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Hub-Equity

hub-equity-mcp

Official
by Hub-Equity

list_hubs

Read-onlyIdempotent

Enumerate standardized Hub-Equity hubs by category (income statement, balance sheet, cash flow, ratio, equity info, metadata) to discover available metrics without many concept searches.

Instructions

List the catalog of standardized Hub-Equity hubs.

Useful when you need to enumerate available metrics for a category (e.g. all balance-sheet hubs) without making N search_concept calls.

Args: category: One of income_statement, balance_sheet, cash_flow, ratio, equity_info, metadata. Omit to list across all categories. include_non_primary: True to include derived/secondary hubs. limit: Cap (max 200, default 80).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
categoryNo
include_non_primaryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYesNumber of items returned (at most `limit`, itself capped at 200)
matchesYesHubs matching the filters, sorted by category then catalog order

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so the safety profile is fully covered. The description adds behavioral context only in the form of parameter domain limits (max 200, default 80) and the efficiency rationale; it says nothing extra about pagination, ordering, or result shape beyond what the output schema presumably covers. Adequate but not rich.

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?

Front-loads the purpose, then the usage rationale, then a compact Args block; nothing is wasted. Minor redundancy in restating the default of 80 that already appears in the schema keeps it from a 5.

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

Completeness5/5

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

For a zero-required-parameter list tool with an output schema already defining the return shape, the description covers purpose, routing, and every parameter's semantics and constraints. Nothing an agent needs in order to call it correctly is missing.

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

Parameters5/5

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

Schema coverage is 0% and no enums are declared in the schema, yet the description supplies the full allowed value set for category (income_statement, balance_sheet, cash_flow, ratio, equity_info, metadata), the meaning of include_non_primary (derived/secondary hubs), and the limit cap of 200 with default 80. This is exactly the compensation required for an undocumented schema.

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?

States a specific verb (List) and a specific resource (the catalog of standardized Hub-Equity hubs), and immediately contrasts itself with the sibling search_concept by framing the tool as a bulk-enumeration alternative. An agent can tell it apart from search_concept without opening either schema.

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?

Gives a concrete usage scenario ('enumerate available metrics for a category, e.g. all balance-sheet hubs') and names the alternative it replaces (N search_concept calls), which is exactly the routing decision an agent needs. It lacks an explicit when-not condition (e.g. when a single known metric is wanted), so it falls short of a full 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.