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carlosazaustre

Activity Reporting MCP Server

submit_googler_interaction

Submit interactions with Googlers by logging activity drafts, including details like format, type, date, and metrics, to ensure accurate reporting on the MCP server.

Instructions

Submit an interaction with Googlers activity draft

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
activityDateYesInteraction Date (YYYY-MM-DD format)
additionalInfoNoAdditional information (optional)
additionalLinksNoAdditional links (optional)
descriptionYesDescription
formatYesFormat
interactionTypeYesInteraction Type
metricsYes
privateNoDo you want to make this activity private? (optional)
tagsNoTags (optional)
titleYesTitle

Implementation Reference

  • Handler case for the 'submit_googler_interaction' tool. Casts input arguments to GooglerInteractionDraft type and invokes the shared submitActivityDraft method with the specific endpoint 'interaction-with-googlers'.
    case "submit_googler_interaction":
      return await this.submitActivityDraft(
        "interaction-with-googlers",
        args as unknown as GooglerInteractionDraft,
      );
  • TypeScript interface defining the structure of input parameters for the submit_googler_interaction tool, extending ActivityDraftBase.
    export interface GooglerInteractionDraft extends ActivityDraftBase {
      /** Format of the interaction */
      format: InteractionFormat;
      /** Type of interaction with Google personnel */
      interactionType: InteractionType;
      /** Metrics related to time investment */
      metrics: {
        /** Time spent in the interaction (in minutes) */
        timeSpent: number;
      };
      /** Optional additional links related to the interaction */
      additionalLinks?: string;
    }
  • src/server.ts:424-490 (registration)
    MCP tool registration including name, description, and detailed inputSchema for validation in the ListTools response.
    {
      name: "submit_googler_interaction",
      description: "Submit an interaction with Googlers activity draft",
      inputSchema: {
        type: "object",
        properties: {
          title: {
            type: "string",
            description: "Title",
            minLength: 3,
            maxLength: 200,
          },
          description: {
            type: "string",
            description: "Description",
            maxLength: 2000,
          },
          activityDate: {
            type: "string",
            pattern: "^\\d{4}-\\d{2}-\\d{2}$",
            description: "Interaction Date (YYYY-MM-DD format)",
          },
          format: {
            type: "string",
            enum: Object.values(InteractionFormat),
            description: "Format",
          },
          interactionType: {
            type: "string",
            enum: Object.values(InteractionType),
            description: "Interaction Type",
          },
          tags: {
            type: "array",
            items: { type: "string" },
            description: "Tags (optional)",
            minItems: 0,
          },
          metrics: {
            type: "object",
            properties: {
              timeSpent: {
                type: "integer",
                minimum: 1,
                description: "Time spent (in minutes)",
              },
            },
            required: ["timeSpent"],
          },
          additionalInfo: {
            type: "string",
            maxLength: 2000,
            description: "Additional information (optional)",
          },
          additionalLinks: {
            type: "string",
            maxLength: 2000,
            description: "Additional links (optional)",
          },
          private: {
            type: "boolean",
            description: "Do you want to make this activity private? (optional)",
          },
        },
        required: ["title", "description", "activityDate", "format", "interactionType", "metrics"],
      },
    },
  • Shared helper function that executes the core logic: API POST to /activity-drafts/{endpoint} with the draft data, handles auth, errors, rate limits, and returns formatted content response.
    private async submitActivityDraft(
      endpoint: string,
      data:
        | ContentCreationDraft
        | PublicSpeakingDraft
        | WorkshopDraft
        | MentoringDraft
        | ProductFeedbackDraft
        | GooglerInteractionDraft
        | StoryDraft,
    ): Promise<{
      content: Array<{
        type: string;
        text: string;
      }>;
    }> {
      const url = `${this.baseUrl}/activity-drafts/${endpoint}`;
    
      try {
        const response = await fetch(url, {
          method: "POST",
          headers: {
            "Content-Type": "application/json",
            Authorization: `Bearer ${this.accessToken}`,
          },
          body: JSON.stringify(data),
        });
    
        if (!response.ok) {
          const errorText = await response.text();
          let errorMessage = `GDE API error (${response.status})`;
    
          if (response.status === 401) {
            errorMessage = "❌ GDE authentication failed. Your ADVOCU_ACCESS_TOKEN may be expired or invalid.\n\nPlease check your Advocu access token configuration.";
          } else if (response.status === 400) {
            errorMessage = `❌ GDE API rejected the request:\n\n${errorText}\n\nPlease check:\n- All required fields are present\n- Field values match expected formats\n- Tags are valid\n- Date format is correct (YYYY-MM-DD)`;
          } else if (response.status === 429) {
            errorMessage = "⏱️ GDE API rate limit exceeded (30 requests/minute). Please wait and try again.";
          } else {
            errorMessage = `❌ GDE API error (${response.status}):\n\n${errorText}`;
          }
    
          // Return error as content instead of throwing
          return {
            content: [
              {
                type: "text",
                text: errorMessage,
              },
            ],
          };
        }
    
        const result = (await response.json()) as Record<string, unknown>;
    
        return {
          content: [
            {
              type: "text",
              text: `✅ GDE Activity draft submitted successfully!\n\nEndpoint: ${endpoint}\nStatus: ${response.status}\nResponse: ${JSON.stringify(result, null, 2)}`,
            },
          ],
        };
      } catch (error) {
        if (error instanceof McpError) {
          throw error;
        }
        const errorMsg = this.getErrorMessage(error);
        throw new McpError(
          ErrorCode.InternalError,
          `❌ Failed to submit GDE activity:\n\n${errorMsg}\n\nEndpoint: ${endpoint}`
        );
      }
    }
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. It states 'Submit an interaction with Googlers activity draft', which implies a write operation (submission), but it doesn't disclose critical behavioral traits such as permissions required, whether this creates or updates data, potential side effects, or response format. 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.

Conciseness4/5

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

The description is a single, efficient sentence that directly states the tool's action. It's appropriately sized and front-loaded with the key verb 'Submit'. There's no unnecessary elaboration, making it concise, though it could be slightly more informative without losing brevity.

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 complexity (10 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It doesn't explain the tool's role among siblings, behavioral implications of submission, or what happens after invocation. For a mutation tool with rich input schema but no output or annotations, more context is needed to guide the agent effectively.

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 high at 90%, meaning the schema already documents most parameters well (e.g., 'activityDate' with format, 'format' with enum values). The description adds no additional parameter semantics beyond what's in the schema. With high coverage, the baseline score is 3, as the description doesn't compensate but also doesn't need to heavily given the schema's detail.

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

Purpose3/5

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

The description 'Submit an interaction with Googlers activity draft' states a verb ('Submit') and resource ('interaction with Googlers activity draft'), but it's somewhat vague. It doesn't clearly specify what 'Googlers activity draft' refers to or how this differs from sibling tools like 'submit_product_feedback' or 'submit_mentoring'. The purpose is understandable but lacks precision and sibling differentiation.

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. With sibling tools like 'submit_product_feedback' and 'submit_mentoring' available, there's no indication of what specific scenarios warrant this tool over others. Usage is implied only by the tool name and description, with no explicit context or exclusions provided.

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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