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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, but the description adds valuable behavioral context: it explains that missing fields mean data not yet entered by contributors (reinforcing open world), that computed scores are indicative with regional caveats, and that data is under ODbL 1.0 requiring attribution. This goes beyond the annotations by clarifying data interpretation and licensing, without contradicting any hint.

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 front-loaded with the core purpose and then lists the return fields and caveats. While it is somewhat lengthy, each sentence adds relevant context (data interpretation, score limitations, license). The structure is logical, but given an output schema exists, some field enumeration could be trimmed without loss, earning a 4 rather than a 5.

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 equips an agent with everything needed to call the tool correctly: the primary key (barcode), optional field filtering, the full return set, and important data quality caveats (crowd-sourced, missing fields, score interpretation). It also covers licensing for downstream use. Combined with the existing annotations (read-only, idempotent, open-world), no critical context 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?

Both parameters (barcode and fields) are fully documented in the input schema with descriptions (100% coverage). The tool description adds no new parameter-specific guidance beyond the schema, so it doesn't enhance what the schema already provides. The baseline score of 3 is appropriate since the schema does the heavy lifting.

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 explicitly states the tool 'Fetch a packaged food product by barcode (EAN-13 or UPC) from Open Food Facts,' providing a specific verb and resource. It also enumerates the returned fields, making the tool's function unmistakable. Although it doesn't explicitly contrast with sibling tools, the barcode-based retrieval is distinct from search, compare, and browse, satisfying the distinction criterion.

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 says nothing about when to use this tool versus its siblings (off_search_products, off_compare_products, off_browse_taxonomy). It does not mention that this is the appropriate choice when a specific barcode is known, nor does it advise against using it for broad searches. The only implicit guidance is that barcode identification is required, but explicit routing to alternatives is missing.

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