Analyze food image

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

Annotations already indicate read-only and non-destructive. The description adds that it does not log data, which is a specific privacy behavior not covered by annotations. It also reveals the internal routing logic (barcode, OCR, meal-photo), providing useful context beyond structured fields.

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?

Single sentence of 20 words, front-loading the core purpose. No filler, each word earns its place.

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 10 parameters, no output schema, and only annotations for behavioral cues, the description is adequate but incomplete. It does not explain what the tool returns, how it handles multiple inputs, or error conditions. For a routing tool, minimal completeness, but gaps exist.

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 must explain parameters. It only mentions the three analysis types but does not map parameters to those types (e.g., barcode_observation for barcode, nutrition_label_text for OCR, image_description for meal estimation). This leaves the agent guessing how to use the 10 parameters correctly.

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 states a specific verb ('Route') and resources ('barcode, nutrition label OCR, or meal-photo estimation'), and distinguishes from siblings like nourish_lookup_barcode and nourish_estimate_meal_photo by indicating it takes agent-provided observations. The 'without logging' clause adds clarity on non-destructive behavior.

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 clear when to use: when the agent has already extracted image observations (text, barcode, etc.) and wants to analyze them. It does not explicitly state when not to use, but the context of siblings suggests raw images should go to other tools. This is clear enough but lacks explicit exclusions.

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