CompareFairly

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

With no annotations provided, the description carries the burden of behavioral disclosure. It discloses the detailed response contents, neutrality policy, and localization behavior. It does not mention error handling or data freshness specifics, but for a straightforward read operation, the disclosure 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?

The description is two sentences, front-loaded with the primary action and a detailed list of returned data. Every sentence adds value: the first specifies the tool's output and scope, the second conveys policy and localization. No filler 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 has 3 parameters, no output schema, and no annotations, the description provides a solid overview of what is returned and the localization behavior. It lacks explicit error conditions or response format details, but for a single-item fetch tool, the description is reasonably 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%, so parameters are well-documented in the schema. The description adds value by explicitly connecting lang/country to localization and clarifying that slug is from search_comparisons, enhancing the semantic meaning beyond the raw 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 tool fetches one full structured comparison, enumerating the contents (scores, sub-scores, per-criterion values, badges, sources, flags, freshness). This distinguishes it from siblings like search_comparisons (searching) and list_categories (listing categories), making the purpose unmistakable.

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 usage context by mentioning the slug comes from search_comparisons, indicating this tool is for retrieving a specific comparison after searching. It also adds a usage caveat (neutral ranking, never paid) but does not explicitly state when not to use it or provide exclusions.

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, the description must carry transparency, and it does by stating it lists categories and includes comparison counts. This implies a read-only operation and conveys the output scope. However, it does not disclose additional details like pagination or exactness of counts, which would enrich transparency.

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, front-loaded sentence that conveys the core purpose and an additional detail (counts). Nothing is wasted, making it highly concise and well-structured.

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 simple listing tool with two optional parameters and no output schema, the description provides adequate context by specifying the action, resource, scope ('market'), and included counts. It could mention how parameters define the market, but the schema covers them, so the overall completeness is strong.

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%, with both lang and country already described with defaults. The description adds no parameter-specific meaning beyond the schema, which is acceptable given the high coverage. Baseline 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 tool lists top-level categories for a market and includes counts, using a specific verb ('List') and resource ('categories'). It distinguishes itself from siblings by focusing on category listing rather than searching or fetching comparisons.

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 is implied through the description's clear purpose, but there is no explicit guidance on when to use this tool versus alternatives like search_comparisons or get_comparison. No exclusions or contexts are mentioned, so it's adequate but minimal.

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 present, so the description carries the full burden. It discloses the return fields ('title, slug, url, json_url, popularity') and the 'neutral, sourced' nature of the results. It does not mention error handling or rate limits, but for a simple search tool, the behavior is adequately transparent and not misleading.

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 resource, followed by return information and a clear usage directive. Every word contributes meaning; there is 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?

For a 4-parameter, low-risk search tool with no output schema and no annotations, the description covers the essential context: what it does, what it returns, and how it connects to get_comparison. It does not detail edge cases (empty results, pagination), but the description is sufficiently complete for an agent to invoke the tool correctly.

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%, so the baseline applies. The description adds context by explaining the output includes a slug used with get_comparison, which makes the query's purpose clearer, but it does not elaborate on parameter usage beyond the schema definitions. The schema already provides sufficient parameter semantics.

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 uses the specific verb 'Search' with a clear resource ('CompareFairly's catalog of neutral, sourced comparisons') and explicitly differentiates from the sibling tool get_comparison by directing the user to 'use this first to find the exact slug'. This makes the tool's unique role immediately clear.

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?

Provides explicit usage guidance: 'Use this first to find the exact slug, then call get_comparison.' This clearly indicates when to use the tool and how it fits with a sibling tool, fulfilling the criterion of explicit workflow context even without listing when-not-to-use scenarios.

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