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stock_quote_batch

Read-onlyIdempotent

Get the latest available stock prices for multiple stocks at once (up to 10). Returns a comparison table with price, daily change, volume, market cap, and P/E. Use this for "show me FAANG stocks", "compare tech stock prices", "how are energy stocks doing?", or any multi-stock price check.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolsYesTicker symbols, max 10. Accept either CSV string ("AAPL,MSFT,GOOGL") or array (["AAPL","MSFT","GOOGL"]).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, and non-destructive behavior, so the description's additional context is useful rather than required. It adds the 'latest available' freshness qualifier, the 10-symbol cap, and the output shape (comparison table with specific fields). It does not discuss possible data delays, invalid ticker handling, or response ordering, but these are minor for a safe read-only tool.

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 with no filler. The primary action and limit come first, followed by output details and concrete example queries. Every sentence contributes value, and the structure is easy to parse quickly.

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 low complexity, full schema coverage, and strong safety annotations, the description is largely complete for selection and invocation. It covers scope, the symbol limit, and return fields, which compensates for the absence of an output schema. A brief note on using stock_quote for a single symbol or on invalid symbol behavior would improve it further, but nothing essential is missing.

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 input schema fully documents the only parameter, symbols, including accepted formats (CSV string or array) and the maximum of 10. Since schema description coverage is 100%, the description does not need to add much. It restates 'up to 10' and 'multiple stocks', but adds no substantive semantic detail beyond the schema.

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 action and scope: 'Get the latest available stock prices for multiple stocks at once (up to 10)' and enumerates the returned comparison fields (price, daily change, volume, market cap, P/E). This distinguishes it from a single-stock quote tool, though it does not explicitly disambiguate from the sibling stock_compare, and its example 'compare tech stock prices' could overlap with that tool.

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 provides explicit example use cases ('show me FAANG stocks', 'compare tech stock prices', 'how are energy stocks doing?') and a general rule ('any multi-stock price check'). It gives clear context for when to use the tool, but it does not explicitly state when not to use it or name single-stock alternatives like stock_quote.

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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TDQS

B3.3/5.0
Disambiguation2/5

Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.

Naming Consistency3/5

Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.

Tool Count1/5

294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.

Completeness4/5

The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.