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get_call_details

Retrieve comprehensive details for specific Gong.io sales calls, including participants, topics, action items, and trackers, to analyze conversation data and extract insights.

Instructions

Get detailed information about specific calls including participants, topics, trackers, action items, and more.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
callIdsYesArray of call IDs to retrieve details for

Implementation Reference

  • MCP CallToolRequestSchema handler for 'get_call_details': validates non-empty callIds array from input arguments, invokes GongClient.getCallDetails, formats result as JSON text content.
    case "get_call_details": {
      const callIds = args?.callIds as string[];
      if (!callIds?.length) {
        throw new Error("callIds is required and must be a non-empty array");
      }
      const result = await gong.getCallDetails(callIds);
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(result, null, 2),
          },
        ],
      };
    }
  • Input schema definition for the 'get_call_details' tool: requires an object with 'callIds' property as non-empty array of strings.
    inputSchema: {
      type: "object",
      properties: {
        callIds: {
          type: "array",
          items: { type: "string" },
          description: "Array of call IDs to retrieve details for",
        },
      },
      required: ["callIds"],
    },
  • src/index.ts:69-84 (registration)
    Registration of 'get_call_details' tool in ListToolsRequestSchema response: includes name, description, and input schema.
    {
      name: "get_call_details",
      description:
        "Get detailed information about specific calls including participants, topics, trackers, action items, and more.",
      inputSchema: {
        type: "object",
        properties: {
          callIds: {
            type: "array",
            items: { type: "string" },
            description: "Array of call IDs to retrieve details for",
          },
        },
        required: ["callIds"],
      },
    },
  • GongClient helper method: sends POST request to Gong API /v2/calls/extensive with filter by callIds to fetch detailed call information.
    async getCallDetails(callIds: string[]): Promise<CallDetailsResponse> {
    	const body = {
    		filter: {
    			callIds,
    		},
    	};
    	return this.request<CallDetailsResponse>('POST', '/calls/extensive', body);
    }
  • TypeScript interface defining the structure of the response from Gong API for call details.
    export interface CallDetailsResponse {
    	requestId: string;
    	records: {
    		totalRecords: number;
    		currentPageSize: number;
    		currentPageNumber: number;
    	};
    	calls: CallDetails[];
    }
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. It states the tool retrieves detailed information, which implies a read-only operation, but doesn't disclose behavioral traits such as authentication requirements, rate limits, error handling, or whether it supports batch processing for multiple call IDs. This leaves significant gaps for a tool with no annotation coverage.

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 front-loads the purpose and lists key data elements. It avoids redundancy and wastes no words, though it could be slightly more structured by separating usage context from data details.

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 no annotations and no output schema, the description adequately covers the purpose and data scope but lacks completeness for behavioral transparency and output expectations. It doesn't explain what 'detailed information' includes beyond a few examples, leaving the agent to infer the return structure. This is minimal viable for a read tool but has clear gaps.

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 schema description coverage is 100%, with the parameter 'callIds' clearly documented in the schema. The description adds no additional meaning beyond implying that details are retrieved for 'specific calls', which aligns with the schema but doesn't provide extra context like ID format or constraints. Baseline 3 is appropriate as the schema does the heavy lifting.

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 ('Get') and resource ('detailed information about specific calls'), specifying what data is retrieved (participants, topics, trackers, action items). It distinguishes from siblings like 'list_calls' (which likely lists metadata) and 'get_transcripts' (which focuses on transcripts), though it doesn't explicitly name alternatives.

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

Usage Guidelines3/5

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

The description implies usage when detailed call information is needed, but provides no explicit guidance on when to use this tool versus alternatives like 'search_calls' or 'list_calls'. It mentions 'specific calls', hinting at use with known call IDs, but lacks clear exclusions or prerequisites.

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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