feat(telemetry): record tool call arguments in logfire spans - #368
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Add the tool call arguments (args dict) to observability spans so telemetry captures what parameters each tool was invoked with. - ToolInterceptCapability.wrap_tool_execute opens a 'tool.call' span with tool_name, tool_call_id, and the validated args dict — the unified interception layer for all tool sources (direct, MCP, ACP). - ToolDisplayCapability.wrap_tool_execute includes the same attributes on its existing instrumentation span. - Add regression test asserting the span carries tool_name, tool_call_id, and the full args dict. Previously the only tool instrumentation recorded the tool name without its parameters, leaving tool call arguments missing from telemetry. Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent) Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
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Summary
Tool call arguments were missing from telemetry: the only instrumentation on the tool execution path recorded the
tool_namebut not the parameters passed to the tool. This PR records the fullargsdict in logfire spans so every tool invocation exports its parameters.Changes
ToolInterceptCapability.wrap_tool_execute()— opens atool.calllogfire span carryingtool_name,tool_call_id, and the validatedargsdict. This is the unified interception layer for all tool sources (direct, MCP, ACP), so arguments are captured regardless of how the tool was registered.ToolDisplayCapability.wrap_tool_execute()— includes the same attributes on its existing instrumentation span (rich/diff display path).tool_name,tool_call_id, and the fullargsdict.changelog/unreleased/2026-08-11-tool-call-telemetry-args.md.Verification
ruff check+ruff formatcleanmypy --strictclean on changed source filesNotes
Args are written as a single span attribute (JSON-serialized by logfire). If per-argument structured attributes are desired for querying, that can be a follow-up.