Australian Manufacturing Directory

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

With no annotations, the description carries the full burden. It discloses that the operation is a read-style retrieval of contact details and that API key validity is required. It does not mention failure modes, rate limits, or response format, but the core behavior is stated.

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 compact sentences with no wasted wording. The key constraint ('Paid Business-plan tool') is front-loaded, and the subscription link is provided efficiently.

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 2-parameter read tool with no output schema, the description covers purpose, prerequisites, subscription path, and the data returned. It is complete enough for an agent to invoke correctly, with minor gaps around expected response shape.

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 the schema already documents both parameters ('abn' and 'api_key'). The description adds the 'active Business-plan API key' nuance and confirms the retrieved fields, but does not significantly expand parameter 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?

States a specific verb ('retrieve') and resource ('phone, email and street address'), clearly identifying the tool as a contact-details lookup. It does not explicitly name sibling tools, but the scope is distinct enough from get_manufacturer_profile and search_manufacturers.

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?

Clear prerequisite context is given: it is a paid Business-plan tool requiring an active API key, with a subscription link. It does not explicitly discuss when to choose this over the sibling tools, but no exclusion guidance is needed for such a focused lookup.

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 discloses the key behavioral trait that the profile is non-contact and uses 'retrieve' implying a read-only operation. However, it doesn't specify error handling, return format, or any side effects, which for a simple get is acceptable but not deep.

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, well-structured sentence that front-loads the purpose, immediately notes the non-contact nature, and then names the alternative. There is zero filler, making it highly efficient.

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 single-parameter retrieve with no output schema, the description provides sufficient context: what it returns (a non-contact profile), the required input (ABN), and where to get contact details. It could list specific profile fields, but that's not essential 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 input schema already documents the single parameter 'abn' with a description and pattern. The description repeats 'using an Australian Business Number' without adding any additional meaning or usage details beyond the schema, so it adds no value above the structured definition.

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 verb 'retrieve', the resource 'non-contact company profile', and the required input (ABN). It also distinguishes itself from get_contact_details by explicitly saying it is non-contact, making its purpose unambiguous.

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?

It explicitly points out that contact details (phone, email, street address) are available through the paid get_contact_details tool, giving a clear alternative and condition. This is a precise when-to-use-this versus when-to-use-that instruction.

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 explaining behavior. It clearly communicates the read-only nature and the expected result: a list of categories with company counts. It does not discuss ordering, pagination, or data freshness, but for a simple parameterless listing tool the description is reasonably transparent.

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 resource, then adds the key output detail. Every phrase earns its place with no unnecessary 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, read-only listing tool, the description is mostly complete: it names the categories and the count returned per category. It lacks explicit return-format details, but the low complexity and absence of parameters mean an agent can reasonably infer how to invoke it. The tool is simple enough that the description covers the essential 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 tool has zero parameters, so there is no parameter detail for the description to add. The baseline of 4 applies here, and the description appropriately focuses on the output rather than 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 clearly states the verb ('List') and the specific resource ('ANZSIC manufacturing categories'), and adds the distinguishing output of company counts per category. This separates it from the sibling tools, which focus on individual contacts, profiles, or searching manufacturers.

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 getting a high-level aggregate view of categories and company counts, rather than individual manufacturer details. However, it does not explicitly say when to choose this over search_manufacturers or get_manufacturer_profile, and it offers no exclusions or alternative routing.

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 honestly discloses that export_ready is a non-filtering forward-compatibility placeholder, which is valuable. But it does not describe the return shape, result limits/ordering, or other behavioral characteristics an agent might need.

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 tightly written sentences with no filler. The main function is front-loaded, and the second sentence earns its place by flagging an important non-obvious parameter behavior.

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 schema is rich and covers all parameters, which makes the tool callable. However, with no output schema and no annotations, the description does not describe the expected return value or provide any routing guidance between search and the sibling get/details tools.

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 little beyond the schema: it groups category and state as primary search criteria and repeats the export_ready caveat already present in the schema. No significant new parameter meaning is introduced.

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 ('Find'), a clear resource ('Australian manufacturers'), and the main filtering dimensions ('ANZSIC category and state'). It clearly differentiates this search tool from sibling tools like get_manufacturer_profile or list_categories, which have narrower 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 intended use is implied clearly by the description, and the schema adds the important tip to call list_categories first for valid category values. However, the description itself does not explicitly contrast this tool with alternatives or state when not to use it.

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