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mako10k

MCP-Confirm

by mako10k

verify_understanding

Confirm AI correctly understood user requirements before proceeding by verifying key points and next steps.

Instructions

Verify that the AI correctly understood the user's requirements before proceeding

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
understandingYesAI's understanding of the user's request
key_pointsNoKey points that the AI wants to confirm
next_stepsNoWhat the AI plans to do next if understanding is correct

Implementation Reference

  • The handler function that executes the verify_understanding tool. It constructs a message summarizing the AI's understanding, key points, and next steps, then elicits user feedback via sendElicitationRequest, and returns the user's response.
    private async handleVerifyUnderstanding(args: Record<string, unknown>) {
      const understanding =
        typeof args.understanding === "string"
          ? args.understanding
          : "Unknown understanding";
      const key_points = Array.isArray(args.key_points)
        ? args.key_points
        : undefined;
      const next_steps =
        typeof args.next_steps === "string" ? args.next_steps : undefined;
    
      let message = `Please verify my understanding:\n\n**What I understood**: ${understanding}`;
    
      if (key_points && key_points.length > 0) {
        message += `\n\n**Key points to confirm**:\n${key_points.map((point: unknown, i: number) => `${i + 1}. ${String(point)}`).join("\n")}`;
      }
    
      if (next_steps) {
        message += `\n\n**What I plan to do next**: ${next_steps}`;
      }
    
      const elicitationParams: ElicitationParams = {
        message,
        requestedSchema: {
          type: "object",
          properties: {
            understanding_correct: {
              type: "boolean",
              title: "Understanding Correct",
              description: "Is my understanding correct?",
            },
            corrections: {
              type: "string",
              title: "Corrections",
              description: "What should I correct or clarify?",
            },
            proceed: {
              type: "boolean",
              title: "Proceed",
              description: "Should I proceed with the planned next steps?",
            },
          },
          required: ["understanding_correct"],
        },
      };
    
      try {
        const response = await this.sendElicitationRequest(elicitationParams);
    
        if (response.action === "accept") {
          return {
            content: [
              {
                type: "text",
                text: `Understanding verification result:\n${JSON.stringify(response.content, null, 2)}`,
              },
            ],
          };
        } else {
          return {
            content: [
              {
                type: "text",
                text: `User ${response.action}ed the understanding verification.`,
              },
            ],
          };
        }
      } catch (error) {
        return this.createErrorResponse(
          `Understanding verification failed: ${error instanceof Error ? error.message : String(error)}`
        );
      }
  • Defines the Tool schema for verify_understanding, including name, description, and inputSchema specifying the expected parameters: understanding (required), key_points, and next_steps.
    private createVerifyUnderstandingTool(): Tool {
      return {
        name: "verify_understanding",
        description:
          "Verify that the AI correctly understood the user's requirements before proceeding",
        inputSchema: {
          type: "object",
          properties: {
            understanding: {
              type: "string",
              description: "AI's understanding of the user's request",
            },
            key_points: {
              type: "array",
              items: {
                type: "string",
              },
              description: "Key points that the AI wants to confirm",
            },
            next_steps: {
              type: "string",
              description:
                "What the AI plans to do next if understanding is correct",
            },
          },
          required: ["understanding"],
        },
      };
    }
  • src/index.ts:524-525 (registration)
    Switch case in executeToolCall method that routes calls to the verify_understanding tool to its handler function.
    case "verify_understanding":
      return await this.handleVerifyUnderstanding(args);
  • src/index.ts:236-236 (registration)
    The verify_understanding tool is registered by including its creator in the getToolDefinitions() return array, which is used by the list tools handler.
    this.createVerifyUnderstandingTool(),
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While it indicates this is a verification step, it doesn't describe what happens after verification (e.g., does it return confirmation, trigger next steps, or require user response?), nor does it mention any constraints like rate limits or permission requirements for a tool that interacts with user understanding.

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 that directly states the tool's purpose with zero wasted words. It's appropriately sized for a tool with clear parameters and no complex behavioral nuances needing explanation.

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?

For a tool with 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., confirmation object, user response, or next step trigger), nor does it address behavioral aspects like whether this blocks execution or how verification failures are handled, leaving critical gaps for agent understanding.

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?

Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds no additional meaning about parameters beyond what's in the schema, meeting the baseline expectation but not providing extra value like explaining how parameters interact or typical usage patterns.

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 tool's purpose as verifying AI understanding of user requirements before proceeding, which is a specific verb-action combination. However, it doesn't differentiate from sibling tools like 'clarify_intent' or 'confirm_action' that might serve similar verification purposes, preventing a perfect score.

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 like 'clarify_intent' or 'confirm_action'. It mentions 'before proceeding' which gives some temporal context, but offers no explicit when/when-not rules or comparison to sibling tools, leaving significant ambiguity.

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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