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XFINLAB Intelligence

by com.xfinlab
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get_sentiment

Get FinBERT-based sentiment analysis of recent headlines for a ticker. Returns per-headline label/confidence/score plus an average score. Real model inference, not a fabricated estimate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of recent headlines to analyze, 1-25.
tickerYesTicker to analyze, e.g. 'AAPL'.
api_keyNoXFINLAB Intelligence API key (X-API-Key). Omit if supplied via HTTP header instead.
marketplace_license_keyNoOptional: an mcp-marketplace.io license key for this listing's paid tier. If valid, upgrades a free XFINLAB API key's daily quota to Pro for this call. Omit if supplied via the X-Marketplace-License-Key header instead, or if not using a marketplace license.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / marketplace_license_key
      Added value: +{
+  "description": "Optional: an mcp-marketplace.io license key for this listing's paid tier. If valid, upgrades a free XFINLAB API key's daily quota to Pro for this call. Omit if supplied via the X-Marketplace-License-Key header instead, or if not using a marketplace license.",
+  "type": "string"
+}
  2. First observed

TDQS

A3.8/5.0
Behavior3/5

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 adds a valuable behavioral disclosure ('Real model inference, not a fabricated estimate'), which prevents agent hallucination. However, it does not mention any potential side effects, rate limits, or the need for an API key (though the schema covers the key). The safety profile (read-only) is not explicitly stated, leaving some ambiguity.

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 two sentences, front-loads the core purpose and output, and then adds a crucial authenticity note. There is no fluff or repetition; every sentence earns its place.

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 no output schema, the description adequately explains the return structure (per-headline label/confidence/score plus average). It covers the main function and the 'real inference' aspect. It could mention limitations or error scenarios, but given the tool's simplicity and the rich schema, it is sufficiently complete.

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 each parameter described. The description does not add any extra meaning beyond the schema; it mentions 'recent headlines' which loosely maps to the limit parameter, but no additional semantics are provided. Baseline of 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 uses a specific verb ('Get') and resource ('FinBERT-based sentiment analysis of recent headlines for a ticker'), which clearly distinguishes it from the sibling tools (market map, feed, events, technical analysis). The purpose is unambiguous and specific.

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 when to use the tool (when sentiment on a ticker is needed) but does not explicitly mention alternatives or when not to use it. The sibling names are distinct enough that an agent could infer the choice, but there is no direct guidance on selection criteria.

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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