## Summary - Improve tool call error messages across 4 libraries (arcade-core, arcade-tdk, arcade-mcp-server, arcade-serve) so agents can self-correct and Datadog can facet on structured fields - Guard empty error messages, enrich input validation errors with field-level detail, fix `@tool` decorator fallback formatting, surface `additional_prompt_content` in MCP responses, and add structured log extras for Datadog - Addresses the 3 worst error patterns: generic "Error in tool input deserialization", bare `KeyError` values, and empty `FatalToolError` messages **Linear:** TOO-627 **Plan:** `docs/plans/2026-04-08-improve-error-messages-handoff.md` ## Tasks - [ ] Task 1: Guard empty error messages (arcade-core) - [ ] Task 2: Enrich input validation error messages (arcade-core) - [ ] Task 3: Improve `@tool` decorator error fallback (arcade-tdk) - [ ] Task 4: Fix MCP agent-facing error response (arcade-mcp-server) - [ ] Task 5: Add structured log extras in BaseWorker (arcade-serve) - [ ] Task 6: Add structured log extras in MCP server (arcade-mcp-server) ## Test plan - [ ] Each task has dedicated unit tests verifying the new behavior - [ ] `make test` passes after all tasks - [ ] `make check` (ruff + mypy) passes - [ ] Verify the 3 worst error patterns now produce actionable messages 🤖 Generated with [Claude Code](https://claude.com/claude-code) <!-- CURSOR_SUMMARY --> --- > [!NOTE] > **Medium Risk** > Touches cross-library error formatting and logging behavior used in production tool execution paths; while mostly additive/guardrails, it changes agent-visible messages and Datadog log facets, which could impact client expectations and alerting. > > **Overview** > Improves tool-call error handling across core/runtime, MCP transport, worker transport, and the TDK to make agent-visible failures more actionable while *reducing sensitive-data leakage*. > > In `arcade-core`, empty error messages now get placeholders, `ToolOutputFactory.fail*` defaults blank messages, and input validation errors are rewritten as field-level summaries that intentionally omit rejected values (avoiding Pydantic echo of secrets). The `@tool` fallback in `arcade-tdk` no longer surfaces `str(exception)` to agents; it returns exception *type-only* in `message` while preserving full detail in `developer_message`. > > Adds a shared `build_tool_error_log_extra` helper and updates `arcade-serve` + `arcade-mcp-server` to emit consistent structured WARNING logs (`error_*`, `tool_name`, optional toolkit/version) for Datadog, while MCP error responses now append `additional_prompt_content` and force `structuredContent=None` on failures per spec. Includes extensive new tests and bumps package versions (`arcade-core` 4.6.2, `arcade-tdk` 3.6.1, `arcade-mcp-server` 1.19.3, `arcade-serve` 3.2.3). > > <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit e5c7ebcaf56176cfbd8e6d1f2b6295352abd0ec0. Bugbot is set up for automated code reviews on this repo. Configure [here](https://www.cursor.com/dashboard/bugbot).</sup> <!-- /CURSOR_SUMMARY --> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
126 lines
4.2 KiB
Python
126 lines
4.2 KiB
Python
from typing import Any, TypeVar
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from pydantic import BaseModel
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from arcade_core.errors import ErrorKind
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from arcade_core.schema import ToolCallError, ToolCallLog, ToolCallOutput
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from arcade_core.utils import coerce_empty_list_to_none
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T = TypeVar("T")
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class ToolOutputFactory:
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"""
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Singleton pattern for unified return method from tools.
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"""
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def success(
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self,
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*,
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data: T | None = None,
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logs: list[ToolCallLog] | None = None,
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) -> ToolCallOutput:
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# Extract the result value
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"""
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Extracts the result value for the tool output.
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The executor guarantees that `data` is either a string, a dict, or None.
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"""
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value: str | int | float | bool | dict | list | None
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if data is None:
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value = ""
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elif hasattr(data, "result"):
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result = getattr(data, "result", "")
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# Handle None result the same way as None data
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if result is None:
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value = ""
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# If the result is a BaseModel (e.g., from TypedDict conversion), convert to dict
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elif isinstance(result, BaseModel):
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value = result.model_dump()
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# If the result is a list, check if it contains BaseModel objects
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elif isinstance(result, list):
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value = [
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item.model_dump() if isinstance(item, BaseModel) else item for item in result
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]
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else:
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value = result
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elif isinstance(data, BaseModel):
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value = data.model_dump()
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elif isinstance(data, (str, int, float, bool, list, dict)):
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value = data
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else:
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raise ValueError(f"Unsupported data output type: {type(data)}")
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logs = coerce_empty_list_to_none(logs)
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return ToolCallOutput(
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value=value,
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logs=logs,
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)
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def fail(
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self,
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*,
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message: str,
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developer_message: str | None = None,
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stacktrace: str | None = None,
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logs: list[ToolCallLog] | None = None,
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additional_prompt_content: str | None = None,
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retry_after_ms: int | None = None,
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kind: ErrorKind = ErrorKind.UNKNOWN,
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can_retry: bool = False,
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status_code: int | None = None,
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extra: dict[str, Any] | None = None,
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) -> ToolCallOutput:
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if not message or not message.strip():
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message = "Unspecified error during tool execution"
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return ToolCallOutput(
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error=ToolCallError(
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message=message,
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developer_message=developer_message,
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can_retry=can_retry,
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additional_prompt_content=additional_prompt_content,
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retry_after_ms=retry_after_ms,
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stacktrace=stacktrace,
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kind=kind,
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status_code=status_code,
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extra=extra,
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),
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logs=coerce_empty_list_to_none(logs),
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)
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def fail_retry(
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self,
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*,
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message: str,
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developer_message: str | None = None,
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additional_prompt_content: str | None = None,
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retry_after_ms: int | None = None,
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stacktrace: str | None = None,
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logs: list[ToolCallLog] | None = None,
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kind: ErrorKind = ErrorKind.TOOL_RUNTIME_RETRY,
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status_code: int = 500,
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extra: dict[str, Any] | None = None,
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) -> ToolCallOutput:
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"""
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DEPRECATED: Use ToolOutputFactory.fail instead.
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This method will be removed in version 3.0.0
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"""
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if not message or not message.strip():
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message = "Unspecified error during tool execution"
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return ToolCallOutput(
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error=ToolCallError(
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message=message,
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developer_message=developer_message,
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can_retry=True,
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additional_prompt_content=additional_prompt_content,
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retry_after_ms=retry_after_ms,
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stacktrace=stacktrace,
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kind=kind,
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status_code=status_code,
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extra=extra,
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),
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logs=coerce_empty_list_to_none(logs),
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)
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output_factory = ToolOutputFactory()
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