get_macro_contextGet macro market context: sector P/E ratios, sector performance, US Treasury rates (2Y/10Y/30Y), CPI inflation data. Also provides key inter-market ratios (HYG/LQD, TLT/SPY) from our price data.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | ||
| inter_market_ratios | No |
Changes observed during successful MCP inspections.
Output schema / properties / date / typePrevious value: -"string"New value: +[
+ "string",
+ "null"
+]Output schema / properties / inter_market_ratios / typePrevious value: -"object"New value: +[
+ "object",
+ "null"
+]Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "properties": {
+ "date": {
+ "type": "string"
+ },
+ "inter_market_ratios": {
+ "type": "object"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, and openWorld behavior, so the safety profile is covered. The description adds a small amount of provenance by noting the ratios come 'from our price data,' but says nothing about data freshness, update cadence, or reliability of the macro figures.
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?
Two sentences, front-loaded with the primary content list and no filler. Every clause enumerates a distinct dataset the caller receives.
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?
An output schema exists, so return values need not be described, and the enumerated contents give a solid preview of scope. The only real gap is failing to clarify its boundary against get_intermarket, which shares stated functionality.
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?
The tool takes no parameters, so there are no argument semantics to explain and the schema is trivially complete; baseline 4 applies. The description correctly adds no parameter detail because none is needed.
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 uses a specific verb+resource (get macro market context) and enumerates concrete contents: sector P/E ratios, sector performance, Treasury rates, CPI, and inter-market ratios. It does not explicitly differentiate itself from the sibling get_intermarket, which appears to overlap on the HYG/LQD and TLT/SPY ratios mentioned here.
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 statement of when to use this tool, when not to, or which alternative to pick. The omission is notable because the sibling get_intermarket also covers inter-market ratios, so an agent has no basis 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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