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workflowy_get_node

Retrieve a specific WorkFlowy node by its ID to access outline content or task details within the hierarchical structure.

Instructions

Retrieve a specific WorkFlowy node by ID

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

  • The primary handler function decorated with @mcp.tool(name="workflowy_get_node"), implementing the tool logic: acquires client, handles rate limiting, calls client.get_node(), and returns the node.
    @mcp.tool(name="workflowy_get_node", description="Retrieve a specific WorkFlowy node by ID")
    async def get_node(node_id: str) -> WorkFlowyNode:
        """Retrieve a specific WorkFlowy node.
    
        Args:
            node_id: The ID of the node to retrieve
    
        Returns:
            The requested WorkFlowy node
        """
        client = get_client()
    
        if _rate_limiter:
            await _rate_limiter.acquire()
    
        try:
            node = await client.get_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
  • Pydantic model WorkFlowyNode defining the structure and validation for the tool's return type.
    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()
  • Helper function that provides the shared WorkFlowyClient instance used in the tool handler.
    def get_client() -> WorkFlowyClient:
        """Get the global WorkFlowy client instance."""
        global _client
        if _client is None:
            raise RuntimeError("WorkFlowy client not initialized. Server not started properly.")
        return _client
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Retrieve' implies a read-only operation, it doesn't specify whether this requires authentication, rate limits, error conditions (e.g., invalid node IDs), or what happens if the node doesn't exist. The description lacks essential context for safe and effective use.

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, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place in conveying the essential purpose.

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 low complexity (single parameter) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and incomplete parameter semantics, it leaves gaps in behavioral and usage context that could hinder effective tool selection.

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 mentions the parameter ('by ID'), but with 0% schema description coverage, it doesn't add meaningful semantics beyond what the schema already indicates (a required string 'node_id'). It doesn't explain the ID format, source, or constraints, leaving significant gaps in parameter understanding.

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 verb ('Retrieve') and resource ('a specific WorkFlowy node by ID'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'workflowy_list_nodes' (which retrieves multiple nodes) or 'workflowy_update_node' (which modifies rather than fetches).

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., needing a valid node ID), contrast it with 'workflowy_list_nodes' for bulk retrieval, or indicate scenarios where fetching a single node is preferred over listing all nodes.

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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