## 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>
When a tool’s output TypedDict uses total=False, MCP clients reject the
response with:
```
MCP error -32602: Structured content does not match the tool's output schema
```
Note that the bug also exists for the Engine transport
(/worker/tools/execute), but since the engine doesn't validate the
output schema, the bug never surfaced. This PR addresses the problem
holistically (MCP and Engine) in preparation for a future where the
Engine transport validates output schemas.
Two bugs combined to cause this:
1. Schema: The outputSchema had no required array and declared all
fields as strict types (e.g. "type": "string"), making every field look
mandatory and non-null.
2. Serialization: model_dump() on TypedDict-derived Pydantic models
emitted None for absent optional fields. A tool returning {"name":
"hello"} produced {"name": "hello", "optional_field": null} which is a
value the schema forbids.
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> **Medium Risk**
> Adjusts core schema generation and MCP JSON Schema conversion for
TypedDicts, affecting how tool input/output contracts are emitted and
validated across clients; mistakes could break compatibility or
validation behavior.
>
> **Overview**
> Fixes MCP/engine validation failures for `TypedDict(total=False)`
outputs by ensuring absent optional keys are **omitted from serialized
output** and that emitted schemas correctly describe **required vs
optional** keys.
>
> `arcade-core` now tracks `required_keys`/`inner_required_keys` and
per-field `nullable` in `ValueSchema`, derives required sets from
TypedDict `__required_keys__`, and unwraps `Optional[T]` to support
optional nested TypedDicts; TypedDict-derived Pydantic models now
`model_dump(exclude_unset=True)` to avoid leaking missing fields as
`null`.
>
> `arcade-mcp-server` JSON Schema conversion now emits `required` arrays
(including for arrays of objects), supports `nullable` by generating
`type: [<type>, "null"]` (and `enum` including `None`), and treats
nullable top-level objects as valid unwrapped output schemas. Adds
focused unit/end-to-end tests plus an expanded example server
demonstrating total-false, mixed required/optional, nullable, and
optional-nested TypedDict outputs, and bumps package
versions/dependencies accordingly.
>
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
53fe8365f613053599130520b75f30b614b465ca. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
<!-- CURSOR_SUMMARY -->
> [!NOTE]
> **Medium Risk**
> Tightens validation on tool metadata, which may break existing tools
that relied on non-JSON-serializable `extras` values or keys; changes
are localized and well-covered by tests.
>
> **Overview**
> Adds **JSON-safety enforcement** for `ToolMetadata.extras`: top-level
keys must be strings at model construction, and `validate_for_tool()`
now recursively rejects non-JSON-native values (including non-finite
floats) with path-rich `ToolDefinitionError` messages.
>
> Expands tests to cover valid/invalid nested `extras` cases and
error-message quality, and bumps `arcade-core` version to `4.5.0`.
>
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
2bab0db3c17f0ddb97868764d10494da543b39e5. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
Closes TOO-192
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> Adds a Figma OAuth2 auth provider and wires it through TDK and MCP
server, with tests updated and package versions bumped.
>
> - **Auth**:
> - Add `Figma` OAuth2 provider in
`libs/arcade-core/arcade_core/auth.py`.
> - **Exports**:
> - Expose `Figma` in
`libs/arcade-mcp-server/arcade_mcp_server/auth/__init__.py` and
`libs/arcade-tdk/arcade_tdk/auth/__init__.py` (`__all__`).
> - **Tests**:
> - Add Figma auth requirement test case in
`libs/tests/tool/test_create_tool_definition.py` and import `Figma`.
> - **Versioning**:
> - Bump `arcade-mcp-server` to `1.10.2` and `arcade-tdk` to `3.2.0`.
>
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
2bacfdc5695b3e7fc5e4532dbd360c3b2263130e. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
---------
Co-authored-by: Francisco Liberal <francisco@arcade.dev>
# Improvements to Arcade TDK Error Handling
I tried my very best to not make any breaking changes in this PR. So,
you will notice various "Deprecation" notices throughout.
### Instructions for PR reviewers
1. Pull down this PR's branch
2. Pull down the Engine's tool error handling PR's branch
3. Update your installed arcadepy to have the following:
- In `arcadepy/resources/tools/tools.py`, if you want to test out
including stacktraces, then you need to update `ToolsResource.execute`
to accept a `include_error_stacktrace` argument and also include the
"include_error_stacktrace" argument to the POST to the Engine inside of
the function's execute method's body.
- In `arcadepy/types/execute_tool_response.py` add the following enum
```py
class ErrorKind(str, Enum):
"""Error kind that is comprised of
- the who (toolkit, tool, upstream)
- the when (load time, definition parsing time, runtime)
- the what (bad_definition, bad_input, bad_output, retry,
context_required, fatal, etc.)"""
TOOLKIT_LOAD_FAILED = "TOOLKIT_LOAD_FAILED"
TOOL_DEFINITION_BAD_DEFINITION = "TOOL_DEFINITION_BAD_DEFINITION"
TOOL_DEFINITION_BAD_INPUT_SCHEMA = "TOOL_DEFINITION_BAD_INPUT_SCHEMA"
TOOL_DEFINITION_BAD_OUTPUT_SCHEMA = "TOOL_DEFINITION_BAD_OUTPUT_SCHEMA"
TOOL_RUNTIME_BAD_INPUT_VALUE = "TOOL_RUNTIME_BAD_INPUT_VALUE"
TOOL_RUNTIME_BAD_OUTPUT_VALUE = "TOOL_RUNTIME_BAD_OUTPUT_VALUE"
TOOL_RUNTIME_RETRY = "TOOL_RUNTIME_RETRY"
TOOL_RUNTIME_CONTEXT_REQUIRED = "TOOL_RUNTIME_CONTEXT_REQUIRED"
TOOL_RUNTIME_FATAL = "TOOL_RUNTIME_FATAL"
UPSTREAM_RUNTIME_BAD_REQUEST = "UPSTREAM_RUNTIME_BAD_REQUEST"
UPSTREAM_RUNTIME_AUTH_ERROR = "UPSTREAM_RUNTIME_AUTH_ERROR"
UPSTREAM_RUNTIME_NOT_FOUND = "UPSTREAM_RUNTIME_NOT_FOUND"
UPSTREAM_RUNTIME_VALIDATION_ERROR = "UPSTREAM_RUNTIME_VALIDATION_ERROR"
UPSTREAM_RUNTIME_RATE_LIMIT = "UPSTREAM_RUNTIME_RATE_LIMIT"
UPSTREAM_RUNTIME_SERVER_ERROR = "UPSTREAM_RUNTIME_SERVER_ERROR"
UPSTREAM_RUNTIME_UNMAPPED = "UPSTREAM_RUNTIME_UNMAPPED"
UNKNOWN = "UNKNOWN"
```
- In `arcadepy/types/execute_tool_response.py` add the following fields
to OutputError:
```py
kind: ErrorKind
status_code: Optional[int] = None
stacktrace: Optional[str] = None
extra: Optional[dict[str, Any]] = None
```
### Example Client Usage
```py
# Example of handling an upstream rate limit
error = response.output.error
if error and error.kind == ErrorKind.UPSTREAM_RUNTIME_RATE_LIMIT:
sleep_time = error.retry_after_ms / 1000
time.sleep(sleep_time)
# and then execute again
```
```py
# Examples of determining what type of runtime error it is
error = response.output.error
if error:
is_retryable_error = error.kind == ErrorKind.TOOL_RUNTIME_RETRY
is_a_bug_in_the_tool = error.kind == ErrorKind.TOOL_RUNTIME_FATAL
is_additional_context_required = error.kind == ErrorKind.TOOL_RUNTIME_CONTEXT_REQUIRED
```
### Example Tool Usage
```py
# EXAMPLE 1 letting Arcade handle upstream error handling for you
reddit_client.post(params) # Arcade's httpx adapter will handle error handling for you!
# ------------------------------------
# EXAMPLE 2 handling upstream bad request yourself, but letting Arcade handle the rest
try:
reddit_client.post(params)
except httpx.HTTPStatusError as e:
if e.status_code == 400:
raise UpstreamError("My extra custom message) from e
raise
```
```py
# EXAMPLE 1 letting Arcade handle it for you
risky_element = my_risky_list[42] # Arcade will raise a FatalToolError for you
# ------------------------------------
# EXAMPLE 2 handling it yourself for extra flexibility
try:
risky_element = my_risky_list[42]
except IndexError as e:
raise FatalToolError("My extra custom message") from e
```
### Non-runtime Error Message Examples
Example ToolkitLoadError Messages:
```
- [TOOLKIT_LOAD_FAILED] ToolkitLoadError when loading toolkit 'sample_tool': Could not import module mock_module. Reason: Mock import error
- [TOOLKIT_LOAD_FAILED] ToolkitLoadError when loading toolkit 'test_toolkit': Tool 'ValidTool' in toolkit 'test_toolkit' already exists in the catalog.
```
Example ToolDefinitionError Messages
```
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_missing_description': Tool 'tool_missing_description' is missing a description
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_with_invalid_secret_type': Secret keys must be strings (error in tool ToolWithInvalidSecretType).
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_with_empty_secret': Secrets must have a non-empty key (error in tool ToolWithEmptySecret).
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_with_invalid_metadata_type': Metadata must be strings (error in tool ToolWithInvalidMetadataType).
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_with_metadata_requiring_auth_without_auth': Tool ToolWithMetadataRequiringAuthWithoutAuth declares metadata key 'client_id', which requires that the tool has an auth requirement, but no auth requirement was provided. Please specify an auth requirement.
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_with_empty_metadata': Metadata must have a non-empty key (error in tool ToolWithEmptyMetadata).
- [TOOL_DEFINITION_BAD_DEFINITION] ToolDefinitionError in definition of tool 'tool_with_unsupported_param_type': Unsupported parameter type: <class 'test_catalog.MyFancyTestClass'>
```
Example ToolInputSchemaError Messages
```
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_missing_input_parameter_annotation': Parameter 'input_text' is missing a description
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_no_type_annotation': Parameter param has no type annotation.
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_invalid_param_name': Invalid parameter name: '123invalid' is not a valid identifier. Identifiers must start with a letter or underscore, and can only contain letters, digits, or underscores.
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_too_many_annotations': Parameter param: Annotated[str, 'name', 'desc', 'extra'] has too many string annotations. Expected 0, 1, or 2, got 3.
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_required_union_param': Parameter param is a union type. Only optional types are supported.
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_non_callable_default_factory': Default factory for parameter param: Annotated[str, 'Parameter'] = FieldInfo(annotation=NoneType, required=False, default_factory=str) is not callable.
- [TOOL_DEFINITION_BAD_INPUT_SCHEMA] ToolInputSchemaError in definition of tool 'tool_with_multiple_tool_contexts': Only one ToolContext parameter is supported, but tool tool_with_multiple_tool_contexts has multiple.
```
Example ToolOutputSchemaError Messages
```
- [TOOL_DEFINITION_BAD_OUTPUT_SCHEMA] ToolOutputSchemaError in definition of tool 'tool_missing_return_type_hint': Tool 'ToolMissingReturnTypeHint' must have a return type
- [TOOL_DEFINITION_BAD_OUTPUT_SCHEMA] ToolOutputSchemaError in definition of tool 'tool_with_unsupported_output_type': Unsupported output type '<class 'test_catalog.MyFancyTestClass'>'. Only built-in Python types, TypedDicts, Pydantic models, and standard collections are supported as tool output types.
```
### Runtime Error Message Examples
Example Tool Runtime Error Messages
```
- [TOOL_RUNTIME_FATAL] FatalToolError during execution of tool 'get_posts_in_subreddit': list index out of range
- [TOOL_RUNTIME_CONTEXT_REQUIRED] ContextRequiredToolError during execution of tool 'get_posts_in_subreddit': Ambiguous username. Please provide a more specific username
- [TOOL_RUNTIME_RETRY] RetryableToolError during execution of tool 'get_posts_in_subreddit': Retry with subreddit=learnpython or subreddit=learnprogramming
```
Example Upstream Runtime Error Messages
```
- [UPSTREAM_RUNTIME_RATE_LIMIT] UpstreamRateLimitError during execution of tool 'get_posts_in_subreddit': 429 Client Error: Too Many Requests
- [UPSTREAM_RUNTIME_BAD_REQUEST] UpstreamError during execution of tool 'get_posts_in_subreddit': 400 Client Error: Bad request. Missing 'id' parameter.
- [UPSTREAM_RUNTIME_BAD_REQUEST] UpstreamError during execution of tool 'search_files': Upstream Google API error: Invalid value '-23'. Values must be within the range: [value: 1\n, value: 1000\n]
```
## Before
### Tool: ``GoogleNews.SearchNewsStories``
```python
@tool(requires_secrets=["SERP_API_KEY"])
async def search_news_stories(
context: ToolContext,
keywords: Annotated[
str,
"Keywords to search for news articles. E.g. 'Apple launches new iPhone'.",
],
country_code: Annotated[
CountryCode | None,
"2-character country code to search for news articles. "
"E.g. 'us' (United States). "
f"Defaults to '{DEFAULT_GOOGLE_NEWS_COUNTRY}'.",
] = None,
language_code: Annotated[
LanguageCode,
"2-character language code to search for news articles. E.g. 'en' (English). "
f"Defaults to '{DEFAULT_GOOGLE_NEWS_LANGUAGE}'.",
] = DEFAULT_GOOGLE_NEWS_LANGUAGE,
limit: Annotated[
int | None,
"Maximum number of news articles to return. Defaults to None "
"(returns all results found by the API).",
] = None,
) -> Annotated[dict[str, Any]]:
"""Search for news articles related to a given query."""
...
```
### Tool Definition: ``GoogleNews.SearchNewsStories``
```
{
"name": "SearchNewsStories",
"fully_qualified_name": "GoogleNews.SearchNewsStories",
"description": "Search for news articles related to a given query.",
"toolkit": {
"name": "GoogleNews",
"description": "Arcade.dev LLM tools for getting new via Google News",
"version": "2.0.0"
},
"input": {
"parameters": [
{
"name": "keywords",
"required": true,
"description": "Keywords to search for news articles. E.g. 'Apple launches new iPhone'.",
"value_schema": {
"val_type": "string",
"inner_val_type": null,
"enum": null,
},
"inferrable": true
},
{
"name": "country_code",
"required": false,
"description": "2-character country code to search for news articles. E.g. 'us' (United States). Defaults to 'None'.",
"value_schema": {
"val_type": "string",
"inner_val_type": null,
"enum": null,
},
"inferrable": true
},
{
"name": "language_code",
"required": false,
"description": "2-character language code to search for news articles. E.g. 'en' (English). Defaults to 'en'.",
"value_schema": {
"val_type": "string",
"inner_val_type": null,
"enum": null,
},
"inferrable": true
},
{
"name": "limit",
"required": false,
"description": "Maximum number of news articles to return. Defaults to None (returns all results found by the API).",
"value_schema": {
"val_type": "integer",
"inner_val_type": null,
"enum": null,
},
"inferrable": true
}
]
},
"output": {
"description": "News search results with article details.",
"available_modes": [
"value",
"error"
],
"value_schema": {
"val_type": "json"
}
},
"requirements": {
"authorization": null,
"secrets": [
{
"key": "serp_api_key"
}
],
"metadata": null
},
"deprecation_message": null
},
```
## After
### Enhanced Tool: ``GoogleNews.SearchNewsStories``
```python
"""Type definitions for Google News API responses and parameters."""
from typing_extensions import TypedDict
CountryCode = str
LanguageCode = str
class SearchNewsParams(TypedDict):
"""Input parameters for searching news articles."""
keywords: str
"""Search query terms to find relevant news articles \
(e.g., 'Apple launches new iPhone')."""
country_code: CountryCode | None
"""Optional 2-letter country code to filter news by region \
(e.g., 'us' for United States, 'uk' for United Kingdom)."""
language_code: LanguageCode | None
"""Optional 2-letter language code to filter news by language \
(e.g., 'en' for English, 'es' for Spanish)."""
limit: int | None
"""Optional maximum number of news articles to return. \
If not specified, returns all results from the API."""
class SourceInfo(TypedDict, total=False):
"""Information about the news source/publication."""
name: str
"""Name of the publication (e.g., 'CNN', 'BBC News', 'The New York Times')."""
icon: str
"""URL to the source's favicon or logo image."""
authors: list[str]
"""List of author names for the article, if available."""
class NewsResult(TypedDict, total=False):
"""Individual news article from the Google News API response."""
position: int
"""Ranking position of this result in the search results."""
title: str
"""Headline or title of the news article."""
link: str
"""Full URL to the original news article."""
source: SourceInfo
"""Information about the publication source."""
date: str
"""Publication date and time (e.g., '2 hours ago', 'Dec 15, 2023')."""
snippet: str
"""Brief excerpt or summary from the article content."""
thumbnail: str
"""URL to a high-resolution thumbnail image for the article."""
thumbnail_small: str
"""URL to a low-resolution thumbnail image for the article."""
story_token: str
"""Token for accessing full coverage of this news story across multiple sources."""
stories: list["NewsResult"]
"""Related news stories from other sources covering the same topic."""
highlight: dict
"""Additional highlighted information about the story."""
class SearchMetadata(TypedDict, total=False):
"""Metadata about the search request and processing."""
id: str
"""Unique identifier for this search request within SerpApi."""
status: str
"""Current processing status ('Processing', 'Success', or 'Error')."""
json_endpoint: str
"""URL to retrieve the JSON results for this search."""
created_at: str
"""Timestamp when the search request was created."""
processed_at: str
"""Timestamp when the search request was processed."""
google_news_url: str
"""Original Google News URL that would return these results."""
total_time_taken: float
"""Total time in seconds taken to process this search."""
class SearchParameters(TypedDict, total=False):
"""Parameters used for the search request."""
engine: str
"""Search engine used (always 'google_news' for this API)."""
q: str
"""Search query string."""
gl: str
"""Country code used for geographic filtering."""
hl: str
"""Language code used for language filtering."""
topic_token: str
"""Token for accessing specific news topics (e.g., 'World', 'Business', 'Technology')."""
publication_token: str
"""Token for accessing news from specific publishers."""
class MenuLink(TypedDict):
"""Navigation link for news categories or topics."""
title: str
"""Display text for the menu item (e.g., 'Technology', 'Sports', 'Business')."""
topic_token: str
"""Token to access this specific topic or category."""
serpapi_link: str
"""SerpApi URL to search within this topic."""
class TopStoriesLink(TypedDict):
"""Link to top stories section."""
topic_token: str
"""Token to access top stories."""
serpapi_link: str
"""SerpApi URL to retrieve top stories."""
class GoogleNewsResponse(TypedDict, total=False):
"""Complete response from the Google News API."""
search_metadata: SearchMetadata
"""Metadata about the search request and processing."""
search_parameters: SearchParameters
"""Parameters that were used for this search."""
news_results: list[NewsResult]
"""List of news articles matching the search criteria."""
menu_links: list[MenuLink]
"""Navigation links to different news categories and topics."""
top_stories_link: TopStoriesLink
"""Link to access top stories."""
title: str
"""Title of the page or topic being displayed."""
class SimplifiedNewsResult(TypedDict):
"""Simplified news article format for tool output."""
title: str
"""Headline of the news article."""
link: str
"""URL to the full article."""
source: str | None
"""Name of the publication source."""
date: str | None
"""When the article was published."""
snippet: str | None
"""Brief excerpt from the article."""
class SearchNewsOutput(TypedDict):
"""Output format for the search_news_stories tool."""
news_results: list[SimplifiedNewsResult]
"""List of news articles in simplified format."""
@tool(requires_secrets=["SERP_API_KEY"])
async def search_news_stories(
context: ToolContext,
keywords: Annotated[
str,
"Keywords to search for news articles. E.g. 'Apple launches new iPhone'.",
],
country_code: Annotated[
CountryCode | None,
"2-character country code to search for news articles. "
"E.g. 'us' (United States). "
f"Defaults to '{DEFAULT_GOOGLE_NEWS_COUNTRY}'.",
] = None,
language_code: Annotated[
LanguageCode,
"2-character language code to search for news articles. E.g. 'en' (English). "
f"Defaults to '{DEFAULT_GOOGLE_NEWS_LANGUAGE}'.",
] = DEFAULT_GOOGLE_NEWS_LANGUAGE,
limit: Annotated[
int | None,
"Maximum number of news articles to return. Defaults to None "
"(returns all results found by the API).",
] = None,
) -> Annotated[SearchNewsOutput, "News search results with article details."]:
"""Search for news articles related to a given query."""
...
```
### Enhanced Tool Definition: ``GoogleNews.SearchNewsStories``
```json
{
"name": "SearchNewsStories",
"fully_qualified_name": "GoogleNews.SearchNewsStories",
"description": "Search for news articles related to a given query.",
"toolkit": {
"name": "GoogleNews",
"description": "Arcade.dev LLM tools for getting new via Google News",
"version": "2.0.0"
},
"input": {
"parameters": [
{
"name": "keywords",
"required": true,
"description": "Keywords to search for news articles. E.g. 'Apple launches new iPhone'.",
"value_schema": {
"val_type": "string",
"inner_val_type": null,
"enum": null,
"properties": null,
"inner_properties": null,
"description": null
},
"inferrable": true
},
{
"name": "country_code",
"required": false,
"description": "2-character country code to search for news articles. E.g. 'us' (United States). Defaults to 'None'.",
"value_schema": {
"val_type": "string",
"inner_val_type": null,
"enum": null,
"properties": null,
"inner_properties": null,
"description": null
},
"inferrable": true
},
{
"name": "language_code",
"required": false,
"description": "2-character language code to search for news articles. E.g. 'en' (English). Defaults to 'en'.",
"value_schema": {
"val_type": "string",
"inner_val_type": null,
"enum": null,
"properties": null,
"inner_properties": null,
"description": null
},
"inferrable": true
},
{
"name": "limit",
"required": false,
"description": "Maximum number of news articles to return. Defaults to None (returns all results found by the API).",
"value_schema": {
"val_type": "integer",
"inner_val_type": null,
"enum": null,
"properties": null,
"inner_properties": null,
"description": null
},
"inferrable": true
}
]
},
"output": {
"description": "News search results with article details.",
"available_modes": [
"value",
"error"
],
"value_schema": {
"val_type": "json",
"inner_val_type": null,
"enum": null,
"properties": {
"news_results": {
"val_type": "array",
"inner_val_type": "json",
"enum": null,
"properties": null,
"inner_properties": {
"title": {
"val_type": "string",
"inner_val_type": null,
"enum": null,
"properties": null,
"inner_properties": null,
"description": "Headline of the news article."
},
"link": {
"val_type": "string",
"inner_val_type": null,
"enum": null,
"properties": null,
"inner_properties": null,
"description": "URL to the full article."
},
"source": {
"val_type": "string",
"inner_val_type": null,
"enum": null,
"properties": null,
"inner_properties": null,
"description": "Name of the publication source."
},
"date": {
"val_type": "string",
"inner_val_type": null,
"enum": null,
"properties": null,
"inner_properties": null,
"description": "When the article was published."
},
"snippet": {
"val_type": "string",
"inner_val_type": null,
"enum": null,
"properties": null,
"inner_properties": null,
"description": "Brief excerpt from the article."
}
},
"description": "List of news articles in simplified format."
}
},
"inner_properties": null,
"description": null
}
},
"requirements": {
"authorization": null,
"secrets": [
{
"key": "serp_api_key"
}
],
"metadata": null
},
"deprecation_message": null
},
```
---------
Co-authored-by: Eric Gustin <eric@arcade.dev>
### Overview
Major restructuring from monolithic `arcade-ai` package to modular
library architecture with standardized uv-based dependency management.
### New Package Structure
- **`arcade-tdk`** - Lightweight toolkit development kit (core
decorators, auth)
- **`arcade-core`** - Core execution engine and catalog functionality
- **`arcade-serve`** - FastAPI/MCP server components
- **`arcade-ai`** - Meta package that includes CLI functionality.
Optionally include evals via the `evals` extra. Optionally include all
packages via the `all` extra.
### Key Benefits
- **Lighter Dependencies**: Toolkits now depend only on `arcade-tdk` (~2
deps) vs full `arcade-ai` (~30+ deps)
- **Faster Builds**: uv provides 10-100x faster dependency resolution
and installation
- **Better Modularity**: Clear separation of concerns, consumers import
only what they need
- **Standard Tooling**: Eliminates custom poetry scripts, uses standard
Python packaging
### Migration Impact
- All 20 toolkits converted from poetry → uv with `arcade-tdk`
dependencies plus `arcade-ai[evals]` and `arcade-serve` dev
dependencies. When developing locally, devs should install toolkits via
`make install-local`.
- Modern Python 3.10+ type hints throughout
- Standardized build system with hatchling backend
- Enhanced Makefile with robust toolkit management commands
- Removed `arcade dev` CLI command
- Reduce the number of files created by `arcade new` and add an option
to not generate a tests and evals folder.
This foundation enables faster development cycles and cleaner dependency
chains for the growing toolkit ecosystem.
### Todo After this PR is merged
- [ ] Post-merge workflow(s) (release & publish containers, etc)
- [ ] Release order plan. @EricGustin suggests releasing in the
following order:
1. `arcade-core` version 0.1.0
2. `arcade-serve` version 0.1.0 and `arcade-tdk` version 0.1.0
3. `arcade-ai` version 2.0.0
4. Patch release for all toolkits (all changes in toolkits are internal
refactors)
- [ ] [Update docs](https://github.com/ArcadeAI/docs/pull/318)
---------
Co-authored-by: Eric Gustin <eric@arcade.dev>
Co-authored-by: Eric Gustin <34000337+EricGustin@users.noreply.github.com>
Francisco Or Something