MCP Yahoo Finance

get_performance_analysis

Analyze adjusted performance for multiple Yahoo Finance symbols across a date range, with optional benchmark comparison for relative returns and correlation.

Instructions

Analyze adjusted performance for multiple symbols over a date range.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "symbols": "<symbols>",
      "start_date": "<start_date>",
      "end_date": "<end_date>"
    },
    "name": "get_performance_analysis"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Maximum price rows returned per symbol, from 1 to 500.
`symbols`	Yes	One to 10 Yahoo Finance symbols to analyze.
`end_date`	Yes	Inclusive end date in YYYY-MM-DD format.
`start_date`	Yes	Inclusive start date in YYYY-MM-DD format.
`benchmark_symbol`	No	Optional symbol used for relative return and correlation.

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.2.0Oct 1, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are supplied, so the description carries the full burden. It does not explain what 'adjusted' means (adjusted close?), what metrics the analysis produces (returns, correlation, benchmark-relative performance), or whether it is read-only. For a computation tool with no output schema, this is a substantial gap.

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?

A single efficient sentence with the core action and scope front-loaded and no filler. It is concise, though its brevity is partly the source of the missing detail rather than an intentional structural choice.

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?

With no annotations, no output schema, and five parameters, the definition should say more about what the analysis returns and how symbols/benchmark combine. As written, an agent knows the inputs only from the schema and has no idea what output to expect.

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%, so all five parameters, including the optional benchmark_symbol, are already documented in the schema. The description adds no parameter-level meaning (e.g., how benchmark_symbol affects results), so baseline 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 (Analyze) and resource (adjusted performance) with scope (multiple symbols, date range). It is clear, but it does not differentiate itself from siblings like get_symbol_comparison or get_historical_stock_prices, which an agent could plausibly pick for similar requests.

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 alternative tools named. With ~20 sibling retrieval tools, the description leaves the agent to infer that this is the multi-symbol comparative analysis option rather than, say, a raw price fetch.

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