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workflowy_uncomplete_node

Mark a WorkFlowy node as not completed to reopen tasks or reset progress. Use this tool to manage task status changes in your outlines.

Instructions

Mark a WorkFlowy node as not completed

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
node_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
chNoChild nodes
cpNoCompletion status (for tests)
idYesUnique identifier for the node
dataNoNode data including layoutMode
nameNoText content of the node
noteNoNote content attached to the node
parentIdNoParent node ID
priorityNoSort order
createdAtNoCreation timestamp (Unix timestamp)
modifiedAtNoLast modification timestamp
completedAtNoCompletion timestamp (null if not completed)

Implementation Reference

  • FastMCP handler function for the workflowy_uncomplete_node tool, including rate limiting, client delegation, and error handling.
    @mcp.tool(name="workflowy_uncomplete_node", description="Mark a WorkFlowy node as not completed")
    async def uncomplete_node(node_id: str) -> WorkFlowyNode:
        """Mark a WorkFlowy node as not completed.
    
        Args:
            node_id: The ID of the node to uncomplete
    
        Returns:
            The updated WorkFlowy node
        """
        client = get_client()
    
        if _rate_limiter:
            await _rate_limiter.acquire()
    
        try:
            node = await client.uncomplete_node(node_id)
            if _rate_limiter:
                _rate_limiter.on_success()
            return node
        except Exception as e:
            if _rate_limiter and hasattr(e, "__class__") and e.__class__.__name__ == "RateLimitError":
                _rate_limiter.on_rate_limit(getattr(e, "retry_after", None))
            raise
  • Core implementation in WorkFlowyClient that performs the HTTP POST to the uncomplete endpoint and handles response parsing and errors.
    async def uncomplete_node(self, node_id: str) -> WorkFlowyNode:
        """Mark a node as not completed."""
        try:
            response = await self.client.post(f"/nodes/{node_id}/uncomplete")
            data = await self._handle_response(response)
            # API returns the full node object
            return WorkFlowyNode(**data)
        except httpx.TimeoutException as err:
            raise TimeoutError("uncomplete_node") from err
        except httpx.NetworkError as e:
            raise NetworkError(f"Network error: {str(e)}") from e
  • FastMCP decorator registering the workflowy_uncomplete_node tool.
    @mcp.tool(name="workflowy_uncomplete_node", description="Mark a WorkFlowy node as not completed")
  • Pydantic model defining the output schema (WorkFlowyNode) returned by the tool.
    class WorkFlowyNode(BaseModel):
        """Represents a single node in the WorkFlowy outline hierarchy."""
    
        # API fields (what the API actually returns)
        id: str = Field(..., description="Unique identifier for the node")
        name: str | None = Field(
            None, validation_alias=AliasChoices("name", "nm"), description="Text content of the node"
        )
        note: str | None = Field(
            None,
            validation_alias=AliasChoices("note", "no"),
            description="Note content attached to the node",
        )
        priority: int | None = Field(None, description="Sort order")
        data: dict[str, Any] | None = Field(None, description="Node data including layoutMode")
        createdAt: int | None = Field(
            None,
            validation_alias=AliasChoices("createdAt", "created"),
            description="Creation timestamp (Unix timestamp)",
        )
        modifiedAt: int | None = Field(
            None,
            validation_alias=AliasChoices("modifiedAt", "modified"),
            description="Last modification timestamp",
        )
        completedAt: int | None = Field(
            None, description="Completion timestamp (null if not completed)"
        )
    
        # Nested structure fields
        children: list["WorkFlowyNode"] | None = Field(None, alias="ch", description="Child nodes")
        parent_id: str | None = Field(None, alias="parentId", description="Parent node ID")
    
        # Handle 'cp' field for backward compatibility - we'll compute from completedAt
        completed_flag: bool | None = Field(
            None, alias="cp", description="Completion status (for tests)"
        )
    
        @property
        def layoutMode(self) -> str | None:
            """Extract layoutMode from data field."""
            if self.data and isinstance(self.data, dict):
                return self.data.get("layoutMode")
            return None
    
        # Backward compatibility aliases for tests
        @property
        def nm(self) -> str | None:
            """Backward compatibility for name field."""
            return self.name
    
        @property
        def no(self) -> str | None:
            """Backward compatibility for note field."""
            return self.note
    
        @property
        def cp(self) -> bool:
            """Backward compatibility for completed status."""
            # Use completed_flag if it was set (from tests), otherwise check completedAt
            if self.completed_flag is not None:
                return self.completed_flag
            return self.completedAt is not None
    
        @property
        def ch(self) -> list["WorkFlowyNode"] | None:
            """Backward compatibility for children field."""
            return self.children
    
        @property
        def created(self) -> int:
            """Backward compatibility for created timestamp."""
            return self.createdAt or 0
    
        @property
        def modified(self) -> int:
            """Backward compatibility for modified timestamp."""
            return self.modifiedAt or 0
    
        @field_validator("id")
        @classmethod
        def validate_id(cls, v: str) -> str:
            """Ensure ID is non-empty."""
            if not v or not v.strip():
                raise ValueError("Node ID must be non-empty")
            return v
    
        @field_validator("createdAt", "modifiedAt", "completedAt")
        @classmethod
        def validate_timestamp(cls, v: int | None) -> int | None:
            """Ensure timestamps are positive."""
            if v is not None and v <= 0:
                raise ValueError("Timestamp must be positive")
            return v
    
        def model_dump(self, **kwargs: Any) -> dict[str, Any]:
            """Custom serialization to include backward compatibility fields."""
            data: dict[str, Any] = super().model_dump(**kwargs)
    
            # Add backward compatibility fields for tests
            data["nm"] = self.name
            data["no"] = self.note
            data["cp"] = self.cp
            data["ch"] = self.children
            data["created"] = self.createdAt or 0
            data["modified"] = self.modifiedAt or 0
    
            return data
    
        class Config:
            """Pydantic model configuration."""
    
            populate_by_name = True  # Allow both field names and aliases
            json_schema_extra = {
                "example": {
                    "id": "node-123",
                    "name": "Example Node",
                    "note": "This is a note",
                    "priority": 1,
                    "layoutMode": "bullets",
                    "createdAt": 1704067200,
                    "modifiedAt": 1704067200,
                    "completedAt": None,
                    "children": [],
                }
            }
    
    
    # Enable forward references for recursive model
    WorkFlowyNode.model_rebuild()
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states the action ('Mark as not completed') which implies a mutation, but doesn't disclose behavioral traits like whether this requires authentication, what happens if the node is already uncompleted, error conditions, or side effects. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with zero waste. It's appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration. Every word earns its place in conveying the essential action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (a mutation operation with one parameter) and the presence of an output schema (which likely covers return values), the description is minimally adequate. However, with no annotations and incomplete parameter documentation, it leaves gaps in understanding behavioral aspects and parameter usage. It meets the minimum viable threshold but lacks depth for safe and effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds no parameter semantics beyond what the input schema provides. With 0% schema description coverage and 1 parameter (node_id), the description doesn't explain what node_id represents, its format, or how to obtain it. However, since there's only one parameter and the tool name implies its purpose, the baseline is 3, but it doesn't compensate for the lack of schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Mark as not completed') and the resource ('a WorkFlowy node'), making the purpose immediately understandable. It distinguishes from sibling 'workflowy_complete_node' by specifying the opposite operation. However, it doesn't explicitly mention the tool name 'uncomplete' in the description, which would make it perfect.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., the node must exist and be currently completed), nor does it differentiate from similar tools like 'workflowy_update_node' which might also handle completion status. There's no explicit when/when-not usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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