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Glama

price_history

Fetch historical OHLCV price data for one or more tickers. Free tier: 1 ticker, 252 days. Paid tier: up to 20 tickers, 1260 days.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoNumber of historical trading days to return. Free tier: max 252 days (~1 year). Paid tier: up to 1260 days (~5 years). Default: 252.
tickersYesTicker symbols to fetch price history for. Free tier: max 1 ticker. Paid tier: up to 20 tickers.
intervalNoPrice interval. "daily" returns one OHLCV row per trading day, "weekly" aggregates to weekly bars, "monthly" aggregates to monthly bars. Default: "daily".daily

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses key behavioral constraints (tier limits, intervals) but does not mention response format, rate limiting, data source, or error handling. The description is adequate but not comprehensive.

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?

The description is extremely concise, consisting of two sentences with zero wasted words. It front-loads the core purpose and efficiently adds tier constraints. Every sentence earns its place.

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?

Despite the conciseness, the description lacks important details for a data-fetching tool: it does not specify the return format (OHLCV columns, order, date range), data source, or pagination behavior. With no output schema, these omissions leave the agent guessing about the response structure, making it incomplete for practical invocation.

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%, with each parameter (tickers, days, interval) documented. The description adds context about tier limits, but this is already present in the schema's parameter descriptions. Thus, the description adds no significant meaning beyond the schema, warranting a baseline of 3.

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 verb 'fetch', the resource 'historical OHLCV price data', and specifies the scope ('one or more tickers'). It distinguishes from sibling tools (like analyze_risk, compare_portfolios) which focus on analysis rather than raw data retrieval.

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

Usage Guidelines4/5

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

The description provides clear context with tier limitations (free/paid) for ticker count and days, guiding usage based on user's plan. However, it does not explicitly mention when not to use this tool or direct to alternatives for derived metrics, leaving some room for interpretation.

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
Disambiguation5/5

Each tool has a distinct purpose (e.g., risk metrics, Greeks, portfolio optimization, simulation), with no overlap or ambiguity. The descriptions clearly separate core risk analysis from advanced features.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern (e.g., analyze_risk, calculate_greeks), making them predictable and easy to distinguish.

Tool Count5/5

With 10 tools, the server covers a comprehensive range of quantitative risk analytics without being bloated. Each tool serves a clear, non-redundant purpose within risk management.

Completeness4/5

The tool set covers essential risk analysis (VaR, Greeks, optimization, stress tests, attribution) but is missing common features like scenario analysis beyond historical crises or backtesting. Still, it is well above average.