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Glama

Twelvedata

by io.github.pipeworx-io

Quote

quote
Read-onlyIdempotent

Twelve Data real-time quote snapshot for a symbol: open, high, low, close, volume, 52-week range, exchange, currency. Use for a full current-day market snapshot.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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").
exchangeNoOptional exchange filter (e.g. "NASDAQ", "NYSE", "Binance").
intervalNoBar interval: 1min, 5min, 15min, 30min, 45min, 1h, 2h, 4h, 1day, 1week, or 1month.
timezoneNoOptional timezone, e.g. "America/New_York" or "UTC".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeNoResponse code
statusNoResponse status
messageNoResponse message

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint=false, so the description adds limited behavioral context beyond listing output fields. No contradictions, but the description could elaborate on data freshness or rate limits.

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?

Two sentences with no wasted words. Essential information (data source, fields, usage hint) is front-loaded. Efficient and easy to parse.

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?

Given the output schema exists (not shown), the description sufficiently explains inputs and output fields. It covers the main use case but could mention relationship to sibling tools like 'price' for completeness.

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% with detailed descriptions for all 4 parameters, including examples and constraints. The description does not add extra parameter meaning beyond what the schema provides, so baseline score of 3 is appropriate.

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?

Description clearly states the tool returns a real-time quote snapshot with specific fields (open, high, low, close, volume, etc.) and suggests use for a full current-day market snapshot. However, it does not explicitly differentiate from sibling tools like 'price' or 'time_series', which may have overlap.

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 gives a clear when-to-use ('full current-day market snapshot') but lacks explicit when-not-to-use or alternatives. Sibling tools like 'price' or 'eod' exist but are not mentioned, leaving ambiguity about selection.

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.

Resources