Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare the tool as read-only, idempotent, and non-destructive, so the description's job is lighter. It adds useful context about the specific data included (e.g., 2Y/10Y/30Y Treasury rates, HYG/LQD, TLT/SPY) and mentions the data source ('our price data'). However, it does not disclose behavioral traits such as data freshness, update frequency, or any limitations, which would have increased transparency.

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 remarkably concise, consisting of two sentences. It front-loads the key purpose ('Get macro market context') and then efficiently lists the specific data categories. Every word adds value, with no fluff or repetition of schema information.

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 zero-parameter tool with an existing output schema, the description is sufficiently complete. It enumerates all major data categories and even includes the inter-market ratios, which adds depth. It does not need to explain return values because an output schema exists. The only minor gap is lack of mention about time periods or data granularity, but this is not critical for a read-only macro context tool.

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 has no parameters, so there are no parameter semantics to explain. The baseline for zero parameters is 4, and the description does not need to compensate for any schema gaps. It adequately summarizes the data content, which is sufficient.

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 with a specific verb ('Get') and a well-defined resource ('macro market context'). It enumerates concrete data types (sector P/E ratios, sector performance, US Treasury rates, CPI inflation, inter-market ratios), which distinguishes it from siblings like get_crypto_context or get_intermarket by its focus on macro indicators.

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 usage for macro context needs, but it does not explicitly state when to use this tool versus alternatives. The mention of inter-market ratios could create ambiguity with the sibling tool get_intermarket, yet no comparisons or exclusion criteria are provided. The guidelines are implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.