SaveIQ

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so safety is covered. The description adds genuinely useful non-annotation detail: the three verdict categories, the 90-day low/high/average in CAD, the reasoning output, and an inflation-detection warning. It stops short of failure behavior (invalid ASIN, product not found, throttling), which matters for an open-world fetch.

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?

It is a single dense sentence that front-loads purpose, then output content, then scope restriction, then input format — a sensible order with no filler. It is slightly run-on, stacking verdicts, statistics, currency, and a warning clause that could be split for faster scanning.

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?

For a one-parameter read tool with no output schema, the description carries the return-value burden well by enumerating the verdict, statistics, currency and warning. Missing only error/edge behavior and any hint about data freshness or latency, which keeps it short of fully complete.

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% for the single parameter, and the description's 'Pass the amazon.ca product link or its 10-character ASIN' restates the schema rather than adding format nuances, edge cases, or examples beyond the one ASIN already in the schema. Baseline 3 applies when 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 opens with a specific verb and resource ('Read an Amazon.ca product's recent price history') and adds the distinctive value proposition: a Buy/Wait/Fair verdict with reasons. It also scopes the domain explicitly ('Amazon.ca only'), so an agent can distinguish it from a generic product search sibling without opening the schema.

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?

Usage context is clear: use it for Amazon.ca products to decide whether now is a good time to buy, and it states the input form to supply (link or 10-character ASIN). It never mentions the sibling find_products or explains when to search for a product first versus checking a price directly, so routing guidance is implied rather than explicit.

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

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely new behavioral facts: a hard cap of 8 results and the specific return fields (ASIN, current price in CAD). It does not mention failure/empty-result behavior for a live external search, which keeps it short of a 5.

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?

Two sentences, front-loaded with the action and scope, followed by the routing condition. The example is short and earns its place by demonstrating the plain-language budget form.

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?

For a single-parameter, read-only lookup with no output schema, the description supplies everything an agent needs: input style, result cap, and the returned fields. Annotations carry the safety profile, so no material gap remains.

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 100% and there is only one parameter, so the schema already explains that the query is shopper intent in words and may include a budget. The description's example ('power bank under $100') reinforces this but adds no syntax or constraint information beyond the schema (e.g. the 240-character limit is only in the schema). Baseline 3 applies.

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 gives a specific verb and resource ('Search Amazon.ca') plus concrete scope: plain-language queries, up to 8 results, each with ASIN and current CAD price. The sibling check_price is not named, but the phrase 'use it when you only have a product name' implies the distinction (check_price presumably works from an identifier), so differentiation is present but indirect.

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?

It states a clear selection condition: use this when you only have a product name, which is the inverse of needing an ASIN for check_price. There is no explicit exclusion or statement of what to do when the query returns nothing, but the positive guidance is unambiguous.

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