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axionquant

AxionQuant MCP Server

Official
by axionquant

etf_weights

Find the sector, industry, and stock percentages that make up any ETF from its ticker.

Instructions

Find what percentage of each sector industry and stocks make up the ETF

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesStock ticker (e.g., AAPL)
Behavior2/5

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It only states the action (find percentages) without detailing expected output, return format, or any side effects. It does not mention whether the result is a list, an object, or whether it includes all holdings or top weights. There is no contradiction, but the information is too thin.

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 one short sentence with no filler. It is front-loaded with the core action. However, the sentence is grammatically awkward and could be clearer with punctuation or restructuring, but it is appropriately concise.

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

Completeness2/5

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

For a tool with a single parameter, no output schema, and no annotations, the description is too vague to enable correct invocation. It does not specify what the returned data structure looks like, whether it covers all sectors/industries/stocks, or how results are ordered. An agent cannot predict the response or know if this differs from etf_holdings or etf_exposure.

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 already describes the single parameter 'ticker' with an example, and schema coverage is 100%. The description adds no additional parameter context. Per the rubric, with high coverage the baseline is 3, and the description provides no extra value beyond what the schema offers.

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

Purpose3/5

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

The description states the verb 'Find' and the resource 'what percentage of each sector industry and stocks make up the ETF'. It conveys the core idea of returning weight breakdowns, but the phrasing is awkward and ambiguous ('sector industry and stocks' likely means sector, industry, and stock levels). It does not explicitly differentiate from similar tools like etf_holdings, etf_holdings_all, or etf_exposure, so an agent gets only a general sense of purpose.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives. The description does not mention sibling tools, nor does it state conditions like 'use etf_holdings for detailed holdings' or 'use etf_exposure for geographic exposure'. An agent must guess based on names alone, which is insufficient given the large family of ETF-related tools.

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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