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

No annotations are provided, so the description must carry the full behavioral burden. 'Get' implies a read operation, but the description does not disclose permissions, pagination, rate limits, return format, or what 'coverage' actually represents, leaving significant ambiguity for a data-retrieval tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence with no wasted words and is front-loaded. However, for a tool with four parameters and a non-obvious domain concept, it is too terse to be considered well-structured guidance.

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 four parameters, no annotations, no output schema, and no required parameters, the description is not complete enough. It does not explain what the response contains, how seller coverage is defined, or how the optional filters interact.

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 documents brand, limit, sellerId, and minRevenue. The description adds no parameter semantics beyond what the schema provides, which establishes the baseline of 3.

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 gives a verb ('Get') and a resource area ('seller coverage information for brands'), so the general purpose is identifiable. However, 'coverage information' is vague and the description does not distinguish this tool from sibling brand tools like smartscout_brand_details, smartscout_brand_growth, or smartscout_brand_search.

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, when not to use it, or which sibling tool to choose instead. The agent is left to infer from the name alone that this tool relates to brand-level seller coverage.

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 the operation is read-only, what 'detailed information' includes, pagination, rate limits, or error behavior. It only implies a read via 'Get'.

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 with no filler. It is appropriately sized for a short description, though it is terse. Structure is fine.

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 annotations and no output schema, the description should explain return values or usage context, but it does not. It also fails to differentiate from closely related brand tools, leaving the agent unable to confidently choose or use it correctly in context. Incomplete for the tool's complexity.

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%, and the only parameter ('brand') is documented as 'Exact brand name' in the schema. The description adds no additional meaning or format details beyond the schema baseline. Baseline 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?

States a specific verb ('Get') and resource ('detailed information about a specific brand'), so the purpose is clear. However, it does not distinguish this tool from siblings such as smartscout_brand_search or smartscout_brand_coverage, leaving ambiguity about which brand endpoint to choose.

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?

Provides no guidance on when to use this tool versus alternatives like brand_search or brand_coverage. There are no conditions, prerequisites, or exclusions mentioned. This is essentially no 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?

With no annotations at all, the description carries full behavioral burden and discloses none of it: no statement of sort order, read-only nature, pagination, or whether growth is absolute or percentage based. A single phrase cannot cover the behavioral profile of an unannotated tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded phrase with zero filler, which is efficient. It is arguably too terse rather than wasteful, so it does not reach the top score.

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 read tool with all three parameters documented in the schema and no output schema to explain, the definition covers the essentials. It still omits return-shape and ranking semantics, which an agent would need to interpret results.

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 limit, period, and minRevenue are already documented in the schema, establishing a baseline of 3. The description adds no extra syntax or units (e.g., what revenue is measured in, how growth is computed per period) 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 ('Find') and resource with a ranking qualifier ('fastest growing brands'), which is more informative than a tautology. It does not distinguish itself from sibling brand tools such as smartscout_brand_search or smartscout_brand_details, so an agent must still infer the difference.

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 indication of when to pick this tool over the ~8 sibling brand/keyword tools, and no prerequisites or exclusions are given. The only implicit guidance is the growth-ranking frame.

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 behavioral burden. It doesn't state that this is a read-only operation, whether results are paginated, what metric fields are returned, or any auth/rate-limit constraints. 'Get their performance metrics' is the only behavioral hint and is too vague to act on.

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 efficient sentence with no filler, and the core action is front-loaded. It is appropriately sized but arguably too terse for a six-parameter tool, which slightly undercuts the value of the brevity.

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, the description should clarify what 'performance metrics' means (revenue, growth, ratings) since it is the only source for that. Combined with the absence of annotations and any usage context, the definition is minimally viable but leaves real gaps for a tool with six optional filters.

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 all six parameters (brand, limit, orderBy, minRevenue, minGrowth30, minProducts) are already documented in the schema, including the orderBy enum and defaults. The description adds nothing beyond that, so baseline 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?

States a specific verb (search) and resource (brands) plus what comes back (performance metrics), which is clearer than a bare 'search' tool. However, it does not differentiate from the many sibling brand tools (brand_details, brand_coverage, brand_growth), leaving the agent to guess which brand tool to pick.

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 when-to-use guidance, no prerequisites, and no mention of alternatives such as brand_details or brand_growth despite a crowded sibling set. The agent must infer the appropriate context entirely from the name.

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 and does little. It never says whether checking is read-only, that attemptIndex=true triggers a potentially expensive or mutating indexing operation, how long indexing takes, or whether partial 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 tight sentence with no wasted words, appropriately front-loaded for such a short definition. It is under-specified rather than bloated, but conciseness itself is fine.

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 whose boolean parameter can trigger dataset indexing, the description omits the behavior, cost, and return expectations, and provides no output schema. It leaves an agent unable to judge the implications of attemptIndex=true or to distinguish this from dataset_status.

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% and both parameters are documented in the schema, so the baseline is 3. The description adds no syntax, default, or side-effect detail beyond what the schema already states.

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 gives a clear verb and resource ('check the status and indexing of SmartScout datasets'), but it fails to distinguish this tool from close siblings like smartscout_dataset_status and smartscout_list_datasets, which sound like they do the same thing. An agent cannot tell from the description which of these three to call.

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 when-to-use guidance, no mention of alternatives, and no conditions for picking this over smartscout_dataset_status. The only usage hint is buried in the schema's attemptIndex field rather than stated in the 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?

With no annotations, the description carries full burden but only says 'Analyze' – it doesn't disclose what 'analysis' entails (returned fields, ranking logic, whether it's a read-only operation), nor any rate or auth behavior. Too thin for a no-annotation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, front-loaded sentence with no waste. Efficient, though its brevity borders on under-specification rather than ideal conciseness.

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?

No annotations and no output schema mean the description must explain behavior and returns, but it doesn't. Optional-asin/brand tradeoffs and the meaning of 'competitor analysis' output are unaddressed.

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 documents asin, brand, and limit. The description merely echoes 'product or brand' without adding format, relationship, or default behavior beyond what the schema already provides. Baseline 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?

States a verb (Analyze) and resource (competitors), scoped to a product or brand. However, it doesn't differentiate from siblings like smartscout_market_analysis or smartscout_opportunity_finder, leaving the intent somewhat vague relative to the crowded sibling set.

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 when-to-use guidance, no alternatives mentioned, and no exclusions. The description gives no signal about when this should be chosen over market_analysis or opportunity_finder.

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 there are row limits, rate limits, query restrictions beyond the schema's 'SELECT only' note, or what the results look like.

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 states purpose and audience with no filler. It is appropriately sized for a simple two-parameter tool, though it omits useful caveats.

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 rich input schema covers both parameters, including the SELECT-only restriction and table enum. With no annotations and no output schema, the description still leaves gaps around usage context and behavioral constraints; adequate but 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?

Schema coverage is 100%: sql is documented as SELECT only and table has an enum. The description adds no parameter-level detail beyond the schema, so baseline 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?

States a specific verb and resource: execute a custom SQL query on SmartScout data. It scopes to advanced users, but does not distinguish itself from siblings such as smartscout_test_query or the specialized search 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?

'Advanced users' is the only usage hint; it does not say when to choose this over the many specialized sibling tools or what conditions make it appropriate. No explicit when-not guidance 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?

No annotations are provided, so the description carries the full disclosure burden. It implies a read/check operation but never states that it is safe and non-mutating, what 'status' values or 'accessibility' states are returned, or what happens when datasetId is omitted. For an unannotated tool, this is thin.

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 tightly worded sentence with no filler and the resource front-loaded. It is efficient, though it may be under-specified rather than optimally concise.

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-optional-parameter read tool with no output schema and no annotations, the description is borderline adequate but leaves key questions unanswered: what a returned 'status' looks like and what 'accessibility' means. The undefined terms in the description itself are the main weakness.

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% and the single optional parameter is fully described there, so the baseline is 3. The description adds nothing about what the ID means or how the results differ when it is omitted versus supplied.

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 ('Check') and resource ('status and accessibility of SmartScout datasets'), which is clear enough to distinguish from unrelated siblings. However, it does not differentiate itself from the very similar siblings smartscout_check_datasets and smartscout_list_datasets, so the agent cannot tell from the description alone which of these three to pick.

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 when-to-use guidance, no prerequisites, and no alternatives named. With two closely-named siblings (check_datasets, list_datasets) in the same toolset, the absence of routing guidance is a real 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?

No annotations are provided, so the description carries the full behavioral burden, and it discloses nothing: no read-only nature, no pagination, no rate limits, no return shape. 'Get' weakly implies a read, but nothing about what 'associated' means or how results are ordered 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?

A single short sentence with no wasted words, but its brevity reflects under-specification rather than disciplined conciseness. There is nothing to front-load or structure because almost no information is conveyed.

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 3-parameter tool with no annotations and no output schema, the description is too thin. It does not explain the keyword-to-brand relationship, whether inputs are required, or what a caller receives, leaving an agent unable to call it 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 three parameters (brand, limit, keyword) are already documented in the schema. The description adds no meaning beyond that, so the baseline 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?

States a verb ('Get') and a resource ('brands associated with search terms'), but the verb is generic and the resource relationship is left vague. With siblings like smartscout_brand_search, smartscout_keyword_products, and smartscout_product_keywords, the description does not clarify how this tool differs from those that also bridge keywords and brands.

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 when-to-use guidance, no prerequisites, and no mention of alternatives. An agent cannot tell from this text whether to call it versus smartscout_brand_search or smartscout_keyword_search for a given task.

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. It discloses only that both organic and paid rankings are returned; nothing about ranking basis, pagination, rate limits, or whether results are live versus cached.

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 with the verb, resource, and scope in order and no filler. It is perhaps under-specified rather than verbose, but it is appropriately sized for what it says.

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 annotations, no output schema, and only one sentence, the description is minimal but the fully-documented schema covers parameter details. Return shape and ranking semantics remain unexplained for a read tool whose behavior is otherwise opaque.

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 all three parameters (keyword, type, limit) are already documented in the schema. The parenthetical '(organic and paid)' loosely echoes the type enum but adds no syntax or format meaning beyond it.

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+resource: retrieve products ranked for a given keyword, with organic/paid scope. It is distinguishable from the inverse sibling smartscout_product_keywords, but never names or contrasts any sibling explicitly.

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 when-to-use guidance, no prerequisites, and no mention of alternatives such as smartscout_keyword_search, smartscout_product_keywords, or smartscout_top_products. The agent must infer selection purely from the tool name.

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 full behavioral burden, yet it discloses nothing about pagination, result caps, rate limits, auth needs, or the shape of the response. It only hints at the metrics returned, leaving the read-only and non-destructive nature implicit in the verb 'search'.

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 short sentence with the key output metrics front-loaded and no filler, which is efficient. It is arguably too terse given the complexity of the sibling tool set, but there is no wasted 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 annotations and no output schema, the description should explain return shape and behavior, but it only names two metrics. It omits pagination, defaults, result ordering, and how the filter parameters combine, which is inadequate for a search tool in a large ambiguous tool family.

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 all four parameters (limit, maxCPC, keyword, minVolume) are already documented in the schema, which sets the baseline at 3. The description adds only a loose mapping of volume/CPC to the returned data, without clarifying filter 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?

States a specific verb (search) and resource (keywords) plus the returned data (search volume, CPC estimates), which is more informative than a bare restatement. However, it does not distinguish itself from close siblings like smartscout_keyword_products or smartscout_product_keywords, so an agent must infer the boundary.

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 statement of when to use this tool versus the many sibling keyword/product/brand tools, nor any prerequisites or exclusions. The agent gets a capability statement but no routing 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?

With no annotations, the description carries the full burden of behavioral disclosure. It implies a read-only operation but doesn't state whether it requires authentication, whether the list is paginated, or how the results are formatted. These gaps matter for an agent deciding whether to call it.

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 wasted words. It states the purpose immediately and 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 parameterless read tool with no output schema, the description covers the basic intent but omits usage context relative to siblings like check_datasets or dataset_status, and doesn't describe the return value or any behavioral constraints.

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 takes no parameters (0 params), so the baseline is 4. The description correctly implies that no inputs are needed, and there are no parameter-related gaps.

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 resource 'SmartScout datasets', specifying that it returns IDs. It is distinguishable from most siblings, though it doesn't explicitly differentiate from similar-sounding ones like smartscout_check_datasets or smartscout_dataset_status.

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 smartscout_check_datasets or smartscout_dataset_status. The description only states what it does, not when it should be chosen.

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 full behavioral burden. It says nothing about read-only safety, required permissions, rate limits, return format, or what metrics are analyzed. This is a significant gap for an analysis tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no wasted words. It is efficient, though the brevity leaves important details absent rather than being a model of informative conciseness.

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 no annotations, no output schema, and three optional parameters, the description is far too thin. It does not explain what metrics are returned, when to choose this tool over siblings, or any behavioral constraints, leaving the agent underinformed.

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 each parameter is already documented in the schema. The description mentions category and subcategory but omits the brand parameter, and adds no format or semantic nuance beyond what the schema provides. 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?

States a clear verb ('Analyze') and resource ('market metrics') with a scoping constraint (category or subcategory). However, it does not distinguish this tool from siblings like smartscout_competitor_analysis or smartscout_opportunity_finder, which also analyze market 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?

No guidance on when to use this tool versus alternatives, nor any conditions, prerequisites, or exclusions. The description merely states what it does, leaving the agent to infer usage context.

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, yet it discloses nothing beyond the verb 'Find' implying a read operation. It says nothing about return format, pagination, permissions, or rate limits.

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 single sentence is front-loaded with the verb and avoids bloat, but the phrase 'based on various criteria' is vague filler that does not earn its place. It is concise yet under-specified.

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 annotations, no output schema, and only a generic one-line description, an agent cannot tell what an 'opportunity' result contains or how to interpret it. The fully documented schema covers parameters, but the description is inadequate for a tool with four filtering dimensions.

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 documents all four parameters; the description adds no meaning beyond 'various criteria' and does not name or explain the filters. Baseline 3 applies when the schema does the heavy lifting.

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 verb ('Find') and resource ('market opportunities'), but 'based on various criteria' is vague and gives no clue how this differs from siblings like smartscout_market_analysis or smartscout_competitor_analysis. It is a minimum-viable statement of purpose, not a precise one.

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 analysis tools, no exclusions, and no prerequisites. The agent is left to infer usage from the schema alone.

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. It implies a read but never states that explicitly, and says nothing about what 'detailed information' contains, whether the ASIN must exist, or whether calls are rate-limited. For a lookup tool with zero structured behavioral hints, this is thin.

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 with no filler. It is appropriately sized for a one-parameter lookup.

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 single-param read with no output schema, the description is minimally viable. It does not hint at what fields are returned, which matters more here because there is no output schema to fall back on, and it leaves sibling disambiguation entirely unaddressed.

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?

Only one parameter and schema description coverage is 100%, so the schema already fully documents the ASIN. The description adds nothing beyond restating 'by ASIN'. Baseline 3 applies when the schema does the heavy lifting.

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 (Get) and resource (detailed product information) keyed by ASIN, so the agent knows exactly what the tool returns conceptually. It does not differentiate itself from close siblings like smartscout_product_search, smartscout_product_history, or smartscout_product_keywords, which an agent must disambiguate by name alone.

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 when-to-use guidance, no prerequisites, and no mention of alternatives. With five product-related siblings in the list, the description gives the agent nothing to decide between this tool and product_search or product_history.

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 states what data is returned (price and sales rank changes) but omits critical details such as whether data is real-time or cached, rate limits, authentication requirements, or the granularity of history (daily, weekly). It does not disclose any side effects or data freshness, leaving significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that is front-loaded with the main action and resource. It is appropriately sized for a simple tool with two parameters and no complex behaviors. There is no wasted text, though it could be slightly more informative without losing conciseness.

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 no output schema, no annotations, and relies on the description to convey its behavior. While the description states what data is returned, it lacks details on the format, granularity, and limitations of the historical data. For a tool that returns time-series data, this is a noticeable gap, though the basic information is present.

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%, meaning both parameters (asin and days) are already fully documented in the schema. The description does not add any meaning beyond what the schema provides – it does not explain the format of asin, the default behavior of days, or any constraints. When schema coverage is high, a baseline of 3 is appropriate even without additional parameter info.

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 what the tool does: retrieves historical data (price and sales rank changes) for a product. It uses a specific verb ('Get') and resource ('historical data for a product'). However, it does not differentiate from siblings like smartscout_product_details or smartscout_product_search, which likely also return product data, so it falls 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 provides no guidance on when to use this tool versus alternatives. There is no mention of when historical data is needed, conditions that make it preferable to product_details or product_search, or any exclusions. It only restates the purpose without usage context.

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 behavioral burden. It discloses nothing about pagination, rate limits, result ordering, whether the 'limit'/'maxPosition' defaults meaningfully constrain output, or what the return set looks like—significant gaps for a data-retrieval tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single well-formed sentence with no wasted words and the core purpose front-loaded. It is efficient, though its brevity borders on underspecification rather than true conciseness.

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 four-parameter read tool with full schema coverage and no output schema, the description covers the essential 'what' but omits result semantics, ordering, and any note that the defaults cap the returned keyword set. Adequate as a minimum viable definition, but 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?

Schema description coverage is 100%, so each of the four parameters is already documented in the schema and the baseline is 3. The description adds no extra meaning about the enum values (organic/paid/both), the ASIN format, or how limit and maxPosition interact.

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 clear verb (Get) and resource (keywords that a product ranks for), which an agent can distinguish from the inverse sibling smartscout_keyword_products. However, it does not explicitly name or differentiate against that sibling, 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?

There is no when-to-use guidance, no exclusions, and no mention of the closely related keyword_products or keyword_search siblings. An agent must infer the directionality (product → keywords) purely from the description phrase 'that a product ranks for'.

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 behavioral burden, and it discloses almost nothing: no auth requirements, no pagination behavior, no default/max result handling (the limit cap of 1000 lives only in the schema), and no note that filters combine as AND. For a 12-parameter query tool with zero annotation coverage, 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?

A single short sentence with no filler, appropriately front-loaded with the verb and resource. It is efficient but borders on under-specified for a 12-parameter 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?

With 12 optional parameters, no annotations, and no output schema, the description is too thin: it does not explain the result shape, ordering defaults, or how the numerous filters compose. An agent could call it, but not confidently or correctly in edge cases.

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 every parameter is already documented in the schema, making the baseline 3. The description restates only three of the twelve parameters (ASIN, title, brand) and adds no semantics beyond what the schema provides, e.g. how price, sales, and rating filters interact.

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 clear verb+resource ('Search for products') and enumerates the primary search keys (ASIN, title, brand). However, it does not distinguish this tool from close siblings such as smartscout_product_details, smartscout_top_products, or smartscout_product_keywords, so the agent cannot tell from the text alone which product tool to pick.

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 when-to-use guidance, no prerequisites, and no mention of alternatives among the many sibling search/product tools. The trailing 'or other criteria' is vague and gives the agent no routing signal.

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 behavioral burden. It implies a harmless connectivity check but says nothing about authentication requirements, rate limits, whether arbitrary endpoints are permitted, or what a success/failure response looks like.

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 with no wasted words. It is efficient, though its brevity is partly the reason other dimensions are thin.

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-optional-parameter diagnostic tool with no output schema, the description is minimally sufficient to call it, but it omits any indication of the response shape or error behavior that an agent would want from a connectivity test.

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?

There is one optional parameter at 100% schema description coverage, so the schema already documents the endpoint format and default. The description adds no syntax, format, or constraint detail beyond the schema, matching the baseline 3.

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 (Test) and resource (raw Domo API endpoint) plus intent (verify connectivity), which distinguishes it from siblings like smartscout_test_query and smartscout_system_info. It does not explicitly say how it differs from those siblings, so it falls 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 gives no when-to-use guidance, no prerequisites (e.g., auth), and names no alternatives among the many sibling diagnostic tools. An agent must infer usage from the word 'test' alone.

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 burden and discloses almost nothing: no read-only reassurance, no auth requirements, no rate limits, and no indication of what 'detailed information' contains. Only the word 'Get' weakly implies a non-mutating lookup.

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 short sentence with no filler and the resource stated immediately. It is efficient, though it is arguably too terse for a tool whose payload is undefined.

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?

There is no output schema, so the description should convey what 'detailed information' actually returns (fields, nested data, size). Combined with no annotations and no usage context, an agent cannot predict the response shape or when this beats sibling seller 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 coverage is 100% for the single sellerId parameter, so the schema already documents the input; the description adds no format, source, or example for the ID. Baseline 3 is appropriate when the schema does the work.

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 clear verb ('Get detailed information') and a specific resource ('a specific seller'), so the agent knows it retrieves a single seller's profile. It does not differentiate from siblings such as smartscout_seller_search or smartscout_seller_products, leaving the agent to infer the boundary from names alone.

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 when-to-use guidance, no prerequisite (e.g., needing a sellerId obtained from seller_search), and no mention of alternatives. The agent must guess whether this or seller_search/seller_products is the right call.

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 burden but says nothing beyond the read intent. It omits pagination behavior, result ordering, default limit implications, rate limits, and whether minBuyBoxPercent acts as a filter on the returned set.

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 with no wasted words. It is efficient, though its extreme brevity borders on under-specification rather than true conciseness.

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 3-parameter read tool with no annotations and no output schema, the description does not explain what a product record contains, pagination, or filtering behavior. It is too thin to let an agent call the tool confidently without opening the schema.

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 every parameter is documented in the schema and the baseline is 3. The description adds no extra semantics about sellerId format, limit bounds, or what minBuyBoxPercent filters.

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 ('Get') and resource ('products sold by a specific seller'), which is clearer than the bare tool name. However, it does not distinguish itself from close siblings like smartscout_seller_details or smartscout_top_sellers, leaving the agent to infer the boundary.

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 on when to use this tool versus alternatives such as smartscout_seller_details or smartscout_product_search. Usage is only implied by the tool name; there are no exclusions or conditions.

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 behavioral burden. 'Search' implies a read-only operation, but no details on permissions, rate limits, pagination, or return format are given.

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 with zero waste. It is appropriately sized for the purpose statement.

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 incomplete. It lacks information about return values, default ordering, pagination, and behavioral traits an agent would need.

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 fully documents all 8 parameters. The description adds no parameter-level detail beyond the search criteria mentioned, which is baseline adequate.

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 (search) and resource (sellers) with search criteria (name, ID, performance metrics). It is clear, but does not explicitly differentiate from sibling tools like smartscout_top_sellers or smartscout_seller_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?

No when-to-use guidance, prerequisites, or alternatives are provided. The description only states what the tool does, leaving the agent to infer appropriate contexts.

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 burden. It implies a safe metadata read but never states side-effect profile, auth requirements, or that results are static schema metadata rather than live data. It does at least signal the return content ('databases and their schemas'), which is the one behavioral hint present.

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 with no filler, appropriate for a simple introspection tool. It could carry slightly more routing information without becoming bloated, but nothing is wasted.

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, optional-argument metadata tool with no output schema, the description is minimally adequate: it conveys what the tool surfaces but not how it differs from the several sibling dataset-listing tools. An agent could call it correctly but might pick a sibling by mistake.

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 single optional enum parameter is already fully documented. The description's phrase 'available SmartScout databases' loosely frames the parameter but adds no format or filtering detail beyond the schema, which is the expected baseline when the schema does the work.

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 (Get) and resource (information about SmartScout databases and their schemas), which is distinct from the catalog/product/brand/keyword focus of siblings. It does not, however, distinguish itself from near-neighbors like smartscout_list_datasets or smartscout_check_datasets, leaving some ambiguity about which introspection tool to pick.

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 on when to call this versus list_datasets, check_datasets, or dataset_status, all of which sound like related discovery tools. There is no mention that this is a discovery/introspection call that might logically precede a smartscout_custom_query.

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 burden. It does not disclose whether the query actually executes against live data, whether it can modify anything, what output shape to expect, or any rate limits — all important for a query-execution tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no waste. It is efficient, though arguably too terse for a tool that needs disambiguation from siblings.

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 (2 params, no output schema), but the description omits the critical distinction from smartscout_custom_query and the sandbox/execution semantics of 'test'. An agent lacks what it needs to select this tool confidently over its near-duplicate siblings.

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% and both parameters are documented in the schema (including the default 'SELECT * LIMIT 5' for query). The description adds nothing beyond that, so the baseline 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?

States a clear verb+resource: it tests a SQL query against one named dataset. However, it does not distinguish itself from the sibling smartscout_custom_query or smartscout_raw_api_test, so an agent cannot tell why it would pick 'test_query' over those without inspecting the schemas.

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 smartscout_custom_query, smartscout_raw_api_test, or smartscout_dataset_status. The word 'test' implies a trial/sandbox mode but the description never says so or states any precondition.

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, and it discloses almost nothing behavioral: no indication of how 'top selling' is ranked (units vs. revenue), no pagination or limit behavior, no auth or rate-limit notes, and no return-shape hint. Only 'Get' weakly implies a read operation.

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 short sentence that front-loads the verb and resource with no filler. It is efficient, though the brevity contributes to the coverage gaps noted elsewhere rather than to 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 4-parameter tool with zero annotations and no output schema, the description is too thin: it never defines the ranking basis for 'top selling', the role of the limit default, or how brand interacts with category/subcategory. An agent can call it, but cannot predict what it returns.

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 all four parameters are already documented, making 3 the baseline. The description mentions category/subcategory filtering but adds no syntax or relationship detail (e.g., whether both can be combined) and omits the brand filter entirely.

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 and resource ('Get top selling products') and constrains scope to a category or subcategory. However, it does nothing to distinguish itself from the very similar sibling smartscout_top_sellers or from smartscout_product_search, leaving the agent to guess which retrieval tool fits.

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 pick this over smartscout_top_sellers, smartscout_product_search, or smartscout_custom_query, nor any prerequisite or exclusion noted. Usage is only implied by the word 'top'.

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 behavioral burden but discloses almost nothing beyond the basic action. It does not mention authentication needs, rate limits, pagination, result ordering, or whether 'top' means top-N by default, so the agent has little behavioral context beyond the schema defaults.

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 with no filler or redundancy. It is efficient, though its extreme brevity leaves limited room for structure.

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 (3 optional params, all documented, no output schema, no annotations). For such a low-complexity tool, one sentence is minimally adequate, but the absence of any usage or behavioral context for a tool with no annotations means it falls short of being fully 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?

Schema description coverage is 100%, so the schema already documents limit, metric, and minRevenue, making the baseline 3 correct. The phrase 'by revenue or other metrics' loosely echoes the metric parameter but adds no syntax or format detail 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 a specific verb and resource ('Get top sellers') plus the ranking dimension ('by revenue or other metrics'), so the agent knows what the tool returns. It does not differentiate from the sibling smartscout_top_products, which ranks products rather than sellers, leaving that distinction to be inferred.

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 only usage hint is that ranking can use 'revenue or other metrics,' which merely mirrors the metric enum. There is no guidance on when to prefer this tool over smartscout_top_products or other seller-related siblings, and no prerequisites or exclusions are given.

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