Today's most-traded US single-stock option contracts by volume, with each contract's volume-to-open-interest ratio. Source: Cboe, ~15-minute delayed. Ranked within a fixed scan set, not the whole market.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint: true and title. The description adds valuable behavioral context: the data source (Cboe), approximate 15-minute delay, and that it ranks within a fixed scan set rather than the whole market. This goes beyond the annotation without contradicting it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences covering purpose, source, scope, and key metric. No filler or repetition, ideal length for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no parameters and a read-only annotation, the description provides sufficient context: source (Cboe), delay (~15 min), scope (most-traded, not whole market), and key metric. It doesn't describe the output format, but for a zero-parameter read-only tool with an output schema absent, this is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist (schema is empty), so there is nothing to explain. The baseline for zero parameters is 4. The description clarifies the output (most-traded contracts with ratio) but does not need parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to list today's most-traded US single-stock option contracts by volume, including volume-to-open-interest ratio. It distinguishes from sibling tools (which cover corporate actions, insider trades, etc.) by explicitly mentioning options and the specific metrics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context (source, delay, fixed scan set) but does not explicitly state when to use this tool versus alternatives or when not to use it. It implicitly implies this is for options trading activity, but lacks explicit guidance on selection criteria or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct data source or analytical angle: buybacks, congress trades, DCA fit, insider buying, 13F filings, price levels, risk phrases, and options volume. There is no overlap in purpose or output, so an agent can unambiguously select the right tool.
All tool names follow a consistent lowercase_with_underscore noun-phrase pattern (e.g., buyback_leaders, risk_filings). The naming is uniform and descriptive, making it easy to predict what each tool does based on the name alone.
The server has 8 tools, squarely in the well-scoped range. Each tool represents a meaningful, non-redundant screen or data source, and none feels like filler or duplicative functionality.
For a market-aware server, the coverage is strong: it spans corporate actions (buybacks), insider activity, institutional holdings, technical levels, risk signals, and options flow. Minor gaps exist—no general price/quote tool or earnings-focused screen—but the set is coherent and covers diverse data sources without major dead ends.