Summary Compensation Table by executive and year.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "executive_compensation"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| ticker | No | ticker or CIK |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing: no read-only indication, no note on whether data is paginated or limited to the most recent proxy year, no coverage caveats, and no sense of what the response contains. The 'by executive and year' phrasing is the only structural hint.
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?
A single short fragment with zero filler and the resource named up front. It is efficient, though the terseness crosses into under-specification rather than true conciseness.
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 tool with no annotations and no output schema, the description should compensate by explaining what the table returns and how the optional ticker is used, but it does not. An agent cannot tell which years or executives are covered, whether results are truncated, or whether the optional parameter has a default behavior.
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 100% for the single 'ticker' parameter ('ticker or CIK'), so the schema already documents it fully. The description adds no parameter-level meaning — 'by executive and year' describes output columns, not the input. Baseline 3 applies when the schema does the work.
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 names a specific resource (the SEC Summary Compensation Table) and its dimensions (by executive and year), which tells an agent what data comes back. But it is a noun phrase with no verb, so it never states the operation (fetch/list/lookup), and it does not distinguish itself from the sibling 'pay_vs_performance' or 'directors'. Purpose is inferable rather than stated.
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?
There is no when-to-use guidance, no indication of prerequisites (e.g., needing a ticker or CIK), and no mention of alternative tools. With 'pay_vs_performance' and 'governance_dataset' among the siblings, an agent has no basis from the description for choosing between them.
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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