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Stratalize Finance

get_global_equity_benchmark

Read-only

Global equity index benchmarks — S&P 500, Nasdaq, Russell 2000, Stoxx 600, DAX, FTSE 100, Nikkei 225, Hang Seng, Shanghai Composite, MSCI EM. YTD returns, P/E ratios, and risk-on/risk-off global signal. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regionNo

TDQS

A3.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, but the description adds substantial behavioral context: live data source, HTTP 503 with no charge when upstream is unavailable, the x402 SLA cost, and the data_source field disclosing provenance. It also mentions the risk-on/risk-off signal as an output. This goes beyond the annotations and provides valuable operational details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core content and then includes operational details separated by a pipe. However, the HTTP 503 behavior is stated twice in redundant terms, adding unnecessary length. The structure is acceptable but could be tighter.

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 tool with one optional parameter and no output schema, the description covers the indices, metrics, failure behavior, cost, and data provenance, providing a solid understanding of the tool's capabilities. The main gap is the lack of clarity about the region parameter's effect on the returned data, which is a notable omission. Overall, it's fairly complete for the tool's simplicity.

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

Parameters1/5

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

The input schema has one parameter (region) with an enum but zero description coverage. The description does not mention the parameter at all, so it fails to explain how to use the region filter or what each enum value returns. This is a complete miss for parameter semantics, as the description must compensate for the 0% schema coverage.

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 identifies the resource as global equity index benchmarks, listing specific indices and metrics (YTD returns, P/E ratios, risk-on/risk-off signal). This distinguishes it from other benchmark tools that focus on commodities, credit, or other asset classes. However, it lacks an explicit verb like 'retrieves' or 'provides,' instead using a noun phrase, which slightly reduces clarity.

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

Usage Guidelines3/5

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

The description conveys the content domain (global equities) and the signal it provides, implying when it would be used. It does not explicitly state when to use this tool instead of alternatives, nor does it mention exclusions or alternate tools. The sibling list provides indirect differentiation, but the description itself lacks direct guidance.

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

A3.5/5.0
Disambiguation2/5

Multiple tools have overlapping purposes, e.g., get_inflation_benchmark and get_bls_inflation_components, get_commodity_benchmark and get_agricultural_commodity_benchmark. Descriptions provide some differentiation, but many benchmark tools cover similar domains, leading to high potential for misselection.

Naming Consistency5/5

All tools follow a consistent 'get_' prefix with snake_case nouns, e.g., get_inflation_benchmark, get_ma_multiples_benchmark. No mixing of conventions or irregular naming patterns.

Tool Count2/5

46 tools is excessive for a server focused on financial benchmarks and intelligence. While the domain is broad, many tools could be consolidated. The high count may overwhelm agents and suggests insufficient scoping.

Completeness3/5

The toolset covers a wide range of financial data—benchmarks, regulatory filings, commodity prices—but lacks granular tools like individual stock prices or sector-specific indices. Some areas (e.g., credit unions) are well-covered, but other common financial operations (e.g., portfolio analytics) are absent.

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