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

With no annotations, the description effectively discloses key behaviors: it returns a free 1-row preview and requires no authentication. This adds useful context about usage limits and access requirements, though it does not detail response structure or potential rate limits.

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 two short, front-loaded sentences. Every sentence adds value: the first states the core action, the second explains cost and alternative usage. No redundant or filler content.

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?

The description adequately covers purpose, usage alternative, and important constraints (free preview, no auth) for a simple fetch tool with only two parameters. It lacks details on return format, but since there is no output schema, a brief explanation of the preview would improve completeness; still, it is sufficient for a basic 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 input schema provides 100% description coverage for both parameters, including an enum for 'type'. The description adds no further parameter-specific details beyond what the schema already contains, so it meets the baseline but does not exceed it.

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 fetches a single data type from DataFood, using a specific verb and resource. It also distinguishes itself from the sibling datafood_bundle by noting that bundle is for 3+ queries, making the purpose immediately clear.

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 provides explicit guidance on when to use this tool versus datafood_bundle, mentioning cost and query volume. However, it does not address the other sibling tools (portfolio_ask, watch_session), so the guidance is not fully comprehensive.

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