Packrift Packaging

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

Annotations already declare readOnlyHint=true (safe read) and openWorldHint=true (external changes). The description adds value by emphasizing 'Real-time' and 'Live, never cached,' informing the agent of freshness behavior and no caching 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?

Two sentences with no fluff. The first sentence states the core purpose, and the second adds key behavioral context. Every word 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?

For a simple tool with one parameter and annotations covering safety, the description covers the purpose and data freshness. However, it does not describe the output format (e.g., a map of ID to count), which would improve completeness. Still, the missing detail 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 0%, so the description must compensate. It clarifies that 'variant_ids' accepts 'one or more' values, matching the minItems constraint, but adds no format or example. This is adequate but minimal 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 returns 'Real-time available inventory count for one or more variant ids,' specifying the verb (returns count) and resource (inventory for variant IDs). It distinguishes from siblings like get_pricing or search_products, which handle different concerns.

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 clarifies that the tool provides live, uncached data, which implies use cases requiring freshness. However, it does not explicitly state when not to use it or mention alternatives; the context suffices given no sibling tool overlaps.

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?

Annotations include readOnlyHint=true and openWorldHint=true, indicating safe exploration and non-exhaustive results. The description adds that it is an exploration tool returning ranked candidates and a plain-language summary, which is consistent and adds context beyond annotations.

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

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

The description is a single sentence that is front-loaded and directly communicates the tool's purpose and output without 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?

Given the tool has 4 parameters, no output schema, and annotations present, the description adequately covers the main purpose and output. It could be more specific about the comparison summary format, but overall sufficient.

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 50% of parameters with descriptions; the tool description does not add additional meaning to parameters beyond what is in the schema. However, it does clarify the output (ranked candidates + summary), which is not in the schema, providing some value.

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

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

The description clearly states it is an exploration tool for buyers comparing a packaging spec, competitor-style item, or Uline-style request against Packrift products, and specifies it returns ranked candidates and a comparison summary. This distinguishes it from sibling tools like search_products or check_inventory.

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 comparing specs or competitor items, but does not explicitly state when to use this tool versus alternatives, nor does it provide when-not-to-use 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?

Annotations already declare readOnlyHint=true, indicating no mutation. The description adds behavioral specifics: always appends '?ref=mcp' and optionally a discount code. This goes beyond annotations without contradicting them.

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 with no wasted words. The first sentence defines the core purpose, the second adds crucial behavioral details. Efficient 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?

The tool lacks an output schema, and the description does not specify the return format. For a URL-builder, stating that it returns a string URL would complete the picture. Without this, the agent must infer the output.

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 0%, so the description must provide parameter meaning. It does so by referencing 'variants and quantities' (items), '?ref=mcp' (ref), and 'discount_code'. All three parameters are implicitly covered, adding essential context.

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 'builds a Shopify cart permalink for given variants and quantities', using a specific verb and resource. This distinguishes it from sibling tools (e.g., check_inventory, get_pricing) which serve different purposes.

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

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

The description implies usage for creating cart URLs but provides no explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned, though the sibling tools are clearly different in function.

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?

Annotations already declare the tool as read-only. The description adds that it returns 'safe next actions' and a 'tracked bulk quote URL', providing behavioral context beyond the annotations. It does not contradict the readOnlyHint.

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

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

The description is a single concise sentence that front-loads the primary action. It is efficient but could be slightly improved by adding more structure or clarifying what 'safe next actions' entail.

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 6 parameters and no output schema, the description does not fully explain the return format or the structure of 'safe next actions' and 'tracked bulk quote URL'. It is adequate but leaves 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 input schema has 100% description coverage, so the description adds no additional meaning to parameters. Baseline of 3 is appropriate as the schema already documents the parameters adequately.

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

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

The description clearly states the tool's purpose: to explain why a nearby product should not be presented as an exact match and then return safe next actions and a tracked bulk quote URL. This verb+resource structure distinguishes it from siblings like search_products or check_inventory.

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 the tool is used when there is no exact match, but it does not explicitly state when to avoid using it or provide alternatives. The context is clear enough for an AI agent to infer appropriate usage.

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

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

Description aligns with readOnlyHint and openWorldHint annotations. It adds behavioral details: returns 5 SKUs ranked by fit with price, stock, URL. No contradictions, but could elaborate on openWorld implications (e.g., results may vary).

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?

Description is three sentences, front-loaded with purpose and inputs, followed by outputs. Every sentence adds essential information 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 no output schema, description adequately explains returns (5 SKUs, ranked, fields). Inputs and usage are clear. Lacks examples of output format or edge cases, but sufficient for a moderately complex 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 0%, but description lists all inputs ('L/W/D in, weight lb, use_case') and enumerates use_case options in parentheses. This adds context beyond the schema's field names, helping agents understand the measurement units and purpose.

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 explicitly states the tool's purpose: 'find the right box or mailer' given item dimensions and weight. It clearly distinguishes itself from sibling tools like check_inventory or get_pricing by focusing on packaging recommendations.

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 clear when-to-use guidance: 'Use when the user has an item's L/W/D and needs the right box or mailer.' It includes example use cases (box-vs-mailer, Uline-by-size), but does not explicitly exclude scenarios or mention alternative tools.

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?

Annotations already declare readOnlyHint and openWorldHint. The description adds that the tool returns a URL (not a direct quote) and is tracked, which is useful context. 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?

Two sentences, front-loaded with the core purpose, no fluff. Every word 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 7 parameters and no output schema, the description is fairly complete. It explains when to use the tool and what it returns. The lack of output schema detail is acceptable as the URL nature is implied.

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 descriptions for all parameters. The description does not add additional parameter semantics beyond what the schema provides. Baseline score of 3 applies.

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

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

The description clearly states it returns a tracked Packrift bulk quote URL for an exact requested packaging spec or SKU. It distinguishes from siblings like get_pricing or search_products by specifying the exact purpose.

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 says 'Use when there is no exact match or the buyer needs bulk/procurement review,' providing clear context. It does not list exclusions or alternatives, but the context is sufficient.

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?

Annotations indicate read-only and open-world behavior, and the description adds context about the output structure and required confirmation sequence, providing valuable behavioral insight beyond annotations.

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 that conveys all key output components without redundancy, though it could be slightly restructured for clarity.

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

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

Despite lacking an output schema, the description thoroughly explains the return structure and logic, covering all relevant aspects for a read-only tool with three optional parameters.

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 67% of parameters with descriptions; the tool description does not add significant extra meaning to parameters beyond the schema, but it hints at usage via output context.

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 returns priority AI-approved SKUs for cart handoff, listing specific output components and distinguishing itself from sibling tools like create_cart_url.

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

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

The description implies this tool is a precursor to create_cart_url by mentioning it returns create_cart_url arguments, but it lacks explicit when-to-use or when-not-to-use guidance relative to 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?

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds the valuable behavioral context 'Live, never cached', which is beyond the annotations. No contradictions found, though it could mention result format or error handling for missing variant IDs.

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

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

The description is extremely concise—one sentence of 11 words—yet front-loads the key purpose and the important 'live, never cached' property. Every word is necessary, 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?

For a simple tool with two straightforward parameters and no output schema, the description covers the core purpose and freshness. However, it could be slightly more complete by noting what happens with invalid variant_ids or the format of the returned price/quantity (e.g., 'Returns a map of variant ID to price and quantity').

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 0%, so the description must compensate. It mentions 'variant_ids' but does not explain the 'quantity' parameter (default 1, integer) or its role. The description adds only partial meaning, leaving the user to infer parameter purpose from 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 returns 'Real-time price and available quantity for one or more variant ids', which distinguishes it from siblings like 'get_product' (likely full product details) and 'check_inventory' (possibly stock levels). It uses specific verbs and resources, and the 'Live, never cached' adds clarity.

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 real-time pricing needs ('Live, never cached') but does not explicitly state when to use this tool over alternatives, nor does it provide exclusion criteria or mention of sibling tools like 'get_product' or 'check_inventory'.

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?

Annotations already declare readOnlyHint=true and openWorldHint=true, but the description adds value by specifying the exact data fields returned (variants, dimensions, weight, inventory). This provides context beyond the annotations without contradicting them.

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 description is concise, front-loaded with the action and resource, and includes essential product details. Every word contributes to clarity with no redundant information.

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

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

For a simple tool with one parameter and no output schema, the description provides a reasonable overview of the output content. However, it lacks information on the result structure, error handling, or any pagination, leaving some ambiguity for the agent.

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

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

The schema has 0% description coverage for the 'handle' parameter. The description only mentions 'by handle' without explaining what a handle is, its format, or examples. More detail is needed to help the agent provide a valid input.

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 product detail by handle, listing specific fields like variants, dimensions, weight, and inventory. It distinguishes from sibling tools such as search_products (search) and get_pricing (pricing) by focusing on a single product's comprehensive 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 explicit guidance on when to use this tool versus alternatives. The description does not mention prerequisites (e.g., needing a handle from search_products) or scenarios where other tools (like check_inventory) might be more 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?

Annotations already provide readOnlyHint and openWorldHint. The description adds that it returns three pieces of data (URLs and text) but does not elaborate on side effects, authorization needs, or external dependencies beyond what annotations imply.

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: the first states what the tool returns, the second specifies its usage. No extraneous information.

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

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

Given no output schema, the description adequately lists the returned items. It lacks guidance on choosing between SKU and handle and does not mention authentication, but overall it is sufficient 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?

Schema coverage is 100%, so baseline is 3. The description does not add meaningful detail beyond the schema; it merely restates that the tool operates on SKU or handle. No explanation is given for source_context, analytics_context, or suppress_analytics.

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 returns a reorder URL, product URL, and copy-procurement-spec text for a given SKU or handle. It uses specific verbs and resources, though it does not explicitly differentiate from sibling tools like get_product or create_cart_url.

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 states 'Use for repeat-buy and procurement handoff workflows,' providing clear context. However, it does not mention when not to use or provide alternative tools.

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?

Annotations already declare readOnlyHint and openWorldHint, so the description's statement about returning rates adds little beyond that. It mentions the Shopify API, which hints at authentication needs, but does not elaborate on rate limits or other behavioral traits.

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

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

The description is two sentences long, front-loaded with the core action, and includes a relevant implementation detail. Every word is valuable, 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?

For a tool with 3 parameters and no output schema, the description covers the main inputs and outputs. Missing details include the enum constraint (only US/CA) and the minimum item count, but overall it is nearly complete for an agent to use 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?

With 0% schema description coverage, the description partially compensates by mentioning 'destination postal code', 'country', and 'cart of variants and quantities'. However, it does not specify parameter types, defaults, or constraints like minItems, leaving some interpretation to the agent.

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 returns shipping rate options given a destination postal code, country, and items. It distinguishes itself from sibling tools like get_pricing or check_inventory by focusing on shipping estimates, and mentions the underlying Shopify API, leaving no ambiguity.

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 when to use this tool (to get shipping rates for a cart), but it does not explicitly state when not to use it or provide alternative tools. The context is clear, but exclusions or comparisons are absent.

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?

Annotations indicate readOnlyHint=true and openWorldHint=true, which align with the description's mention of 'live' exploration. The description adds valuable behavioral details beyond annotations, such as specific data returned (location-level BOX quantities, fulfillment summary). No contradictory information.

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 tool's purpose and output. It is concise and to the point, with no unnecessary details. Slightly more action-oriented language could improve it.

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 4 parameters, no output schema, and no nested objects, the description provides a reasonable overview of return values. However, it lacks details on how parameters interact (e.g., multiple variant_ids) and does not mention error cases or optionality. Adequate but not 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 50%, so the baseline is 3. The tool description does not elaborate on parameters like 'quantity' or 'variant_ids' beyond what the schema provides. It mentions 'one or more variants', implying variant_ids usage, but adds no further semantic meaning.

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 specifies the tool is for inventory exploration of 'AI_APPROVE variants' and lists what it returns (Shopify total quantity, available-for-sale, etc.). It provides a clear resource and action, though the verb 'exploration' is less direct than 'get' or 'check'. It distinguishes from the sibling 'check_inventory' by mentioning specific return fields.

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 the tool is for AI_APPROVE variants, providing some context, but it does not explicitly state when to use this tool over siblings like 'check_inventory' or 'search_products'. No exclusions or prerequisites are mentioned.

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?

Annotations already indicate read-only and open-world. The description adds that it calculates dimensions, ranks box/mailer candidates, and provides void-fill guidance, clarifying the tool's exploratory nature. No contradiction.

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 with no redundancy. Front-loaded with the core purpose, followed by specific outputs. 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?

For a tool with 7 parameters (3 required) and no output schema, the description gives a high-level overview but lacks details on return values, ranking criteria, or error conditions. Adequate for basic selection but incomplete for full understanding.

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 0%, and the description provides no explanation of any parameter, such as 'limit', 'use_case', or 'padding_in'. The agent must infer meaning from parameter names 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 it is an exploration tool for item dimensions and weight, calculating inside dimensions and ranking candidates. It differentiates itself from purchase/confirmation tools by mentioning 'before live price/inventory confirmation'. However, it does not explicitly distinguish from the sibling tool 'find_packaging_for_item'.

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

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

The description implies it's for initial exploration before price/inventory confirmation, but does not specify when not to use it or mention alternatives like 'find_packaging_for_item' or 'check_inventory'.

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?

Annotations already declare readOnlyHint: true, lowering the burden. The description adds useful behavioral context: it only executes when buyer_confirmed is true, and it confirms live price and inventory. No contradiction with annotations, as 'returns' does not imply mutation.

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 front-loaded sentences with no redundancy. Every word adds value, specifying the one-call nature, confirmation steps, and conditional return.

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

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

The description explains the core flow (confirm then return) but lacks output details (since no output schema) and sibling differentiation. Adequate for a moderate-complexity tool, but could be better with explicit output description or usage contexts.

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 75%, so the schema documents most parameters. The description repeats the importance of buyer_confirmed and mentions sku context but adds little beyond schema. Baseline score of 3 is appropriate given high coverage.

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: 'purchase prep for agents' using an exact SKU, and it confirms product, price, and inventory before returning a cart URL. It distinguishes itself from siblings like get_pricing or create_cart_url by specifying the confirmation and conditional return logic.

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 when an agent wants a one-call purchase prep with buyer confirmation. However, it does not explicitly state when to use this tool versus alternatives like get_cart_handoff_candidates or check_inventory, nor does it mention prerequisites or exclusions. Some guidance is provided but not comprehensive.

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?

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds that results are limited by the 'limit' parameter, which addresses the open-world behavior. It does not mention rate limits, authentication, or what happens with no results, but the annotations cover safety. 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?

A single sentence that concisely states the action, the resource, and the output. Every element is essential. No redundant phrases. Well front-loaded with the verb and noun.

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 only two parameters and no output schema, the description covers the basic functionality and return fields. It lacks details on pagination, sorting, or ordering, but the openWorldHint and limit parameter mitigate that. Adequate but could mention sorting or ordering behavior for 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?

Schema description coverage is 50%: 'query' is described in schema, 'limit' is not. The description adds context for 'limit' by stating 'Returns up to `limit` products', which clarifies its role. For 'query', the schema already specifies it matches title, vendor, type, tags, so the description does not add much. Overall, the description enhances the understanding of the limit parameter.

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 'Search', the resource 'Packrift catalog', and specifies the keyword-based interaction. It lists the return fields (price range, stock state, etc.), which distinguishes it from sibling tools like 'get_product' that retrieve a single product or 'check_inventory' that checks stock. The purpose is unambiguous and well-defined.

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 when you need to search products by keyword, but it does not explicitly state when not to use this tool or mention alternatives such as 'get_product' for exact product retrieval or 'check_inventory' for stock-only queries. No exclusions or prerequisites are provided.

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