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Currency Conversion

currency_conversion
Read-onlyIdempotent

Twelve Data real-time currency conversion: pass a forex pair symbol (e.g. 'EUR/USD') and an amount to get the converted value at the current exchange rate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dpNoDecimal places (0–11).
amountYesAmount in the base currency to convert.
formatNoResponse format: "JSON" (default) or "CSV".
symbolYesTicker/symbol. Stocks e.g. "AAPL", "MSFT"; forex "EUR/USD"; crypto "BTC/USD"; ETFs "SPY"; indices "IXIC". Comma-separate for a batch (e.g. "AAPL,MSFT").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeNoResponse code
statusNoResponse status
messageNoResponse message

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds 'real-time' and 'current exchange rate' context, but does not disclose any additional behavioral traits beyond what annotations cover. With the annotations handling safety, the description adds marginal value.

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 a single, front-loaded sentence that covers the core purpose without unnecessary elaboration. It is concise yet informative, though it could be slightly more structured by separating input details.

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?

With an output schema present, the description does not need to detail return values. It covers the primary use case and mentions real-time conversion. It does not explicitly address batch processing (comma-separated symbols) which is in the schema, but overall it is sufficiently complete given the richness of structured fields.

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 coverage is 100%, so the schema already documents all four parameters with descriptions and examples. The description does not add new semantic meaning beyond the schema; it only reiterates example symbols. Baseline 3 is appropriate.

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?

The description clearly states it performs real-time currency conversion using Twelve Data, specifies the required inputs (forex pair symbol and amount) and the output (converted value at current exchange rate). This is a specific verb+resource combination that distinguishes it from sibling tools like exchange_rate or forex_pairs.

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 implies usage by specifying inputs ('pass a forex pair symbol...'), but it does not provide explicit guidance on when to use this tool versus alternatives like exchange_rate or forex_pairs, nor does it mention when not to use it.

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

A3.7/5.0
Disambiguation3/5

While many tools have distinct purposes, there is notable overlap between price, quote, eod, and time_series for price data. Also, the multiple ask_pipeworx variants and deep_research could cause confusion about which to use for factual queries. Some tools like bet_research and polymarket_arbitrage also have overlapping domains.

Naming Consistency4/5

Most tools follow a descriptive snake_case pattern (ai_visibility_check, ask_pipeworx, compare_entities). A few are single words (cryptocurrencies, indices, profile) which is acceptable. No mixing of camelCase or other conventions, so consistent overall.

Tool Count2/5

47 tools is quite high for a single server. While the domain is broad (financial data, prediction markets, SEC filings, etc.), many tools are highly specific (e.g., polymarket_arbitrage, bet_research, scan_dependency) and could be consolidated. The count feels bloated and adds cognitive load.

Completeness4/5

The tool set is impressively comprehensive, covering stocks, forex, crypto, economic data, SEC filings, prediction markets, entity resolution, and even claims validation. Minor gaps exist (e.g., limited drug data despite having some tools), but overall the surface supports a wide range of agentic workflows without obvious missing operations.