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

With no annotations provided, the description carries the burden of conveying behavior. The verb 'Get' implies a read-only operation, but no additional behavioral details such as error handling, permissions, or return shape are disclosed.

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 the target resource. There is no redundant or filler wording.

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 get-by-ID tool, the description is mostly sufficient. It lacks an explicit note about what fields are included in the detailed information and has no output schema, but the tool's simplicity reduces the need for extensive 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 already documents listing_id fully with 100% coverage. The description does not add any further meaning about the parameter beyond what the schema states, 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 uses a specific verb ('Get') and resource ('mining listing') and indicates retrieval by ID, which clearly distinguishes it from search_listings and the other list tools. The phrase 'detailed information' conveys the scope of the returned data.

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 for retrieving a single known listing by ID, as opposed to searching for listings. However, it does not explicitly state when to prefer this over search_listings or mention any 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?

No annotations are provided, but this is a read-only stats tool with no side effects expected. The description names the kind of data returned but doesn't disclose details like staleness of statistics, pagination, or whether it returns aggregate counts only. That is acceptable for a simple stats endpoint.

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?

One clear sentence, front-loaded with the purpose and useful examples, with no filler.

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 zero-parameter, no-output-schema statistics tool, the description is complete. It could mention whether the stats are real-time or cached, but the examples convey the content adequately.

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?

No parameters exist, so there is no schema burden. The description adds value by enumerating example outputs (total listings, popular commodities), which is all an agent needs to know for zero-parameter invocation.

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?

Description clearly states it gets current statistics about the Mine Market platform and explicitly lists examples (total listings, popular commodities). This is a specific verb-resource pair that distinguishes it from siblings like search_listings and get_listing_details.

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 it is the platform-level overview tool while siblings are narrower (search, details, commodity/country lists). It doesn't explicitly state when not to use it, but the scope is clear enough for an agent to select it for platform-level stats.

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 burden of behavioral disclosure. 'Get a list' implies a read-only operation and the description states the result scope ('all commodity types available'), but it does not explicitly mention whether the call has side effects, whether authentication is required, or how results are returned.

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?

A single, front-loaded sentence communicates the resource, scope, and examples without any filler or redundant phrasing. Every word contributes to the meaning.

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 (zero parameters, no output schema, no annotations), the description is nearly complete: it names the resource, the scope, and the result type ('a list'). It does not specify the exact output format, but this is a minor gap for a simple enumeration 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?

The schema has zero parameters and schema description coverage is 100%, so there is nothing for the description to add. The baseline of 4 applies because the tool requires no inputs and the description adequately conveys what will be returned.

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 ('Get a list') and identifies the exact resource ('commodity types available on Mine Market') with concrete examples. This clearly distinguishes the tool from siblings like list_countries and get_market_stats.

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 context is clear: this is the tool to use whenever the agent needs the set of available commodity types on Mine Market. It does not explicitly state when not to use it, but the sibling tools cover different resources, so the usage context is reasonably 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 or output schema exist, so the description carries the burden of behavioral disclosure. It states the inclusion criterion ('countries with mining listings') and implies a read-only listing operation, but it omits return format, ordering, or pagination behavior such as whether results are sorted alphabetically.

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 action, subject, and scope without any filler. Every word contributes necessary meaning.

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 zero-parameter, simple list operation with no output schema, the description is adequately complete: it identifies what is returned and the filtering criterion. An explicit note about return format would help, but the low complexity makes this a minor gap.

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 is empty with zero parameters, so there are no parameter semantics to document. The description correctly does not invent parameters, meeting the baseline for a no-parameter tool.

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 ('Get') and a clear resource ('list of all countries with mining listings on Mine Market'), making its purpose immediately understandable. It also naturally distinguishes itself from sibling tools like list_commodities and search_listings by naming the exact output scope.

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 explicit when-to-use guidance or mention of alternatives is present. The intended usage is reasonably implied by the simple enumeration purpose, but there is no direct guidance on when to choose this tool over list_commodities or search_listings.

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 must disclose behaviors on its own. It only says the tool searches and filters; it does not mention return format, pagination, result limits, read-only status, or any side effects. Some behavioral context is captured by the schema defaults, but the description adds little beyond the tool's name.

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 one, front-loaded sentence that clearly opens with the action and resource, then lists filter categories. It is efficient with minimal overhead, though 'and more' is slightly vague and could be replaced with concrete examples.

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?

With 8 parameters, no annotations, and no output schema, the description is the main source of high-level guidance. It covers the essential purpose and main filter dimensions, which is adequate for a basic call, but it omits information about how filters interact, what the response looks like, and whether results are paginated or limited.

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 parameters are already well documented. The description adds a high-level grouping (commodity, location, price range) and commodity examples, but does not provide additional meaning about parameter combinations, units, or edge cases. 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 states a specific verb ('search') and resource ('mining projects, tenements, and mineral properties on Mine Market'). It also mentions filtering by commodity, location, and price range. It clearly distinguishes itself from siblings by its search/filter intent, but does not explicitly name or contrast with any alternative tool.

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 for exploring and filtering listings, which is distinguishable from get_listing_details or list_commodities, but no explicit when-to-use or when-not-to-use guidance is given. The usage context is inferable but not stated.

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