Sense2 Promotional Products

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

No annotations provided, so description bears full burden. It does not disclose read-only nature, permissions, rate limits, or side effects. The description only states content structure, not 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?

Single sentence of 22 words, efficiently conveying purpose and structure. No wasted words.

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?

Description explains what is returned (curated list, quarterly, structured) but lacks return format, authentication needs, or comparison to sibling tools. Adequate for a simple no-param tool but incomplete given no output schema or annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist, so baseline is 4. Description adds no parameter info, but none is needed. Schema coverage is 100% trivially.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool returns 'The 100 Best Promotional Products in Australia' with structure (10 sections x 10 products, editorial intros). It distinguishes from siblings like get_product (single product) and search_products (search results) by specifying a curated quarterly flagship edit.

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 (e.g., get_100_best_intel, search_products). The description provides no context for appropriate use 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, and the description fails to disclose any behavioral traits such as read-only nature, authentication needs, or response size. It simply enumerates content without behavioral context.

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

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

The description is a single, long run-on sentence listing many items. It lacks structure and conciseness; important information is not front-loaded efficiently. It could be broken into bullet points or shorter sentences.

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 parameters and no output schema, the description does a fair job enumerating the content. However, it does not describe the format or structure of the returned data (e.g., JSON keys, nested objects), leaving some ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the baseline is 4. The description adds meaning by detailing what the output contains, which is valuable given the absence of an output 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 lists multiple components (lenses, test, insights, guide, etc.) but does not explicitly state the action (e.g., 'Retrieves the editorial intelligence layer'). The verb is implied by the tool name. It distinguishes from siblings by specifying the content, but the purpose is somewhat buried in a verbose list.

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 like get_100_best or get_brand. The description does not mention any prerequisites, conditions, 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?

Although no annotations are provided, the description explicitly states that the tool returns a list of 12 collections with product counts and URLs. This gives clear insight into the output and implied read-only behavior, covering the main behavioral aspects needed for an agent.

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

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

A single sentence that includes all critical details: action, resource, count, examples, and output fields. No redundant words, well-structured and front-loaded.

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 parameters, no output schema, no annotations), the description is complete. It tells the agent exactly what to expect from the output, and the lack of additional context is not a deficiency.

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?

With no parameters, schema coverage is 100%. The description adds value by explaining the exact content and structure of the output, which is beyond what the empty schema conveys. It fully compensates for the lack of parameters.

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', the resource 'Shop by Aesthetic editorial collections', the exact count (12), gives examples, and notes included fields (product counts and URLs). This makes the purpose unmistakable and distinguishes it from sibling tools like 'get_inspiration' or 'get_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?

No guidance on when to use this tool versus alternatives. There is no mention of prerequisite contexts, exclusions, or related tools. The description only covers what the tool 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 present, so the description must convey behavioral traits. It implies a read-only retrieval operation but does not specify authorization requirements, error handling for invalid slugs, idempotency, or any side effects. It adds minimal behavioral context beyond listing returned fields.

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, efficient sentence with no wasted words. It front-loads the purpose and lists key content, making it easy to parse quickly.

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 (one parameter, no output schema), the description adequately covers the return value by listing main fields. It could be improved by mentioning idempotency or that it returns a single object, but it is sufficiently complete for a straightforward retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema covers 100% of parameters, and the single 'slug' parameter is described. The description adds value by enumerating the fields returned (story, signature, logo tagline, industries), which clarifies the output's meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves full brand case-study details by slug, listing specific fields (story, signature, logo tagline, industries). The verb 'Get' and resource 'brand case-study details' are specific, and the use of a unique identifier (slug) distinguishes it from siblings like get_brands (which likely lists all 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 guidance is provided on when to use this tool versus alternatives such as get_brands (list) or get_brand_moves (related brand moves). The description does not mention prerequisites, use cases, or when not to use it.

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

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

Despite no annotations, the description adequately conveys that the tool retrieves a fixed set of creative strategy concepts. It does not disclose any side effects, rate limits, or other behavioral traits, but the tool is simple and read-only.

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 sentence that efficiently conveys the tool's purpose and content. It is front-loaded with the main item and contains no unnecessary words.

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 parameters and no output schema, the description sufficiently explains the returned content (12 Brand Moves and Combining Aesthetics framework). It lacks structural details about the output format, but is adequate for a retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero parameters. Per guidelines, baseline is 4. The description adds meaning by detailing the content returned (brand moves and framework), which compensates for the lack of parameters.

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 that the tool provides 'The 12 Sense2 Brand Moves' and 'Combining Aesthetics framework', specifying the exact content. This distinguishes it from sibling tools like 'get_aesthetics' or 'get_inspiration'.

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 other similar tools (e.g., 'get_aesthetics', 'get_brand'). The description does not mention any prerequisites or 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 carries the burden. It transparently states the tool returns a static list of brands with specific fields. It does not mention authentication or rate limits, but for a read-only list that is acceptable.

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?

Single sentence, front-loaded with action and examples, no unnecessary words. Highly efficient and well-structured.

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 output schema and no parameters, the description fully covers what the tool returns: a list of brands with industry, headline, and URL, with concrete examples. Complete for the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist. The description adds meaning by detailing the content of the list (specific brands, fields) beyond what the empty schema provides. Baseline for 0 params is 4, and the description exceeds that.

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', the resource 'brands', and provides specific examples (Google, Nike) and fields returned (industry, headline, URL). It distinguishes from the singular 'get_brand' sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for listing all case-study brands, but does not explicitly state when to use this tool versus alternatives like 'get_brand' or when not to use it. With 18 siblings, more guidance would be beneficial.

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 full burden. It discloses that it returns both matching missions and a concierge (Findie) for unmatched briefs, which is valuable behavioral insight. However, it could mention if it modifies any state or requires authentication, but since no annotations exist and the tool appears read-only, the current level is adequate.

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

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

Two sentences, zero waste. The first sentence describes what it returns with clear examples; the second provides usage guidance. Perfectly front-loaded and 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?

Given the tool has only one optional parameter and no output schema, the description fully covers its purpose, usage, and key behavioral trait (returning Findie for non-matches). It is complete for an agent to correctly invoke and interpret the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents the query parameter. The description adds that it's an 'optional keyword filter' but no additional meaning beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as providing 'pre-solved buying briefs' with concrete examples like 'conference giveaways under $5 for 500 people'. It differentiates from siblings by stating to use it FIRST for questions with quantity, budget, or deadline, making its purpose distinct.

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?

Explicitly states 'Use this FIRST for any question that includes a quantity, budget or deadline', providing clear when-to-use guidance. Also implies fallback behavior by mentioning Findie for non-matching briefs, effectively guiding tool 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 were provided, so the description carries the full burden. It accurately implies a read-only operation ('list') with no destructive behavior. The description is straightforward and does not hide any behavioral traits, though it could mention permanence or authorization needs.

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 conveys all necessary information without any wasted words. It is appropriately sized and front-loaded.

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 parameters, no output schema), the description is mostly complete. It could benefit from specifying the output structure (e.g., returns a list of category objects with name and count), but for a basic listing tool it is adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema coverage is trivially 100%. The description adds no parameter information because none are needed. The baseline for no parameters is 4, and the description meets this.

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 'List all product categories with product counts', using a specific verb ('list') and resource ('product categories') with additional detail ('product counts'). It distinguishes this tool from siblings like 'get_brands' or 'get_product' which handle different entities.

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. While the purpose is clear, there is no explicit mention of when-to-use or when-not-to-use compared to sibling tools like 'get_brands' or 'search_products'.

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 provided, so description carries full burden. It implies read-only behavior by listing facts but does not explicitly state that it is safe, non-destructive, or what the response format is. Minimal disclosure beyond the data content.

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?

Single sentence that is informative but somewhat lengthy due to enumeration of many data points. Front-loaded with main purpose. Could be split into two sentences for readability, but still effective.

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 parameters and no output schema, the description provides a thorough list of outputs. For a simple fact retrieval tool, this is adequately complete. Lacks only minor details like return format or limits.

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?

Input schema has zero parameters (100% coverage trivially). Description adds value by detailing the types of facts returned (e.g., Google ratings, Sedex membership), which is meaningful context beyond the empty 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 uses a clear verb ('get' implied) and specifies the resource ('company facts for procurement and supplier questions') with detailed list of data points (ABN, years operating, etc.). It distinguishes itself from sibling tools that cover brands, products, and aesthetics.

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?

Explicitly states the tool is for 'who is Sense2', 'how big are they', 'are they compliant' style questions, providing clear context for use. No mention of when not to use, but sibling differentiation makes it implicit.

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 describes the tool's output in detail: themed sections, per-product intel, why it stands out, best branding move, and signature campaign moment. This gives a concrete sense of what the tool returns, though it does not explicitly state 'returns' or mention limitations.

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 dense sentence that efficiently packs examples, output structure, and usage guidance. It is front-loaded with the main concept and avoids fluff, though the long parenthetical list and flowery phrasing like 'signature campaign moment it owns' add slight sprawl.

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 there are no parameters, no annotations, and no output schema, the description is quite complete: it explains what the tool offers, the structure of results, and when to use it. It could be even more explicit about the return format (e.g., 'returns a list of sections'), but the description adequately covers the essentials.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, so the baseline is 4. The description does not discuss parameters, but none exist, so there is no missing information. The schema is empty and accurately matches the no-input nature of the tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: providing creative/unusual promotional item ideas in themed sections with per-product intel. It distinguishes itself from sibling tools by specifying 'unusual promotional items other suppliers don't carry' and listing concrete examples like cocktail umbrellas and custom ice cubes.

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 explicitly specifies when to use the tool: for briefs involving 'something different', 'unusual', 'never seen before', 'stand out from other brands', or 'conversation starter' ideas. It does not name alternative tools, but the use-case guidance is clear and contextual.

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 description must carry behavioral burden. It implies a read-only lookup, but does not explicitly state non-destructive nature, rate limits, or return 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?

Two sentences: first lists topics, second gives usage examples. No wasted words; front-loaded with essential info.

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 FAQ tool with one optional parameter and no output schema, description is adequate. Could specify return format or that it returns answers, but not critical.

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 baseline is 3. Description adds minimal extra meaning beyond schema: it lists example topics that map to tag values, but does not elaborate on format or behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it provides practical buying answers for specific topics (MOQ, lead times, artwork, etc.) and gives concrete example questions. This distinguishes it from sibling tools like get_product or get_quote.

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?

Description provides example questions to use it for ('what is the minimum order', etc.), indicating clear context. However, it does not explicitly state when NOT to use it or compare with alternatives.

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 correctly identifies a read-only list operation, but provides no details on result size, ordering, pagination, or potential side effects. The description is adequate but minimal.

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 6-word sentence, highly concise. However, it could be front-loaded with output format details. Still, it earns its place with no fluff.

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 low complexity and lack of annotations/output schema, the description is partially complete. It states the resource and action but omits the return structure (e.g., array of object with industry name and count). More detail would improve 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 tool has zero parameters with 100% schema coverage, so baseline is 4. The description adds no parameter information, which is acceptable as none exists.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('List') and identifies a clear resource ('industry affinities with product counts'). The tool name and description together uniquely identify its purpose among the sibling tools, as no other sibling mentions industries.

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 like get_categories or get_brands. It lacks any context about suitable scenarios, 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 provided, so the description must disclose behavioral traits. It hints at the output content (creative insight, signature move, brand vibe) but does not explicitly state read-only, idempotency, or side effects. The inference is reasonable for a retrieval tool, but lacks explicit 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 a single, 14-word sentence that front-loads the action ('Get a single inspiration card by slug') and includes parenthetical detail. No redundant information; every word adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Without an output schema, the description should explain return values. It mentions 'full creative insight, signature move, brand vibe', providing insight into the response content. This is adequate for a simple retrieval tool, though a more explicit structure listing would raise completeness further.

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% with description 'Inspiration slug from get_inspirations', and the tool description adds 'by slug'. This combination provides context that the slug originates from another tool, enhancing semantic understanding beyond the schema alone.

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 retrieves a single inspiration card by slug, specifying the content includes 'full creative insight, signature move, brand vibe'. This distinguishes it from sibling 'get_inspirations' which lists cards, making the purpose specific and differentiated.

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 and parameter schema reference 'slug from get_inspirations', implicitly guiding users to first list cards to obtain the slug. However, it does not explicitly exclude alternatives like 'get_brand_moves' or provide when-not-to-use scenarios, but the guidance is clear enough for typical use.

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 provided, so description should fully disclose behavior. Only states it lists cards, but lacks details on read-only nature, pagination, latency, or any side effects.

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?

Single sentence with necessary context, no wasteful words. Could be slightly more structured but 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?

Adequate for a simple list operation with one parameter. Missing details on response format, sorting, or filtering beyond limit, but sufficient given simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 100% of parameters. Description adds no extra meaning beyond schema's 'max results' explanation. 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?

Description clearly states verb 'List' and resource 'Sense2 editorial inspiration cards' with added context about brand-crushes and insights. However, it does not distinguish from sibling 'get_inspiration' tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like 'get_inspiration' or other list tools. Missing context for when this tool is appropriate.

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. It reveals output includes product counts and URLs, but lacks details like fixed 30 count, ordering, or read-only nature. Missing behavioral traits beyond basic listing.

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?

Single sentence with clear verb-first structure. Every word is informative with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters or output schema, the description adequately covers purpose and output. Minor gap: doesn't confirm if list is always 30 or if pagination applies, but minimal impact for such simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters, schema coverage 100%. Description adds value by confirming 'all 30' and specifying output fields, which is sufficient baseline for zero-parameter tools.

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 'all 30 Shop by Intent curated collections', with specific examples of collections and output fields. It distinguishes itself from siblings like 'get_categories' which have different resources.

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 vs alternatives (e.g., 'get_buyer_missions', 'get_categories'). No mention of when not to use or prerequisite 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 provided, so description carries full burden. Discloses hand-curated nature, monthly refresh, and per-product trend signals. No behavioral contradictions.

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

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

Two sentences, no filler. Front-loaded with key information (trending products, location, refresh cycle). Every sentence earns its place.

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 zero parameters and no output schema, description sufficiently explains what is returned and when to use. Could specify if output is a list or single item, but still clear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist; schema coverage 100%. Description adds value by explaining output content and update frequency, meeting baseline for zero-param tools.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description specifies it returns trending Australian promotional products/corporate gifts, hand-curated and refreshed monthly with trend signals. Clearly distinguishes from static category 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?

Explicitly states when to use ('what's trending', 'what's popular now', 'what's new' style questions) and contrasts with static category search. Lacks explicit when-not-to-use but adequate.

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 and adds meaningful context by explaining locale's effect on name/currency/pricing/URL while descriptions remain English. This goes beyond a simple getter and discloses a non-obvious behavior, though error behavior and response format are not covered.

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

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

Two concise sentences, front-loaded with the core purpose, and every clause adds useful detail about locale behavior. No redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter getter with no output schema, the description covers the tool's purpose and a key nuance (localization), making it sufficiently complete. It could be slightly richer by mentioning what 'full product details' includes, but that is minor.

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% (baseline 3), but the description adds value beyond the schema: it explicitly lists 'pricing' as a localized field, which the schema omits, and clarifies that descriptions stay English across all locales.

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 'Get full product details by PID' clearly states the tool's function with a specific verb and resource, and the PID parameter makes it distinct from sibling getters like get_brand or get_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 clearly implies when to use this tool (when you have a product ID and need full details), but does not explicitly mention alternatives or exclusions, such as using search_products when the PID is unknown.

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 adds a key detail about quotes below MOQ being flagged as belowMoq and indicative only, which is not in the schema. However, it does not disclose return format, error conditions, or side effects, leaving some behavioral uncertainty.

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 two sentences with no filler. The first sentence immediately states the tool's purpose, and the second adds a critical constraint. Every word earns its place, making it highly concise and well-structured.

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 (3 parameters, no output schema, no annotations), the description covers the essential purpose and an important edge-case (belowMoq). It does not describe the return value structure, but the tool name and general context imply a quote object. This is adequate but not exhaustive.

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 complete descriptions for all three parameters (pid, locale, quantity), achieving 100% schema coverage. The description adds nothing meaningful about parameter meaning beyond what the schema states, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with a specific verb and resource: 'Get a pricing quote for a product at a specific quantity.' It distinguishes itself from sibling tools like get_product and search_products by focusing specifically on pricing quotes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use the tool: when a pricing quote for a product at a specific quantity is needed. It does not explicitly state when not to use it or mention alternatives, but the purpose is specific enough that the usage context is unambiguous.

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

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

No annotations provided, so description carries full burden. It discloses that reviewers are shown by initials only and what each review evidences. It does not mention read-only nature, but the lack of parameters and destructive hints imply 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?

Two sentences, front-loaded with key information, no wasted words. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters and no output schema, the description fully explains what the tool returns, including privacy and evidence categories.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist, so description need not add param info. Baseline 4 for 0 parameters is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it retrieves Sense2 customer reviews and platform ratings from Google and Trustpilot, with links and featured verbatim reviews. It distinguishes from sibling tools by specifying the specific content source and type.

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 explicit usage examples like 'how good is Sense2' and 'what do customers say', but does not explicitly mention when not to use or name alternatives among siblings.

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 fully discloses behavior: returns landing-page URL, region, freight terms, and explicitly states no transit-day estimates. No contradictions.

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

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

The description is well-organized: starts with purpose, then examples, then parameter usage and important note. Slightly verbose but every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple parameter and no output schema, the description provides all necessary context: what it does, how to use it, what it returns, and a critical limitation. Complete for agent decision-making.

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 covers the slug parameter 100%. Description adds value by explaining the effect of including a slug (full intro) and providing examples, beyond the schema's basic 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's purpose: returning service areas where Sense2 delivers in Australia, with a dedicated page per location. It lists example questions and distinguishes from sibling tools that focus on products, brands, etc.

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 instructs to pass a slug for a specific area or omit for all, and provides a critical note not to promise delivery dates. It lacks explicit comparison to alternatives but gives clear 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?

With no annotations, the description carries the full burden of behavioral disclosure. It explicitly states the return shape, the meaning of 'total' vs 'returned', the cap at 500, and how to paginate with offset. This is strong transparency, though it omits details like error handling or empty query behavior, which are minor for a search 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 two sentences, front-loaded with the purpose, and efficiently conveys all critical behavioral information. No word is wasted; every clause contributes to understanding the tool's behavior 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?

For a simple search tool with no output schema, the description is complete. It covers the return format, pagination, and result cap. It also indirectly clarifies how limit and offset work together. No significant gaps remain for the 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?

Schema coverage is 100%, so the baseline is 3, but the description adds value by explaining the relationship between returned and total, the 500-cap, and how to use offset for large result sets. This enriches the meaning of the parameters beyond the basic schema descriptions.

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 function: 'Search Sense2 promotional product catalogue by keyword.' The verb 'search' is specific and distinct from all sibling get_* tools, which all retrieve specific entities rather than performing keyword searches. This makes the purpose unmistakable and well-differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on how to use the tool, such as pagination with offset and the cap of 500 results per page. It does not explicitly mention when not to use it, but the contrast with sibling get_* tools is implicit. The guidance on walking large sets is practical and adds value.

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