anyllm-proxy/docs/tool-calling-diffs.md

Tool Calling Differences: Anthropic vs OpenAI

Tool Definitions

Aspect	Anthropic	OpenAI
Wrapper type	None (flat)	{type: "function", function: {...}}
Schema field	input_schema (JSON Schema)	function.parameters (JSON Schema)
Description	description (optional)	function.description (optional)
Name	name	function.name

Tool Use in Responses

Aspect	Anthropic	OpenAI
Location	Content blocks in assistant message	tool_calls[] in assistant message
ID field	tool_use.id	tool_call.id
Name	tool_use.name	tool_call.function.name
Arguments	tool_use.input (JSON object)	tool_call.function.arguments (JSON string)

Tool Results

Aspect	Anthropic	OpenAI
Location	Content block in user message	Separate tool role message
Reference	tool_result.tool_use_id	tool_call_id in message
Error flag	is_error: true	No standard error flag
Content	String or content blocks	String

Streaming Tool Calls

Aspect	Anthropic	OpenAI
Start event	content_block_start with tool_use block	Chunk delta with tool_calls[].id
Argument deltas	input_json_delta (partial JSON)	tool_calls[].function.arguments (fragments)
End event	content_block_stop	finish_reason: "tool_calls"

ID Strategy

This proxy uses a stateless ID bridge: the OpenAI tool_call.id is used directly as the Anthropic tool_use.id. This avoids server-side session storage and allows the client to reference tool calls across turns without the proxy maintaining state.

Known Limitations

• OpenAI arguments may contain invalid JSON (partial deltas, truncated output). The proxy uses lenient parsing that wraps unparseable strings as Value::String.
• Anthropic supports is_error on tool results; OpenAI has no equivalent. The proxy prepends "Error: " to error content.
• Parallel tool use control (disable_parallel_tool_use in Anthropic) has no direct OpenAI equivalent.