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analyze_call

Analyze sales call transcripts to identify sentiment, objections, commitments, next steps, and calculate deal health scores for actionable insights.

Instructions

Full sales call analysis — sentiment, objections, commitments, next steps, deal health score. Cost: $0.025 USDC. Service: callsight.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
transcriptYes
call_typeNosales
productNo

Implementation Reference

  • The request handler for 'CallToolRequestSchema' which handles dynamic tool execution. It resolves tool names from a fetched registry and calls the 'callTool' helper.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      const { name, arguments: args } = request.params;
    
      let registry: Registry;
      try {
        registry = await fetchRegistry();
      } catch (error) {
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({ error: "Failed to fetch tool registry", detail: String(error) }),
            },
          ],
        };
      }
    
      const tool = registry.tools.find((t) => t.name === name);
      if (!tool) {
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({
                error: `Tool '${name}' not found`,
                available_tools: registry.tools.map((t) => t.name),
              }),
            },
          ],
        };
      }
    
      try {
        const result = await callTool(tool, args as Record<string, unknown>);
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(result, null, 2),
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify({
                error: "Tool call failed",
                tool: name,
                service: tool.service,
                detail: String(error),
              }),
            },
          ],
        };
      }
    });
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. It mentions cost and service provider, which adds useful context about external API usage and potential monetary implications. However, it lacks critical details: whether it's idempotent, rate limits, error handling, or authentication needs. For a paid analysis tool, this is insufficient.

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 concise and front-loaded, with the core purpose stated first. The two sentences earn their place: one defines analysis outputs, the other provides cost/service info. No redundant or verbose phrasing, though it could be more structured for readability.

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 no annotations, 0% schema coverage, no output schema, and 3 parameters, the description is incomplete. It covers the analysis purpose and cost but misses parameter explanations, behavioral traits (e.g., idempotency, errors), and output format. For a paid tool with multiple inputs, this leaves significant gaps for agent understanding.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'sales call analysis' which implies the 'transcript' parameter, but doesn't explain 'call_type' or 'product' at all. The description adds minimal value beyond what's inferable from parameter names, failing to clarify semantics for 2 of 3 parameters.

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: 'Full sales call analysis — sentiment, objections, commitments, next steps, deal health score.' It specifies the verb 'analyze' and resource 'sales call' with detailed outputs. However, it doesn't explicitly differentiate from sibling tools like 'detect_fallacies' or 'indic_sentiment' that might also analyze content, leaving room for ambiguity.

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 minimal usage guidance. It mentions cost and service provider ('Cost: $0.025 USDC. Service: callsight.'), which hints at external API usage, but offers no explicit when-to-use rules, alternatives, or prerequisites. Without comparing to siblings like 'indic_sentiment', agents may struggle to choose appropriately.

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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