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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds significant context: the series is 'append-only', 'grounded on a real series, not a model's guess', and returns 'found:false' for unknown slugs, addressing hallucination risk beyond 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 concise and well-structured: starts with primary output, then derived stats, then use cases, then reliability guarantee. Every sentence adds value, and it is front-loaded with key information.

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?

Given the input schema covers all parameters, annotations cover safety, and no output schema is provided, the description fully explains the return value (series, stats, found flag) and behavior for unknown slugs. It is complete for a read-only historical lookup 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 description doesn't need to add much. It provides context linking 'slug' to product or vendor and implies 'kind' differentiates hardware/software. This adds marginal value over the schema, earning a 4.

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 it returns the full dated price series and derived stats for ONE product or vendor by slug. It distinguishes itself from siblings (e.g., compare, find_best) by emphasizing single entity focus and being a 'citable answer' grounded in real data.

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?

Explicitly lists query types like 'how much did X cost' and 'did X's price drop', making it clear when to use. It does not explicitly state when not to use or alternatives, but the context of siblings implies different use cases. Slight lack of direct exclusion guidance.

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