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?

With no annotations provided, the description carries the behavioral disclosure burden. It states that prices are refreshed daily directly from dealer websites, indicating cached data rather than live queries, and explicitly includes in-stock status. It does not mention error handling or rate limits, but for a read-only listing tool the key behavioral traits are well covered.

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?

Three sentences, each with a clear purpose: what is returned, what input is accepted, and how the data is sourced. No filler or repetition. The main function is front-loaded in the first sentence.

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?

The tool has only one required parameter and no output schema, so the description must explain the return shape. It does: a ranked list of all 11 dealers with in-stock status. It also covers input format and data freshness. Minor omissions like currency or sort tie-breakers do not prevent correct usage for a straightforward price comparison 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 description coverage is 100%, so the baseline is 3. The description adds value by clarifying that 'coin' accepts either a slug or name and gives concrete examples (krugerrand-1oz-or, souverain, napoleon), which reduces ambiguity about acceptable input formats beyond the schema's generic 'Coin slug or name.'

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 provides a specific verb ('List') and resource ('all 11 tracked dealers ranked by price for a coin'), with concrete output details like in-stock status. This clearly distinguishes compare_prices from siblings such as get_best_price (which would not list all dealers) and list_dealers (which would not be coin-specific).

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: use this when you need dealer price comparisons for a specific coin. It accepts a coin slug or name with examples. However, there is no explicit guidance about when to choose this over alternatives like get_best_price or compare_coins, so the agent must infer the intended use case.

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 of behavioral disclosure. It reveals that data is refreshed daily, that results are ranked, that in-stock status is included, and that weight, purity, and country are also returned. This is solid coverage for a read-only lookup, though failure behavior is not mentioned.

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 well-structured and front-loaded: the main purpose appears in the first sentence, followed by return details, freshness, and input format. The list of dealers is long but earns its place by defining the exact scope of the search.

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, this description is complete: it explains what the tool returns, the input format with examples, the dealer universe, and data freshness. It could mention what happens when no price is found, but this is a minor gap given the tool's simplicity.

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 for the single 'coin' parameter is 100%, so the schema already explains the parameter. The description adds a small amount of value by mentioning 'name' as an alternative input and giving an additional example ('napoleon'), but it does not need to compensate for a coverage gap.

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 identifies the action (get best dealer price) and resource (a coin), specifies the exact set of dealers, and describes the returned ranked price list. It is specific enough to be understood, but it does not explicitly distinguish itself from siblings like compare_prices, so it stops short of a 5.

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 its use case: call this when you need the best dealer price for a coin and a ranked list of dealer prices. However, it provides no explicit guidance on when to prefer this tool over alternatives such as compare_prices or compare_coins, and no exclusions are stated.

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?

With no annotations, the description carries the behavioral disclosure burden. It conveys a read-only listing with optional filtering and states that output includes name and city. However, it advertises a 'name filter' that does not exist in the input schema and contains an inaccurate dealer count, which undermines confidence in behavioral accuracy.

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 core sentence is concise and front-loaded, but the exhaustive dealer enumeration is unnecessary and introduces a factual error (8 vs 9 French dealers). The added detail creates confusion without adding reliable value.

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 low-complexity list tool with one optional parameter and no output schema, the description gives the essential return fields (name and city) and the filter option. It is not fully complete because the unsupported name filter and inaccurate count could cause incorrect usage, and it does not explain behavior when no matches are found.

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 documents the only real parameter (city) with 100% coverage, so the baseline is 3. The description actively detracts from this by adding 'or name filter,' which has no corresponding parameter in the schema. This could mislead the agent into passing a nonexistent `name` argument.

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 states a clear verb ('List') and resource ('tracked bullion dealers'), and specifies the output fields (name and city), which distinguishes it from the coin/price-focused sibling tools. However, it claims '8 French' while listing nine French dealer names, so the purpose is clear but the counts are inaccurate.

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 clear context that this tool is for retrieving dealer data, but it does not explicitly mention when to use it versus alternatives or when not to use it. Usage is implied by the resource and sibling tool names, not stated directly.

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 exist, so the description carries the full transparency burden. It discloses the return format (a table with slug, name, country, metal, weight), the supported search fields, optional metal filtering, and the fact that partial matches are accepted. This conveys the key operational behavior expected by an agent.

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?

Three concise sentences, each earning its place: scope, output fields, and matching behavior. The main verb and purpose are front-loaded, and there is no redundant or vague prose.

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, the description covers input behavior, filter options, and output fields, which is especially important given no output schema. Minor omissions like empty-result behavior or case sensitivity are not critical for correct invocation.

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 descriptions are minimal ('Search term', 'Filter by metal'), but the description adds meaningful semantics: query maps to name, country, or keyword with partial-match support and concrete examples; metal takes gold/silver. This goes beyond the structured schema and helps an agent craft valid inputs.

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 ('Search'), names the resource ('the catalog of 80+ gold and silver investment coins'), and identifies search dimensions (name, country, keyword). It is clearly distinct from siblings like compare_coins, get_best_price, and get_coin_specs, which address different tasks.

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 gives clear context for when to use the tool: searching by name, country, or keyword, with an optional metal filter. Partial match examples ('maple', 'france', 'libertad') further clarify expected queries. It does not explicitly name alternative tools, but the catalog search focus versus sibling pricing/spec functions implies appropriate usage.

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