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vlearner

mcp-etf-holdings

by vlearner

etf_holdings

Retrieve an ETF's top holdings and their portfolio weight percentages by ticker symbol. Use it to inspect fund composition and concentration before investing.

Instructions

Return the top holdings of an ETF with their portfolio weight percentages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesETF ticker symbol, e.g. 'SPY'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It does disclose that only 'top' holdings are returned with weights, implying a truncated result set, which is useful scoping context. But it never quantifies 'top', states data freshness, or notes any auth/rate constraints.

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?

A single tight sentence with the key output (weights) front-loaded alongside the resource. No filler or redundant restatement of the tool name.

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 simple one-parameter read tool with an output schema present, return-shape explanation is unnecessary. The only real gap is the undefined size of the 'top' list, which mildly affects expectations but not invocation correctness.

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 description coverage is 100% for the single ticker parameter, so the schema already documents the argument including an example ('SPY'). The description adds no parameter-level meaning beyond that, so the baseline of 3 applies.

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?

States a specific verb (Return) and resource (top holdings of an ETF) plus the payload (portfolio weight percentages). However, it does not distinguish itself from siblings like etf_info or find_etfs_holding_stock, leaving the agent to infer the boundary.

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?

No when-to-use guidance, no prerequisites, and no mention of alternatives such as etf_info for broader fund data or find_etfs_holding_stock for the reverse lookup. The agent must infer the appropriate context entirely.

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