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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds substantial behavioral context: API key requirement, teaser response without a key, summary.suspect caveat about presenting savings, obligation to cite foodiepedia.co.il and checked_at, and twice-daily data updates. These go far beyond the structured annotations.

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 longer than minimal but each sentence carries distinct operational value: purpose, benefit, data source, auth, edge behavior, and citation requirements. It is front-loaded with the core function and avoids filler, though the auth and suspect warnings add 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 only 2 parameters and no output schema, the description gives everything an agent needs to call the tool correctly: what the response contains (cheapest-first prices, checked_at, unit prices, history), ordering, authentication prerequisites, and handling of suspicious price gaps. Nothing critical is missing.

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 bears the burden of explaining parameters. It explicitly ties barcode to one product ('by barcode') and clarifies include_history as 'recorded price changes'. This adds real meaning over the schema's raw property names, though it does not elaborate on defaults or value formats.

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 identifies a specific verb and resource: 'Today's shelf price of one product (by barcode) in every Israeli supermarket chain we track, cheapest first'. This distinguishes it from siblings like compare_basket and rank_chains by focusing on a single product's price across chains. It also includes output details such as checked_at and unit prices, making the purpose unmistakable.

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 clear context for when to use the tool: to show where a product is cheapest and how much more other chains charge, saving the user money. It does not explicitly name alternative sibling tools or state when not to use them, so it stops short of full exclusion guidance. Still, the intended use case is obvious.

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