BullionRadar

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

With no annotations, the description carries the full burden. It discloses the output content (specs, investment data, best price) and notes it mirrors a web page, but does not mention any read-only nature, potential network dependence for 'live' prices, or how the comparison behaves if coins are invalid. This is adequate but not rich.

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 sentence that front-loads the primary action ('Side-by-side comparison of two coins') and uses a colon-enclosed list to detail what is included. It is efficient, though the long list of fields makes it slightly dense.

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 only two parameters and no output schema, the description provides a solid high-level overview of the returned data (specs, investment data, best live dealer price). It does not explain output format or errors, but for a comparison tool with this simplicity, it is fairly 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 already provides clear descriptions for both parameters ('First coin slug' and 'Second coin slug') with 100% coverage. The description does not add any extra meaning beyond the schema, so a 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 'Side-by-side comparison of two coins' with a specific verb and resource. It enumerates the categories (specs, investment data, best live dealer price) and references the /comparer page, effectively distinguishing this from sibling tools like compare_prices or get_coin_specs by the comprehensive side-by-side nature.

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: use this when you need a side-by-side comparison of two coins. However, it does not explicitly state when to prefer this over alternatives (e.g., 'for just specs, use get_coin_specs') or provide exclusion criteria.

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 must carry the behavioral disclosure burden. It states the core behavior (listing dealers ranked by price), which conveys a read-only nature, but it doesn't specify whether the ranking is ascending or descending, whether pagination exists, or what fields are returned. The ambiguity around 'ranked' and the lack of response details are notable gaps.

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 that front-loads the action and object. There's no fluff or redundant information; it earns its place by efficiently conveying the tool's purpose.

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 tool with no output schema and no annotations, the description provides the basic purpose but leaves out critical context: the sort order (ascending/descending), the response structure, and any edge cases (e.g., no dealers found). While the simplicity mitigates the gaps, the lack of response details makes it only minimally 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 parameter 'coin' is covered by the schema with a clear description ('Coin slug or name'). The tool description adds no additional parameter semantics beyond mentioning 'for a coin.' Since schema coverage is 100%, the baseline of 3 applies, and no extra value is contributed.

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 a specific verb (list) and resource (dealers) with a clear qualifier (ranked by price for a coin). It distinguishes itself from siblings like compare_coins and get_best_price by focusing on a ranked list of all dealers, not a best price or comparison between coins.

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: when you want a list of dealers ordered by price for a specific coin. It doesn't explicitly discuss alternatives or exclusions, but the context of sibling tools provides some implied differentiation. No direct 'when to use this vs. get_best_price' guidance 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?

The description adds useful context about data sources (11 French/European dealers) and update frequency (daily), which is beyond the schema. However, because no annotations are provided, it doesn't disclose what happens if no price is found, whether the result is a single number or includes dealer details, or any other edge-case behavior.

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 extremely concise, consisting of two short sentences. It states the core purpose and key context without any redundant words, making it easy to scan.

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 one-parameter tool with no output schema, the description provides adequate context: what it does, data coverage, and freshness. It doesn't describe the return format or handling of missing data, but the simplicity of the tool makes this acceptable, though not perfect.

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 fully describes the coin parameter with examples (krugerrand-1oz-or, maple-leaf-1oz-or), so schema coverage is 100%. The description adds no additional meaning beyond 'for a coin', so it does not improve parameter understanding 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 tool returns the best dealer price for a coin and gives data source details. The verb is implicit (get/return) but the meaning is unambiguous. It differentiates from sibling tools like compare_prices by focusing on the single best price, though it doesn't explicitly contrast them.

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?

No guidance is provided about when to use this tool versus alternatives like compare_prices or search_coins. The description implies it gives the best price, but does not state exclusions or recommend when to choose it over siblings.

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 the burden. It lists return fields but doesn't disclose behavior on missing/invalid slugs, error handling, or any side effects. This is sufficient for a straightforward read operation but lacks deeper behavioral context.

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 lists all returned attributes, which is both informative and structured. While the list is long, every item serves to set expectations for the tool's output.

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 tool with a single parameter and no output schema, the description provides a thorough enumeration of fields, including niche details like French VAT rate and liquidity score. It lacks mention of error handling for unknown coins, but the field list makes the tool's behavior largely predictable.

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 schema already fully describes the sole parameter 'coin' with examples. The description adds context that it's for gold or silver investment coins, reinforcing the parameter's semantic domain, but it doesn't introduce additional syntax or format details.

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 defines the tool as providing a full data sheet for a gold or silver investment coin, listing specific attributes like weight, purity, and mintage. This distinguishes it from siblings like compare_prices or list_dealers, which serve different purposes.

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 for retrieving comprehensive specs for a single coin. It doesn't explicitly name alternatives or exclusions, but the context is clear and the sibling names (e.g., compare_prices, search_coins) make when to use this tool unambiguous.

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 the burden. It discloses that only 'tracked' dealers are listed and that there is an optional city filter, but it does not mention return format, ordering, case sensitivity, or whether the filter is exact/partial. This is adequate for a simple list tool but leaves some behavioral gaps.

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, front-loaded with the action and resource, and contains no filler or redundant information. Every 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?

For a simple list tool with one optional parameter and no output schema, the description adequately covers purpose and the main variant (filter by city). It could mention return format or exact-match behavior, but these are not critical for such a straightforward operation.

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% — the parameter is described as 'French city name to filter.' The description adds 'Optional' and repeats 'filter,' but does not provide additional meaning beyond the schema. 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 uses a specific verb ('List') and a clear resource ('tracked coin dealers'), and mentions an optional filter ('city'). This clearly distinguishes it from sibling tools, which all focus on coins and prices rather than dealers.

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 clearly implies when to use this tool: whenever the agent needs to list tracked dealers, optionally narrowed by city. No alternative listing tool exists among siblings, so no explicit when-not or alternative is required, but context is clear.

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 full responsibility for behavioral disclosure. It only states what the tool does (search) without revealing any behavioral details such as return format, pagination, filtering behavior, or whether it is read-only/safe. This is a significant gap for a search tool.

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 clear sentence that front-loads the action and purpose. No wasted words, and all essential information is present without excessive detail.

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 two-parameter search tool with a 100% schema description, the description is mostly complete for its complexity. However, it lacks any guidance on usage context or return behavior, and without annotations, the agent has to infer important details, slightly reducing completeness.

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?

Although the schema already describes both parameters with 100% coverage, the description adds meaning by clarifying what the 'query' parameter accepts (name, country, or keyword), which goes beyond the schema's generic 'Search term.' This enriches the 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 clearly states the tool searches coins by name, country, or keyword. The verb 'search' plus the resource 'coins' and the search criteria make the purpose specific and distinguishable from sibling tools like compare_coins or list_dealers.

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 the tool is for finding coins based on search terms, but provides no explicit guidance on when to use it versus alternatives like compare_coins or get_coin_specs. No exclusions or alternative recommendations are given.

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