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Glama

Twelvedata

by io.github.pipeworx-io

Stocks

stocks
Read-onlyIdempotent

Twelve Data reference list of all supported stock symbols with exchange and country metadata. Use to discover or validate tickers before querying price endpoints.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional instrument type filter (e.g. "Common Stock").
symbolNoOptional ticker filter (e.g. "AAPL").
countryNoOptional country filter (e.g. "United States").
exchangeNoOptional exchange filter (e.g. "NASDAQ", "NYSE", "Binance").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeNoResponse code
statusNoResponse status
messageNoResponse message

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering safety and behavior. The description adds useful context about the data returned (exchange and country metadata), but does not disclose additional traits like pagination or rate limits, which is acceptable given the annotations.

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 concise sentences with no wasted words. The first sentence defines the tool, the second provides usage guidance. Efficient and effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (reference list with optional filters), the description is complete. Output schema exists, so return values need not be explained. No gaps for the intended use case.

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 the input schema already documents all four optional parameters. The description does not add further meaning beyond the schema, which is expected when schema is complete. 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 the tool provides a reference list of supported stock symbols with metadata, and explicitly states its purpose: to discover or validate tickers before querying price endpoints. This distinguishes it from sibling tools like 'price' or 'quote' that handle price data.

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

Usage Guidelines5/5

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

The description explicitly advises using this tool to discover or validate tickers before querying price endpoints, providing clear guidance on when to use it. This differentiates it from price-related siblings.

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