Understand sector-wide market activity by viewing counts of advancing, declining, and unchanged stocks, plus top holdings and each sector's daily performance.
How wide today's move is: per sector, how many of its companies are up, down and unchanged, with its largest companies and today's move. The universe is the S&P 500's members where a vendor lists them.
| Name | Required | Description | Default |
|---|---|---|---|
| leaders | No |
Changes observed during successful MCP inspections.
v0.2.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It explains the output concept (counts of up/down/unchanged, largest companies, today's move) and the universe caveat ('where a vendor lists them'), which adds useful context. However, it does not disclose whether the data is real-time, delayed, or end-of-day, nor how the 'leaders' parameter affects the output.
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 sentences and front-loads the core purpose. The second sentence adds the universe definition, which is valuable. It is concise and readable, though the 'leaders' parameter could have been clarified without much extra length.
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?
For a simple one-parameter tool with no output schema, the description gives a reasonable sense of what is returned (per-sector counts, largest companies, today's move). However, it omits the meaning of the 'leaders' parameter and any temporal/real-time caveats, which an agent would need to invoke it correctly.
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?
Schema description coverage is 0%, so the description must compensate for the undocumented 'leaders' parameter. The description mentions 'largest companies' but never explicitly ties that to the 'leaders' parameter or explains what the integer controls (e.g., number of top companies per sector). This is a clear gap.
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 states a specific verb ('How wide today's move is') and resource (per-sector breadth of S&P 500 members), and distinguishes it from sector_performance by focusing on breadth (counts of up/down/unchanged companies) rather than aggregate performance. It is clear but does not explicitly name a sibling alternative.
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 implies this tool is for assessing market breadth by sector, and the universe definition ('S&P 500's members where a vendor lists them') provides context. However, it does not explicitly state when to use this tool versus sector_performance or movers, nor does it give exclusions or alternative conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.