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Source code in superme_sdk/services/_content.py 
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class ContentMixin:
    def add_internal_content(
        self,
        input: list[str],
        *,
        extended_content: Optional[str] = None,
        past_instructions: Optional[str] = None,
    ) -> dict:
        """Save notes or knowledge to your personal library.

        Example:
            ```python
            result = client.add_internal_content(
                ["My key insight: distribution beats product."],
                past_instructions="Use this when answering growth questions.",
            )
            learning_id = result["learning_ids"][0]
            ```

        Args:
            input: Text blocks to save.
            extended_content: Optional longer-form content.
            past_instructions: Instructions for how the AI should use this content.

        Returns:
            Dict with success status and learning IDs.
        """
        args: dict[str, Any] = {"input": input}
        if extended_content is not None:
            args["extended_content"] = extended_content
        if past_instructions is not None:
            args["past_instructions"] = past_instructions
        return self._mcp_tool_call("add_internal_content", args)

    def update_internal_content(
        self,
        learning_id: str,
        *,
        user_input: Optional[list[str]] = None,
        extended_content: Optional[str] = None,
        past_instructions: Optional[str] = None,
    ) -> dict:
        """Update an existing note in your library.

        Example:
            ```python
            client.update_internal_content(
                "learning_abc123",
                user_input=["Updated insight: community beats ads at scale."],
            )
            ```

        Args:
            learning_id: The learning ID to update.
            user_input: Replacement note content.
            extended_content: Replacement long-form content.
            past_instructions: Replacement AI usage instructions.

        Returns:
            Dict with update result.
        """
        args: dict[str, Any] = {"learning_id": learning_id}
        if user_input is not None:
            args["user_input"] = user_input
        if extended_content is not None:
            args["extended_content"] = extended_content
        if past_instructions is not None:
            args["past_instructions"] = past_instructions
        return self._mcp_tool_call("update_internal_content", args)

    def add_external_content(
        self,
        urls: list[dict],
        *,
        reference: bool = True,
        instant_recrawl: bool = True,
    ) -> dict:
        """Submit URLs to be crawled and added to your knowledge base.

        Example:
            ```python
            result = client.add_external_content(
                [{"url": "https://myblog.com/post-1"}, {"url": "https://myblog.com/post-2"}]
            )
            print(result["successful"], "URLs added")
            ```

        Args:
            urls: List of URL objects. Each must have a ``"url"`` key.
            reference: Show citations from this content in AI answers.
            instant_recrawl: Crawl immediately vs. queue.

        Returns:
            Dict with counts of successful, existing, and failed URLs.
        """
        return self._mcp_tool_call(
            "add_external_content",
            {"urls": urls, "reference": reference, "instant_recrawl": instant_recrawl},
        )

    def check_uncrawled_urls(self, urls: list[str]) -> dict:
        """Check which URLs are not yet in your knowledge base.

        Example:
            ```python
            result = client.check_uncrawled_urls(["https://myblog.com/post-1"])
            print(result["uncrawled_urls"])
            ```

        Args:
            urls: URLs to check.

        Returns:
            Dict with ``uncrawled_urls`` list and counts.
        """
        return self._mcp_tool_call("check_uncrawled_urls", {"urls": urls})

add_internal_content 

add_internal_content(
    input: list[str],
    *,
    extended_content: Optional[str] = None,
    past_instructions: Optional[str] = None,
) -> dict

Save notes or knowledge to your personal library.

Example 
result = client.add_internal_content(
    ["My key insight: distribution beats product."],
    past_instructions="Use this when answering growth questions.",
)
learning_id = result["learning_ids"][0]

Parameters:

Name Type Description Default
input list[str]

Text blocks to save.

 required
extended_content Optional[str]

Optional longer-form content.

 None
past_instructions Optional[str]

Instructions for how the AI should use this content.

 None

Returns:

Type Description
dict

Dict with success status and learning IDs.
Source code in superme_sdk/services/_content.py 
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def add_internal_content(
    self,
    input: list[str],
    *,
    extended_content: Optional[str] = None,
    past_instructions: Optional[str] = None,
) -> dict:
    """Save notes or knowledge to your personal library.

    Example:
        ```python
        result = client.add_internal_content(
            ["My key insight: distribution beats product."],
            past_instructions="Use this when answering growth questions.",
        )
        learning_id = result["learning_ids"][0]
        ```

    Args:
        input: Text blocks to save.
        extended_content: Optional longer-form content.
        past_instructions: Instructions for how the AI should use this content.

    Returns:
        Dict with success status and learning IDs.
    """
    args: dict[str, Any] = {"input": input}
    if extended_content is not None:
        args["extended_content"] = extended_content
    if past_instructions is not None:
        args["past_instructions"] = past_instructions
    return self._mcp_tool_call("add_internal_content", args)

update_internal_content 

update_internal_content(
    learning_id: str,
    *,
    user_input: Optional[list[str]] = None,
    extended_content: Optional[str] = None,
    past_instructions: Optional[str] = None,
) -> dict

Update an existing note in your library.

Example 
client.update_internal_content(
    "learning_abc123",
    user_input=["Updated insight: community beats ads at scale."],
)

Parameters:

Name Type Description Default
learning_id str

The learning ID to update.

 required
user_input Optional[list[str]]

Replacement note content.

 None
extended_content Optional[str]

Replacement long-form content.

 None
past_instructions Optional[str]

Replacement AI usage instructions.

 None

Returns:

Type Description
dict

Dict with update result.
Source code in superme_sdk/services/_content.py 
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def update_internal_content(
    self,
    learning_id: str,
    *,
    user_input: Optional[list[str]] = None,
    extended_content: Optional[str] = None,
    past_instructions: Optional[str] = None,
) -> dict:
    """Update an existing note in your library.

    Example:
        ```python
        client.update_internal_content(
            "learning_abc123",
            user_input=["Updated insight: community beats ads at scale."],
        )
        ```

    Args:
        learning_id: The learning ID to update.
        user_input: Replacement note content.
        extended_content: Replacement long-form content.
        past_instructions: Replacement AI usage instructions.

    Returns:
        Dict with update result.
    """
    args: dict[str, Any] = {"learning_id": learning_id}
    if user_input is not None:
        args["user_input"] = user_input
    if extended_content is not None:
        args["extended_content"] = extended_content
    if past_instructions is not None:
        args["past_instructions"] = past_instructions
    return self._mcp_tool_call("update_internal_content", args)

add_external_content 

add_external_content(
    urls: list[dict],
    *,
    reference: bool = True,
    instant_recrawl: bool = True,
) -> dict

Submit URLs to be crawled and added to your knowledge base.

Example 
result = client.add_external_content(
    [{"url": "https://myblog.com/post-1"}, {"url": "https://myblog.com/post-2"}]
)
print(result["successful"], "URLs added")

Parameters:

Name Type Description Default
urls list[dict]

List of URL objects. Each must have a "url" key.

 required
reference bool

Show citations from this content in AI answers.

 True
instant_recrawl bool

Crawl immediately vs. queue.

 True

Returns:

Type Description
dict

Dict with counts of successful, existing, and failed URLs.
Source code in superme_sdk/services/_content.py 
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def add_external_content(
    self,
    urls: list[dict],
    *,
    reference: bool = True,
    instant_recrawl: bool = True,
) -> dict:
    """Submit URLs to be crawled and added to your knowledge base.

    Example:
        ```python
        result = client.add_external_content(
            [{"url": "https://myblog.com/post-1"}, {"url": "https://myblog.com/post-2"}]
        )
        print(result["successful"], "URLs added")
        ```

    Args:
        urls: List of URL objects. Each must have a ``"url"`` key.
        reference: Show citations from this content in AI answers.
        instant_recrawl: Crawl immediately vs. queue.

    Returns:
        Dict with counts of successful, existing, and failed URLs.
    """
    return self._mcp_tool_call(
        "add_external_content",
        {"urls": urls, "reference": reference, "instant_recrawl": instant_recrawl},
    )

check_uncrawled_urls 

check_uncrawled_urls(urls: list[str]) -> dict

Check which URLs are not yet in your knowledge base.

Example 
result = client.check_uncrawled_urls(["https://myblog.com/post-1"])
print(result["uncrawled_urls"])

Parameters:

Name Type Description Default
urls list[str]

URLs to check.

 required

Returns:

Type Description
dict

Dict with uncrawled_urls list and counts.
Source code in superme_sdk/services/_content.py 
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def check_uncrawled_urls(self, urls: list[str]) -> dict:
    """Check which URLs are not yet in your knowledge base.

    Example:
        ```python
        result = client.check_uncrawled_urls(["https://myblog.com/post-1"])
        print(result["uncrawled_urls"])
        ```

    Args:
        urls: URLs to check.

    Returns:
        Dict with ``uncrawled_urls`` list and counts.
    """
    return self._mcp_tool_call("check_uncrawled_urls", {"urls": urls})