CompareFairly

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

No annotations provided, so the description carries full burden. It discloses key behaviors: neutral ranking, never paid, localized data. It doesn't cover auth or error conditions, but for a read-only tool this is adequate.

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 efficiently convey the tool's output and key quality notes without unnecessary detail. No fluff or redundancy.

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 tool's simplicity and 100% schema coverage, the description fully covers what the tool returns and its important attributes (localization, neutrality). No output schema is needed as the description enumerates content.

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 has 100% coverage, so baseline is 3. The description adds context that data is localized to lang/country, reinforcing the parameters, but doesn't significantly extend their meaning beyond the schema.

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 'Fetch one full structured comparison' and lists all included data elements, making the tool's purpose explicit. It distinguishes from siblings like 'search_comparisons' by implying this is for a single comparison by slug.

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 context on when to use (fetching a single comparison) and notes neutral ranking and localization. It doesn't explicitly exclude alternatives, but the purpose is clear enough to guide selection.

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?

No annotations are provided, so the description carries full burden. It only states the basic function (listing categories with counts) and does not disclose any behavioral traits such as performance, authentication needs, rate limits, or lack of side effects. For a read operation, transparency is minimal.

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 a single, concise sentence of 14 words. It is front-loaded with the essential information and contains no redundant or extraneous content.

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 that there is no output schema, the description partially compensates by stating the return includes category names and comparison counts. However, it does not describe the return format (e.g., array of objects) or any potential edge cases. It is adequate but not 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?

The input schema has 100% coverage, with descriptions for both parameters (lang and country). The tool description does not add additional meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

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 the action (list), the resource (top-level categories), the context (for a market), and includes what is returned (number of comparisons). It distinguishes from siblings like get_comparison and search_comparisons by specifying the scope and return value.

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 implies this tool is used to retrieve a list of categories for a market, but it does not provide explicit guidance on when to use it versus alternatives (e.g., when to use get_comparison instead). No 'when not to use' or explicit context is given.

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?

With no annotations provided, the description carries the full burden. It describes the return fields and mentions 'neutral, sourced comparisons', but does not disclose behavioral traits like idempotency, rate limits, authentication needs, or what happens with empty results. It adds moderate value beyond the schema.

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 two sentences, front-loaded with the action and output, followed by workflow guidance. Every sentence adds value with no redundancy or wasted words.

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 no output schema, the description explains the return fields (title, slug, url, json_url, popularity). However, it does not clarify how 'market' relates to lang and country parameters, or mention default behavior when no query is provided. Overall adequate but missing some context.

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?

The input schema has 100% description coverage for all 4 parameters, so the description does not need to add much. The description hints at the query being free-text and mentions 'market' which is implied by lang and country, but does not provide additional meaning beyond the schema.

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 the action ('Search CompareFairly's catalog') and the resource ('neutral, sourced comparisons for a given market'), and it specifies the returned fields (title, slug, url, json_url, popularity). It distinguishes itself from siblings by explicitly directing to use this tool first to get a slug for get_comparison.

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 explicit workflow guidance: 'Use this first to find the exact slug, then call get_comparison.' This clearly indicates when to use this tool vs. its sibling get_comparison. However, it does not mention when to avoid using it (e.g., when slug is known) or how it relates to list_categories.

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