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complete_node

Mark a node as completed in Resurgo-MCP to track progress and manage knowledge capture workflows.

Instructions

Mark a node as done

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateYes

Implementation Reference

  • src/nodes.ts:169-199 (registration)
    Registers the MCP tool 'complete_node' including input schema (nodeId: uuid), description, and handler function that calls apiClient.completeNode and formats the response.
    server.tool(
      'complete_node',
      'Mark a node as done',
      {
        state: z.object({
          nodeId: z
            .string()
            .uuid()
            .describe('The ID of the node to mark as done'),
        }),
      },
      async ({ state }) => {
        const result = await apiClient.completeNode(state);
    
        if (result.error) {
          return {
            content: [{ type: 'text', text: result.error }],
            isError: true,
          };
        }
    
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify(result.data, null, 2),
            },
          ],
        };
      },
    );
  • Handler function for 'complete_node' tool: invokes apiClient.completeNode with state, handles error or success by returning text content.
    async ({ state }) => {
      const result = await apiClient.completeNode(state);
    
      if (result.error) {
        return {
          content: [{ type: 'text', text: result.error }],
          isError: true,
        };
      }
    
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(result.data, null, 2),
          },
        ],
      };
    },
  • Zod input schema for the tool: requires nodeId as UUID string.
    state: z.object({
      nodeId: z
        .string()
        .uuid()
        .describe('The ID of the node to mark as done'),
    }),
  • API client helper method: sends POST request to backend /mcp/complete-node endpoint with nodeId.
    async completeNode(params: {
      nodeId: string;
    }): Promise<ApiResponse<any>> {
      return this.request('/mcp/complete-node', {
        method: 'POST',
        body: JSON.stringify(params),
      });
    }
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 done') but doesn't disclose behavioral traits like whether this is a mutation (implied by 'mark'), what permissions are required, if changes are reversible, side effects (e.g., triggers notifications), or response format. For a mutation tool with zero annotation coverage, this is a significant gap.

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 waste. It's front-loaded with the core action and appropriately sized for a simple tool. Every word earns its place, making it easy to parse quickly.

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

Completeness2/5

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

Given the tool's complexity (mutation with 1 parameter, nested object, no annotations, no output schema), the description is incomplete. It lacks details on behavior, usage context, parameter semantics, and expected outcomes. For a tool that modifies state, this minimal description leaves critical gaps for an AI agent to operate effectively.

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

Parameters4/5

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

The description has 0 parameters explicitly mentioned, but the input schema has 1 parameter (nodeId) with 0% schema description coverage. The description implies a 'node' parameter through context, but doesn't add details beyond what's inferred. With only one parameter and no schema descriptions, the baseline is high, but the description doesn't fully compensate for the coverage gap by explaining parameter meaning or constraints.

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 'Mark a node as done' clearly states the action (mark) and resource (node) with a specific verb and object. It distinguishes from siblings like 'get_due_items' (read) or 'snooze_node' (delay), but doesn't explicitly differentiate beyond the basic action. The purpose is unambiguous but could be more specific about what 'done' means in this context.

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., node must exist, be in a certain state), exclusions (e.g., cannot mark already-done nodes), or relationships to sibling tools like 'snooze_node' for deferring completion. Usage is implied only by the action name.

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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