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yantrix-ai

@praveen030686/data-apis-mcp

Get AI Stock Report

finance_ai_report
Read-onlyIdempotent

Generate AI-powered stock analysis reports with price action, fundamentals, competitive positioning, and investment outlook using Claude AI.

Instructions

Get Claude AI-powered stock analysis including price action, fundamentals, competitive position, and investment outlook. Costs $0.25 USDC per request via x402 on Base.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesStock ticker (e.g., AAPL, MSFT, GOOGL)

Implementation Reference

  • Handler function for the finance_ai_report tool that fetches the AI report from the finance API.
    async ({ symbol }) => {
      const data = await apiFetch(`${FINANCE_API}/api/v1/market/ai-report/${symbol.toUpperCase()}`);
      return { content: [{ type: "text", text: JSON.stringify(data, null, 2) }] };
  • src/index.ts:247-257 (registration)
    Registration of the finance_ai_report tool with its metadata and input schema.
    server.registerTool(
      "finance_ai_report",
      {
        title: "Get AI Stock Report",
        description: `Get Claude AI-powered stock analysis including price action, fundamentals, competitive position, and investment outlook.
    Costs $0.25 USDC per request via x402 on Base.`,
        inputSchema: {
          symbol: z.string().min(1).max(10).describe("Stock ticker (e.g., AAPL, MSFT, GOOGL)"),
        },
        annotations: { readOnlyHint: true, destructiveHint: false, idempotentHint: true, openWorldHint: true },
      },
Behavior4/5

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

Annotations already cover read-only, open-world, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations: it discloses the cost ($0.25 USDC per request) and payment method (via x402 on Base), which are critical behavioral traits not captured in annotations. No contradiction with annotations.

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 highly concise and front-loaded: the first sentence covers the core purpose and scope, and the second sentence adds essential cost information. Every sentence earns its place with no wasted words, making it efficient for an AI agent to parse.

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

Completeness4/5

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

Given the tool's moderate complexity (single parameter, no output schema), the description is mostly complete. It covers purpose, scope, and cost, but lacks details on output format or error handling. With annotations providing safety and idempotency, and schema covering parameters, the description is sufficient but could be slightly enhanced with output expectations.

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%, with the parameter 'symbol' well-documented in the schema. The description does not add any parameter-specific information beyond what the schema provides, so it meets the baseline of 3 for high schema coverage without extra value.

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

Purpose5/5

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

The description clearly states the tool's purpose with specific verbs ('Get AI-powered stock analysis') and resources ('stock'), and distinguishes it from siblings like finance_stock_price or finance_stock_financials by specifying it provides AI-generated analysis covering price action, fundamentals, competitive position, and investment outlook.

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

Usage Guidelines4/5

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

The description implies usage context (when you need AI-powered stock analysis) but does not explicitly state when not to use it or name alternatives. It distinguishes from siblings by content type but lacks explicit guidance on choosing between this and other finance tools like finance_stock_financials or finance_stock_profile.

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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