Skip to main content
Glama

OptionsBell Options Flow

Top prints of the day

get_top_prints

The day's biggest options bets ranked by estimated premium - the same view OptionsBell alert emails lead with. Perfect for 'what were the largest options trades today?'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoTrading day, YYYY-MM-DD. Defaults to the latest available day.
typeNo
limitNoMax rows (default 20).
symbolsNoComma-separated tickers, e.g. 'AAPL,NVDA,TSLA'.
min_premiumNoMinimum premium in USD (default 25000).

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries full burden. It discloses ranking by estimated premium and daily scope, but it does not explain what qualifies as a 'print,' whether the premium is total per trade, or any filtering behavior. This is a moderate level of transparency for a read-only list tool.

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 two short, front-loaded sentences that immediately convey the tool's purpose and an example query. No redundant or filler content.

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?

The tool is a simple filtered list with 5 optional params and no output schema. The description covers what it returns and gives a concrete use case. It lacks detail on return fields, but given the tool's simplicity and well-described schema params, it is sufficiently complete.

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 80%, so the baseline is 3. The description itself does not add param-specific meaning, but the schema already documents date, limit, symbols, and min_premium. The description implies date/default behavior by 'day's' but doesn't enhance parameter understanding beyond schema.

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 returns 'the day's biggest options bets ranked by estimated premium,' which is a specific verb-resource pair (get/top prints). It also distinguishes itself by referencing the same view used in alert emails, making it unambiguous what the tool provides.

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 gives a clear use case ('what were the largest options trades today?') and says it's 'Perfect for' that query. However, it does not explicitly mention when to avoid this tool or compare it to sibling tools, so it falls short of full guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation4/5

Each tool targets a distinct analytical view (contract scan, per-symbol detail, history, sentiment, etc.), with clear boundaries. The only minor overlap is between get_symbol_flow and get_unusual_activity when filtering by a single symbol, but descriptions clarify the difference (single-symbol detail vs. broad scanner).

Naming Consistency5/5

All tool names follow a consistent get_<object> pattern (e.g., get_expiry_concentration, get_oi_changes), with ping as the standard exception for liveness checks. The naming is predictable and uniform.

Tool Count5/5

13 tools is well within the ideal range for a specialized data analytics server. Each tool covers a distinct query type and earns its place without redundancy.

Completeness5/5

The tool surface comprehensively covers the domain of unusual options flow discovery and analysis: data discovery, contract-level scans, per-symbol views, time series, sentiment, and market-wide aggregations. No obvious gaps or dead ends.