seasonal_patternStatistics for well-known S&P 500 calendar effects: santa-claus-rally, sell-in-may, september-effect, best-days-of-the-year, worst-days-of-the-year, turn-of-the-month, presidential-cycle, january-barometer, options-expiration, pre-holiday, day-of-the-week, midterm-year.
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | Yes |
Changes observed during successful MCP inspections.
Input schema / properties / pattern / enumPrevious value: -[
- "santa-claus-rally",
- "sell-in-may",
- "september-effect",
- "best-days-of-the-year",
- "worst-days-of-the-year",
- "turn-of-the-month",
- "presidential-cycle",
- "january-barometer"
-]New value: +[
+ "santa-claus-rally",
+ "sell-in-may",
+ "september-effect",
+ "best-days-of-the-year",
+ "worst-days-of-the-year",
+ "turn-of-the-month",
+ "presidential-cycle",
+ "january-barometer",
+ "options-expiration",
+ "pre-holiday",
+ "day-of-the-week",
+ "midterm-year"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint=false, so the safety profile is covered. The description adds nothing behavioral: no indication of what statistic is returned (mean return, win rate, date range), no timeframe, no output shape, and it merely echoes the enum values.
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 single sentence is dominated by a 12-item hyphenated enum recital that duplicates the schema verbatim, while the actual tool behavior is compressed into a few words. Low information density for its 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?
With no output schema and no annotations beyond the read-only/closed-world hints, the description should explain what statistics come back and over what horizon. It omits both, leaving the agent unable to predict the response or choose correctly among seasonality siblings.
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 carries the burden, yet it only restates the enum list already present in the schema. It does not explain what each pattern denotes or what the selected pattern produces, so no meaning is added beyond the structured field.
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 phrase 'Statistics for well-known S&P 500 calendar effects' identifies the resource and domain, but supplies no verb (retrieve/compute/list) and never distinguishes itself from siblings like monthly_seasonality, day_seasonality, or seasonal_trends. An agent cannot tell from the text alone how this differs from the other seasonality tools.
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 conditions, and no mention of alternatives among the seven seasonality-related siblings. The agent must guess that this tool is for pre-canned named effects rather than arbitrary windows.
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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