': {
│   │   │   │   │   'prompt_token_count': 5553,
│   │   │   │   │   'total_token_count': 5553,
│   │   │   │   │   'prompt_tokens_details': [{'modality': 1, 'token_count': 5553}],
│   │   │   │   │   'candidates_token_count': 0,
│   │   │   │   │   'thoughts_token_count': 0,
│   │   │   │   │   'cached_content_token_count': 0,
│   │   │   │   │   'cache_tokens_details': [],
│   │   │   │   │   'candidates_tokens_details': []
│   │   │   │   },
│   │   │   │   'finish_reason': 'MALFORMED_FUNCTION_CALL',
│   │   │   │   'finish_message': 'Malformed function call: print(default_api.write_todos(todos=[\n    default_api.WriteTodosTodos(content=\'Perform web search for "CrewAI vs LangGraph comparison"\', status=\'pending\'),\n    default_api.WriteTodosTodos(content=\'Analyze search results for key information on architecture, scalability, integration, community, documentation, licensing, cost, and use cases for both CrewAI and LangGraph.\', status=\'pending\'),\n    default_api.WriteTodosTodos(content=\'Perform web search for "CrewAI architecture performance integration"\', status=\'pending\'),\n    default_api.WriteTodosTodos(content=\'Analyze search results for key information on architecture, scalability, integration, community, documentation, licensing, cost, and use cases for both CrewAI and LangGraph.\', status=\'pending\'),\n    default_api.WriteTodosTodos(content=\'Perform web search for "LangGraph architecture performance integration"\', status=\'pending\'),\n    default_api.WriteTodosTodos(content=\'Analyze search results for key information on architecture, scalability, integration, community, documentation, licensing, cost, and use cases for both CrewAI and LangGraph.\', status=\'pending\'),\n    default_api.WriteTodosTodos(content=\'Consolidate all findings and generate a comprehensive report comparing CrewAI and LangGraph.\', status=\'pending\')\n]))',
│   │   │   │   'model_name': 'gemini-2.5-flash'
│   │   │   },
│   │   │   id='run--8a36437b-6e83-4081-881e-e4bb174b752d-0',
│   │   │   usage_metadata={'input_tokens': 5553, 'output_tokens': 0, 'total_tokens': 5553, 'input_token_details': {'cache_read': 0}}
│   │   )
│   ],

[riadzeitounn]

Happening to me alot, although I tell the model not to write code, but gemini 2.5 pro for some reason always does that

[XinyueZ]

up to repo owner

[haadirakhangi]

Facing the same issue. Is there any way to fix it?

[nhuang-lc]

@XinyueZ it looks like you were running into this with gemini-2.5-flash, were there other models where you were seeing this behavior as well?

@riadzeitounn looks like gemini-2.5-pro also had this issue

@haadirakhangi was your issue with gemini as well?

Personally I usually test with the latest OpenAI (gpt-4.1, gpt-5) / Anthropic models (sonnet 3-7 and up, recently 4 and 4-5) and I don't see this issue. I'll investigate this.

It might be good to add retries automatically to try and mitigate this issue

[XinyueZ]

Retry is a good idea, but where? Internal or external at use side?

@XinyueZ it looks like you were running into this with gemini-2.5-flash, were there other models where you were seeing this behavior as well?

@riadzeitounn looks like gemini-2.5-pro also had this issue

@haadirakhangi was your issue with gemini as well?

Personally I usually test with the latest OpenAI (gpt-4.1, gpt-5) / Anthropic models (sonnet 3-7 and up, recently 4 and 4-5) and I don't see this issue. I'll investigate this.

It might be good to add retries automatically to try and mitigate this issue

[haadirakhangi]

Yeah, I ran into the same problem with Gemini. It seems like Gemini can't handle tools names that includes hypens -. I noticed this while using an MCP server that followed that naming convention.

@haadirakhangi was your issue with gemini as well?

Personally I usually test with the latest OpenAI (gpt-4.1, gpt-5) / Anthropic models (sonnet 3-7 and up, recently 4 and 4-5) and I don't see this issue. I'll investigate this.

It might be good to add retries automatically to try and mitigate this issue