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veroq_compare

Compare news coverage across multiple sources, analyze per-source bias, and receive a synthesized overview of any topic.

Instructions

Compare how different news sources cover the same topic, with per-source bias analysis and synthesis.

WHEN TO USE: When you need to understand media bias or see how coverage of an event differs across outlets. RETURNS: Topic headline, VEROQ confidence/bias scores, per-source analysis, and overall synthesis. COST: 2 credits. EXAMPLE: { "topic": "Federal Reserve rate decision" }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesTopic to compare coverage on

Implementation Reference

  • Handler for veroq_compare_tickers: sends a 'Compare ...' question to the /api/v1/ask endpoint.
    execute: async ({ tickers }) => {
      return await api("POST", "/api/v1/ask", undefined, {
        question: `Compare ${tickers}`,
        fast: false,
      }) as Record<string, unknown>;
    },
  • Input schema for veroq_compare_tickers: single 'tickers' string field.
    inputSchema: z.object({
      tickers: z.string().describe("Tickers to compare — 'AAPL vs MSFT' or 'NVDA, AMD, INTC' (2-5 tickers)"),
    }),
  • Registration of veroq_compare_tickers tool using createVeroQTool.
      createVeroQTool(server, {
        name: "veroq_compare_tickers",
        description: `Compare 2-5 tickers side by side — price, technicals, sentiment, and correlation.
    
    WHEN TO USE: When comparing investment options or analyzing portfolio relationships. Provides price comparison, technical indicator comparison, sentiment comparison, and Pearson correlation matrix.
    
    RETURNS: Per-ticker data (price, change%, RSI, signal, sentiment) plus correlation matrix and comparative summary.
    
    COST: ~3 credits for 2 tickers, ~5 for 5 tickers.
    
    EXAMPLE: { "tickers": "AAPL vs MSFT" }
    EXAMPLE: { "tickers": "NVDA, AMD, INTC" }`,
        inputSchema: z.object({
          tickers: z.string().describe("Tickers to compare — 'AAPL vs MSFT' or 'NVDA, AMD, INTC' (2-5 tickers)"),
        }),
        execute: async ({ tickers }) => {
          return await api("POST", "/api/v1/ask", undefined, {
            question: `Compare ${tickers}`,
            fast: false,
          }) as Record<string, unknown>;
        },
        display: (result) => {
          const d = result as Record<string, unknown>;
          return String(d.summary || JSON.stringify(d, null, 2).slice(0, 3000));
        },
        annotations: { readOnlyHint: true, openWorldHint: true },
        category: "intelligence",
        credits: 3,
      });
  • Listed as a core tool in the Finance vertical kit configuration.
    coreTools: [
      "veroq_analyze_ticker",
      "veroq_verify_market_claim",
      "veroq_generate_trading_signal",
      "veroq_comprehensive_intelligence",
      "veroq_compare_tickers",
      "veroq_ask",
      "veroq_verify",
    ],
Behavior3/5

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

No annotations are provided, so the description carries full burden. It states costs (2 credits) and returns (headline, scores, analysis, synthesis), implying a read-only operation. However, it does not explicitly state non-destructive behavior or disclose any side effects beyond the output.

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 efficient: 4 sentences plus an example. It front-loads purpose, then usage, returns, cost, and example. No redundant information; each section serves a purpose.

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?

For a tool with one parameter and no output schema, the description adequately covers purpose, usage, return structure (headline, scores, analysis, synthesis), and cost. It lacks details on the number of sources or bias score interpretation but is sufficient for an agent to decide and invoke.

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 coverage is 100% with one parameter 'topic' described. The description adds an example ('Federal Reserve rate decision') which reinforces usage but does not add meaning beyond the schema. Baseline 3 is appropriate.

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 it compares how different news sources cover the same topic with bias analysis and synthesis. It distinctively differentiates from sibling tools like veroq_ticker_news or veroq_feed by focusing on multi-source comparison rather than single-source news.

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 'WHEN TO USE' section explicitly states the use case: understand media bias or see coverage differences across outlets. It does not mention when not to use or alternatives, but the sibling list shows no direct competitor, making this guidance clear enough.

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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