Depureco Industrial Vacuum Explorer

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

No annotations are provided, so the description must fully explain behavior. It fails to disclose what the tool returns (e.g., product IDs vs full product data), whether it requires canonical slugs from getFilterOptions, or if it performs any side effects. The 'configure' name suggests mutation, but description indicates search, creating ambiguity.

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 brief and front-loaded, but for a tool with 15 optional parameters and no output schema, it is under-specified. The example is valuable, but the structure lacks necessary detail about parameter combinations or return format.

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 complexity (15 optional filters, no output schema, no annotations), the description is insufficient. It doesn't explain the return value, how filters are combined, or how the natural-language example maps to structured parameters. This leaves significant ambiguity for an AI agent.

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 baseline is 3. The description itself adds no parameter-specific meaning, though the example query hints at natural-language usage. Parameters like 'power' refer to getFilterOptions values, but this is only in the schema, not the main description.

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 finds products matching a need, with concrete examples. It distinguishes from sibling tools that fetch filter options, though it doesn't explicitly differentiate. The name 'configureProduct' is slightly misleading, but the description resolves it.

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 guidance on when to use this tool vs alternatives. The examples imply use cases but don't explain prerequisites like fetching filter options first, or mention that getProductData is for retrieving product details. No exclusions or alternative tool references.

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 full burden for behavioral disclosure. It provides domain context (vacuumable materials) and examples, but no operational details such as return behavior, filtering semantics, or whether results are sorted/curated. It does not explain how search or includeEmpty affect behavior beyond their schema descriptions.

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 very short and has no filler, which is positive, but it is under-specified. It reads more like a vague list of examples than a clear tool description. It earns points for efficiency but loses for clarity.

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 no output schema and no annotations, the description should provide a fuller picture. It lacks an explicit statement of what is returned, what an 'application' is, or any usage context. The examples help, but the tool is not self-contained enough for an AI agent to invoke confidently.

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 schema already provides clear meanings for both parameters. The description adds no parameter-specific information. Baseline 3 is appropriate since the description and schema together cover the parameters adequately.

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 implies the tool returns materials that can be vacuumed, with examples, but it never explicitly states an action like 'get' or 'list.' The name 'getApplications' helps, but the description alone is vague about what an 'application' is versus the material examples. It partially distinguishes from siblings by focusing on vacuumable materials, but lacks a clear verb+resource statement.

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 on when to use this tool instead of siblings like getProductCategories, getUsages, or getSectors. The description gives no context about typical use cases or when to prefer a sibling tool. This is a clear gap.

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 describes the tool as providing guidelines and instructs to call it first, implying it is a safe, read-only operation. However, it does not explicitly state that it has no side effects or whether it returns static content, leaving some ambiguity.

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 that front-load the critical instruction to call first. Every word earns its place, and there is no redundant information.

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 (no params, no output schema, no annotations), the description is sufficient for an agent to understand its purpose and priority. It does not describe the format or content of the guidelines, but for an operational-instruction tool, this is 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 has no parameters (0 params, 100% schema coverage), and the description correctly adds no parameter information. Per the rubric, a baseline of 4 is appropriate when there are no params and the schema is complete, so the description does not need to compensate.

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 tool as providing 'operational guidelines for the AI,' which is a specific resource distinct from sibling tools that retrieve product-related data. The verb 'get' is implicit in the tool name, and the description conveys the core purpose without ambiguity, though it does not explicitly state the action.

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 instruction 'Call first' provides explicit guidance on when to use this tool, indicating it should be invoked before other tools. This is a clear usage directive, but it does not mention any alternatives or conditions for when not to use it, which would be unnecessary given its unique role.

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 behavior. It only gives a noun phrase and examples, but does not explain how filtering works, whether includeEmpty affects results, or what the return structure looks like. This is minimal behavioral disclosure.

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, with two short sentences and useful examples. Every word contributes to the basic purpose, with no redundancy. It lacks depth, but the efficiency is well-executed.

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 simplicity of the tool (two optional params, no output schema), the description is too sparse. It does not explain what 'available' refers to in the product context, nor does it mention the search filter's effect. The absence of annotations places a higher burden on the description, which it fails to meet.

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 provides 100% coverage of both parameters (search and includeEmpty) with clear descriptions, so the description does not need to add parameter details. The description adds no extra meaning but does not hurt either, earning the baseline score.

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 indicates the tool returns certifications, with concrete examples (CE, Atex, Type H dust). It distinguishes itself from sibling getter tools by focusing on the specific resource 'certifications'. However, it lacks an explicit verb like 'lists' or 'fetches', making it slightly less direct.

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 on when to use this tool versus sibling tools or how the search parameter affects results. The description simply states what is available, without any contextual instructions.

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 full burden of behavioral disclosure. It does not mention filtering, pagination, ordering, or whether empty terms are included by default, despite the includeEmpty parameter hinting at such behavior. The description only gives example values, leaving the tool's behavior opaque.

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, front-loading the core subject ('Container capacities') and using a compact example to clarify the returned value format. It wastes no words, though it could arguably be slightly more explicit about the return type.

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 filtered list tool with full schema descriptions, this description is minimally sufficient. It lacks an explicit statement of what is returned (e.g., a list of strings) and how the includeEmpty parameter affects output, but the schema partially compensates. The absence of an output schema and annotations leaves some gaps, but the tool's simplicity lowers the required 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?

The schema already provides 100% coverage for both parameters with clear descriptions ('Optional text filter' and 'If true, include terms with no published products'). The tool description adds no additional parameter-level detail, so the baseline 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 clearly identifies the resource ('Container capacities') and provides examples of the values returned, which distinguishes it from sibling tools like getProductTypes or getSectors. However, it lacks an explicit verb in the description, relying on the 'get' prefix in the name to imply retrieval.

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 fetching container capacity ranges, but it does not explicitly state when to use it over alternatives. No usage context or exclusions are provided, requiring the agent to infer from the name and examples.

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 full behavioral disclosure burden, but it only provides example values and no information about safety, return behavior, filtering defaults, or side effects. The description does not contradict annotations (none exist), but discloses zero behavioral traits.

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 short phrase plus examples, with no wasted words. It is front-loaded with the resource name and examples, though it could have used the space to include a verb or usage hint without becoming verbose.

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 no output schema and no annotations, the description is under-specified: it does not state what is returned, how it is filtered, or how it relates to the surrounding configuration tools. The schema covers parameters, but the overall context is incomplete.

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 100% coverage of both parameters ('search' and 'includeEmpty'), each with a description. The tool description adds no parameter-specific information, so the baseline score of 3 applies.

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 identifies the resource as 'Collection systems' with concrete examples, but lacks an explicit verb or statement of what the tool does beyond the name. It is clearer than a tautology due to examples, but does not clearly distinguish its retrieval action from sibling lookup tools.

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?

There is no guidance on when to use this tool versus alternatives like getCollectionCapacities or getProductTypes. The examples imply it is for checking collection system options, but no explicit context, prerequisites, or exclusions are provided.

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 full burden of behavioral disclosure. It does not state whether this is a read-only lookup, what the default filtering behavior is, or how results are returned. The only behavioral hint (includeEmpty) is in the schema, not the description.

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, with no wasted words. The examples are useful and front-loaded. It is a fragment rather than a full sentence, but for a simple lookup tool, it is 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 simple reference tool with no output schema or annotations, the description is too sparse. It does not explicitly state what the tool returns overall or how it relates to the product configuration context, leaving the agent with incomplete information.

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% for both parameters, so the schema already documents them clearly. The description adds no parameter-specific meaning, though the examples imply what search values might look like, which is marginal value.

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 is a noun phrase 'Filter cleaning' with examples rather than a clear statement of action. It implies the tool retrieves filter cleaning systems, but does not explicitly say 'list' or 'get'. It distinguishes the subject from siblings through examples like 'manual, Jet Clean, automatic backflush'.

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 on when to use this tool instead of the many sibling get* tools, nor any prerequisites or exclusions. The description lacks any contextual usage cues, making it hard for an agent to know when to select it.

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 full burden of behavioral disclosure. It does not explicitly state that the tool is read-only, what the output structure looks like, or any side effects. The phrase 'Available product search criteria' implies a list is returned, but the lack of return format and safety information leaves a significant transparency gap.

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 main purpose and includes a clear usage instruction. It is concise, with no redundant information, and every clause serves a distinct function.

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 description explains the tool's purpose and usage directive, which is acceptable for a simple tool with optional parameters. However, without an output schema or annotations, it does not describe the response structure or safety profile. The description is adequate but leaves some contextual gaps that the agent must infer.

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 has 100% description coverage for both parameters, so the baseline is 3. The description adds some context by listing the categories (materials, sectors, etc.) that the 'search' parameter filters over, but it does not add specific parameter semantics beyond the schema and does not mention 'includeEmpty' at all.

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 provides available product search criteria, listing examples like materials, sectors, and certifications. It also explicitly directs the agent to call it before configureProduct, distinguishing it from sibling tools that fetch individual data categories.

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 a clear usage directive: 'Call before configureProduct.' This provides a strong temporal context for when to use the tool. However, it does not mention alternatives or exclusions, but the sequential guidance is sufficient for basic usage.

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, and it fails. It only names the data returned, with no mention of filtering behavior, inclusion/exclusion of empty results, return structure, or side effects. The description is essentially a fragment that tells the agent nothing about how the tool behaves.

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 very short and free of fluff, which is conciseness in a limited sense. However, it is under-specified to the point of being terse, resembling a title or label more than a helpful explanation. It is not structured with front-loaded key information; it simply lacks substance.

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 getter with two optional parameters, the description should still explain what the returned values are (e.g., a list of terms, numeric values) and how the parameters affect results. The output schema is absent, so the description must cover return semantics, but it only states units. The tool's behavior around 'includeEmpty' and 'search' is undocumented, leaving the agent without enough 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 provides 100% coverage with descriptions for both 'search' and 'includeEmpty', so the baseline for this dimension is 3. The description adds no extra semantic meaning to the parameters, but it doesn't need to since the schema already documents them. No contradiction or significant gap exists here.

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 the resource ('motor power values') and units ('kW/HP'), which gives some indication of what the tool returns. However, it lacks a verb like 'get' or 'list', making it more of a label than a clear statement of purpose. It does somewhat distinguish from sibling tools like getPowerValues by specifying 'motor', but the intent is still vague.

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?

There is no guidance on when to use this tool versus alternatives such as getPowerValues or getTechnicalSpecs. The description does not mention the 'search' or 'includeEmpty' parameters, nor any context for when this tool is appropriate. This is a clear gap in usage guidance.

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, and the description does not disclose behavioral traits such as whether results are filtered by search, how includeEmpty affects output, or the data structure returned. The phrase 'Available power supplies' only hints at a read-only listing, but important behavior is left unstated.

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 with no filler words. The examples are useful and compact. However, it is so brief that it omits guidance that could fit without bloating the text.

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 no output schema and no annotations, the description carries the burden of explaining what the tool returns and how behavior changes with parameters. It only provides a vague resource label and examples, leaving the return format and the effect of includeEmpty/search unclear.

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 descriptions already fully document both parameters ('Optional text filter' and 'If true, include terms with no published products'), so the description adds no extra parameter context. The examples indirectly inform search content but do not clarify parameter semantics 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 states 'Available power supplies' with concrete examples (electric, compressed air, battery), making it clear the tool returns a list of power supply types. It lacks an explicit verb, but the tool name supplies that. It partially distinguishes from siblings like getPowerValues via examples, though not fully.

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 given on when to use this tool versus alternatives such as getPowerValues or getMotorPowerValues. There are no exclusions, prerequisites, or context clues about typical usage scenarios.

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 full burden of disclosing behavioral traits. The description only states a nominal phrase and gives no information about whether the tool reads, writes, or performs side effects, nor about return formats, filtering behavior, or required permissions. This is a significant gap.

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 very short, but this is under-specification rather than effective conciseness. It is not structured as a clear function description and lacks essential details. Every word should earn its place, but here the words do not convey enough useful information.

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 no annotations and no output schema, the description is completely inadequate. It does not explain what the tool returns, how to use it, any prerequisites, or how it relates to the overall domain. Even though the parameter count is low, the description fails to provide enough context for an agent to select and 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?

The input schema covers both parameters with descriptions ('Optional text filter' and 'If true, include terms with no published products'), so schema coverage is 100%. The description adds no additional parameter meaning, but the baseline of 3 is appropriate because the schema already documents the parameters adequately.

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 'Total product power ranges' is a noun phrase rather than a verb phrase, so it fails to clearly state what action the tool performs. It hints at the subject matter (power ranges for products) but does not say whether it retrieves, calculates, or configures such ranges. It also does not distinguish this tool from sibling 'getMotorPowerValues'.

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?

There is no guidance on when to use this tool versus alternatives. The description makes no mention of specific use cases, scenarios, or exclusions. Sibling tools like getMotorPowerValues could overlap, but the description provides no differentiation.

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 full burden of disclosing behavior. It only mentions that accessories come with codes and images, but does not clarify that results are filtered by productId, the response structure, pagination, or any potential limitations. This is minimal at best.

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 short sentence with an example, no filler words, and the core concept is front-loaded. It earns its place and is appropriately concise for a simple get tool.

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 tool with one parameter and no output schema, the description is somewhat complete but leaves out the crucial connection that the returned accessories are tied to the provided productId. It also does not mention the output format, but for a straightforward read tool it is minimally viable.

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 description for productId is 100% covered (states numeric ID, product title, or slug), so the baseline is 3. The description does not add any meaning about how productId affects the results; the relationship is implied by the tool name but not explicitly stated.

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 identifies the resource (accessories) and gives concrete examples (antistatic kits, lances, brushes), which makes it clear the tool returns accessory information. The verb 'get' is present in the tool name, and the description distinguishes it from sibling tools by focusing specifically on accessories, though it does not explicitly state 'returns' or 'lists'.

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?

There is no guidance on when to use this tool versus alternatives such as getProductData or getFilterCleaningSystems. No prerequisites, exclusions, or scenarios are mentioned, leaving the agent to infer usage purely from the name and description.

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 full burden of behavioral disclosure. It gives no information about return values, side effects, permissions, or how the search/includeEmpty parameters affect results. The only behavioral hint is implicit in the tool name, not in the description.

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 short and free of fluff, which is concise, but it is under-specified rather than efficiently complete. It lacks a verb and clear structure, making it not fully successful as a description of the tool's function.

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 tool with 2 optional parameters and no output schema, the description should at least state that it lists available product safety categories and how the parameters filter results. It doesn't—it merely labels the resource. This leaves a significant gap for an agent trying to decide whether to invoke it.

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 provides complete descriptions for both parameters (search, includeEmpty), so the baseline is 3. The description adds no parameter-specific semantics but gives example category values (ACD, Atex 1/2D, etc.) that offer domain context. It doesn't go 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 'Product safety categories' is a noun phrase with examples but lacks an explicit verb like 'list' or 'retrieve'. It adds the qualifier 'safety' and example values, which is slightly more than a tautology, but it doesn't clearly state the operation. The tool name 'getProductCategories' implies retrieval, but the description alone is vague.

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?

There is no guidance on when to use this tool or how it relates to sibling tools such as getProductTypes or getApplications. The description does not mention any filtering use case, prerequisites, or alternative tools, leaving the agent without context for selection.

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 burden of behavioral disclosure. It lists the data content but does not explicitly state that this is a read-only operation, mention required permissions, or outline behavior for invalid product IDs. The scope of returned data is described, but safety and error behavior remain implicit.

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 is front-loaded with the key information and includes a concrete example. Every word earns its place, and it is appropriately sized for the tool's simplicity.

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, the description gives a reasonable outline of return contents (description, features, options, accessories, manuals). It lacks detail on the response structure or error handling, but given the simplicity, it is mostly 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 schema already provides 100% parameter documentation, including the example 'PUMA ACD' and accepted formats. The description merely repeats the example without adding any new semantic meaning, so it adds no value 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's purpose: retrieving a full product sheet including description, standard features, options, accessories, and manuals. It distinguishes this tool from siblings like getProductAccessories or getTechnicalSpecs by emphasizing the comprehensive 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?

The description implies use when a complete product data package is needed, but does not explicitly state when to prefer specialized alternatives. The phrase 'Full product sheet' provides clear context, but no exclusions or alternative 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?

No annotations are provided, and the description is purely definitional with examples. It does not disclose behaviors such as whether the list is exhaustive, whether it includes unpublished types, or any filtering/pagination behavior beyond the schema parameters.

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 very short and front-loaded, but it is under-specified. It consists of a fragment and examples, which is not a complete sentence describing the tool's purpose. It is concise but not appropriately informative.

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 no output schema, no annotations, and only a fragment-like description, the tool is incomplete contextually. It does not explain what the return value looks like, how the search parameter behaves, or what 'published products' means in relation to includeEmpty.

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% (both 'search' and 'includeEmpty' are described in the schema), so the baseline is 3. The description does not add any additional meaning beyond the schema, but it does not need to compensate for missing schema documentation.

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 'Product types. E.g.: mobile vacuum, fixed dust collector, pre-separator.' is essentially a noun phrase that restates the tool name without a verb. The examples provide some clarity about what the tool returns, but it does not explicitly say 'gets' or 'lists' product types, and it does not distinguish this tool from sibling tools like getProductCategories.

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?

There is no guidance on when to use this tool versus alternatives. The sibling tools include getProductCategories and getProductData, but the description gives no context about the distinction or when to prefer this tool.

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 does not mention that includeEmpty affects whether empty sectors are returned, nor does it describe the output format, pagination, or any read-only guarantees. The description is purely a noun phrase and provides no behavioral traits beyond the existence of the list.

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 short sentence fragment with meaningful examples, containing no fluff. It is concise, though slightly under-specified, but still efficient for the low complexity of the tool.

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?

Despite the low complexity and schema coverage, the description leaves critical gaps: no indication of what the returned data looks like, how filtering works, or how includeEmpty changes results. For an AI agent to invoke correctly, more context is needed.

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 cover both parameters ('Optional text filter' and 'If true, include terms with no published products') with 100% coverage. The description adds only illustrative examples, not additional parameter semantics, so the 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 'Industrial sectors. E.g.: food, pharmaceutical, 3D printing, metalworking.' names the resource (industrial sectors) and provides concrete examples, but lacks an explicit verb like 'returns' or 'lists'. It is clear enough to infer a read-only list operation, but does not articulate a specific action or 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?

There is no guidance on when to use this tool versus the many sibling get* tools (e.g., getProductCategories, getUsages). No context for typical use cases or alternatives is provided.

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 full responsibility for behavioral disclosure. It merely defines 'product structure' as 'mobile or fixed' but does not explain what the tool does, what it returns, or any side effects. This is a severe lack of 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 extremely short, but this is under-specification rather than effective conciseness. A single fragment 'Product structure: mobile or fixed' does not provide enough substance to be considered well-structured. It is not front-loaded with useful information.

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 absence of an output schema and the simple parameter schema, the description must explain what the tool returns. It only hints at a classification ('mobile or fixed') but leaves out key details such as the format of results, whether it lists all structures, and how filtering works. The description is insufficient for an agent to use 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?

The schema descriptions for 'search' and 'includeEmpty' are complete (100% coverage), so the baseline is 3. The description adds no additional meaning about how these parameters relate to 'mobile or fixed', but it does not contradict the schema. Thus it neither helps nor harms parameter understanding.

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 'Product structure: mobile or fixed' is a noun phrase without an explicit verb. It does not clearly state that the tool retrieves or lists structures, making the purpose vague. It also does not distinguish itself from sibling tools like getProductTypes or getSectors.

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. There is no mention of context, prerequisites, or exclusions. The description gives no indication of 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, the description carries the full behavioral disclosure burden. It lists data types but does not disclose return format, error behavior, authentication needs, or any other behavioral traits. The implied read-only nature is not enough to score higher.

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 compact sentence that is mostly efficient, but the word 'Precise' is filler and adds no functional value. It is concise and front-loaded, but not maximally lean.

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 single-parameter schema is fully documented, and the description lists the returned data categories. However, with no output schema or annotations, the description does not explain response structure or how this tool fits alongside siblings, leaving only adequate context for selection and 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?

Schema description coverage is 100% for the single parameter, productId, which already documents accepted formats (numeric ID, exact product title, or slug). The description adds no input semantics, so the baseline 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 clearly identifies the tool as returning technical specifications and enumerates specific data fields (power, airflow, vacuum, filter, dimensions, weight, Atex marking). It uses a clear verb+resource structure, but does not explicitly distinguish it from related tools like getPowerValues or getProductData.

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 on when to use this tool versus alternatives such as getPowerValues, getMotorPowerValues, or getProductData. The description implies a consolidated technical data lookup but lacks explicit context, prerequisites, or 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 present, so the description carries the full burden of behavioral disclosure. It does not mention what the tool returns, whether it is read-only, or any side effects. The description is essentially non-informative about 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 one short fragment, but it is under-specified rather than genuinely concise. It does not earn its place because it provides minimal useful information about 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?

The tool lacks an output schema and the description is extremely minimal. It fails to provide essential context such as what the tool returns, the meaning of 'usages', or how it relates to the many sibling tools, making the description inadequate.

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 input schema fully documents 'search' and 'includeEmpty'. The description adds no further parameter meaning, so the baseline score of 3 applies.

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 'Usage mode: occasional or continuous' gives some domain context but lacks an explicit action verb or resource. It vaguely implies the tool retrieves usage modes, but the purpose must be inferred from the tool name rather than stated clearly.

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?

There is no guidance on when to use this tool compared to siblings like getProductData or getTechnicalSpecs. No context, exclusions, or alternatives are provided.

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 for behavioral disclosure. The description provides no explicit behavior—it does not state that the tool returns a list, how results are filtered, or whether there are any side effects. The noun phrase 'Certified Atex zones' hints at the resource but does not describe operational 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—a single noun phrase plus clarifying examples. It contains no unnecessary words and is immediately clear about the core resource. Despite being brief, it earns its place by giving domain context and 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?

The tool is simple, but the description is too sparse for full completeness. There is no output schema, no annotations, and no explanation of the return format or underlying behavior. The description only identifies the resource and examples, leaving operational details unspecified.

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 input schema already documents 'search' as an optional text filter and 'includeEmpty' as controlling inclusion of empty terms. The description adds no parameter information; therefore, the baseline score of 3 applies.

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 tool's name getZoneTypes and description 'Certified Atex zones' clearly identify it as a retrieval operation for Atex zone type enumerations. The examples (zone 22, zone 21, ordinary) add specificity and help distinguish it from sibling tools like getApplications or getProductCategories. However, the description lacks an explicit verb and only refers to the resource indirectly.

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: if you need certified Atex zone types, this is the tool. It does not provide explicit when-to-use guidance or mention alternatives, but the sibling tools are all for different entities, so the context is fairly clear. No exclusions or exception cases are mentioned.

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