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

Annotations already mark the tool as read-only and idempotent, and the description adds meaningful behavioral details: uncovered funds are listed but excluded from percentages, amounts are optional, and money values appear only when amounts are given. This goes well beyond what annotations provide.

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-load the core purpose and then add edge-case behavior without any fluff. Every clause contributes useful information, and the structure is easy to parse quickly.

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?

Even without an output schema, the description conveys the return shape: company holdings, percentage and money values, and the funds through which each holding is held. It also flags uncovered funds, leaving little ambiguity for a moderately complex aggregation 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?

Schema coverage is 100%, so the baseline is 3. The description adds value by explaining that money amounts are conditional on input amounts and that the output identifies which funds each holding comes through, enriching the schema's parameter descriptions.

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?

States a specific verb ('look through'), the resource (a list of US ETFs), and the outcome (underlying companies with percentages, money, and source funds). This clearly distinguishes it from sibling tools like compare_funds or stock_exposure.

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 makes the intended use case clear: when you have a portfolio of US ETFs and want aggregated exposure to underlying companies. It does not explicitly name alternatives or exclusions, but the context is strong enough for an agent to select it appropriately.

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