Packrift MCP

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

Annotations already mark the tool as read-only and open-world. The description adds behavioral context by indicating the data is real-time and never cached, which is useful. 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 two short sentences, no fluff, and immediately states the core purpose and key trait (live/unceached). 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?

For a simple read-only tool with one parameter and no output schema, the description covers purpose and data freshness. However, it does not hint at the return format (e.g., mapping or single count), which could help an agent anticipate the response.

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 0% coverage, so the description must compensate. It clarifies that the variant_ids parameter accepts one or more IDs, matching the minItems constraint, but does not explain the format or source of variant IDs. Minimal added value over the schema structure.

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

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

The description clearly states the tool provides real-time inventory counts for specific variant IDs, using a specific verb and resource. It distinguishes from siblings like get_pricing or get_product by focusing on live inventory data.

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

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

The description implies usage when real-time inventory is needed ('Live, never cached'), but does not explicitly state when to use this tool versus alternatives like get_product or search_products, nor does it mention 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?

Annotations already indicate readOnlyHint=true and openWorldHint=true. The description adds that the tool returns ranked candidates and a comparison summary, which is the key behavioral output. No contradictions exist, and the description effectively complements the 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 concise sentence divided into two clear clauses. It front-loads the purpose ('Exploration tool for buyers comparing...') and wastes no words. Every part 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 the tool's complexity (4 parameters, no output schema), the description covers the core purpose and outputs. It does not explain ranking criteria or differentiate from siblings, but as an exploration tool the context is sufficient for an agent to understand expected behavior.

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 50% (requested_spec and competitor_reference have descriptions). The tool description reinforces the meaning of requested_spec by mentioning 'packaging spec, competitor-style item, or Uline-style request', but does not cover limit or family parameters. It adds moderate value beyond the schema but does not fully compensate for the missing parameter 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 purpose: comparing a packaging spec, competitor-style item, or Uline-style request against Packrift AI_APPROVE products, and returning ranked candidates plus a plain-language summary. It uses a specific verb ('comparing') and resource, and its purpose is distinct 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 buyers comparing specs but does not explicitly state when to use this tool versus alternatives. No exclusions or alternative sibling tool names are mentioned, leaving the agent to infer context. This is adequate but lacks explicit 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 and openWorldHint, which are consistent with the description. The description adds behavioral details like always appending ?ref=mcp and optionally adding discount codes, which are beyond what annotations provide.

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 concise sentences, front-loaded with the main action, and every word adds value. No unnecessary 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?

The description is fairly complete for a simple URL builder: it explains the key parameters and behavior. It does not explain the return value, but that is implicitly a URL string. The missing details on error handling are 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?

With 0% schema coverage, the description partially compensates by explaining items as variants and quantities, and mentioning discount_code. However, it does not detail the structure of the items array or format of variant_id, leaving some ambiguity.

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 builds a Shopify cart permalink for given variants and quantities, which is a specific verb and resource. It differentiates from sibling tools like check_inventory or get_product, 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 when to use it (to generate a cart link) but does not provide explicit guidance on when not to use it or how it compares to alternatives. The mention of appending ?ref=mcp is a usage detail, but lacks exclusions or 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?

Annotations declare readOnlyHint true, but the description mentions returning a 'tracked bulk quote URL,' which may imply a side effect or mutation, contradicting the annotation. The description does not clarify whether tracking involves state changes or external calls, leaving behavioral ambiguity.

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

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

The description is a single concise sentence covering the tool's key actions without redundancy. It is front-loaded with the primary purpose, though it could be structured with more detail on outputs.

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

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

With 6 parameters including nested objects, no output schema, and no explanation of return format, the description is incomplete. It fails to clarify the structure of 'safe next actions' or the role of parameters like analytics_context and suppress_analytics.

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 parameters are well-documented in the schema. The description does not add any additional meaning or usage hints beyond what the schema provides, meeting the baseline for 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 explains why a nearby product is not an exact match and returns safe next actions and a tracked bulk quote URL. It distinguishes itself from sibling tools like get_bulk_quote_link by including explanation and next actions, though the purpose could be more specific.

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 there is no exact match, but it does not explicitly state when to or not to use this tool, nor does it mention alternatives like search_products or get_bulk_quote_link. The context is clear but lacks exclusionary 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 indicate readOnlyHint=true and openWorldHint=true, and the description aligns by stating it returns results (5 SKUs). It adds behavioral details (ranked by fit, includes price/stock/URL) without contradicting 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?

Three sentences, front-loaded with usage guidance, no unnecessary 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 5 required params, no output schema, and low schema coverage, the description covers usage, inputs, and output summary. It could elaborate on 'ranked by fit' but is adequate 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?

Schema coverage is 0%, so the description compensates by listing all parameters and their units (L/W/D in, weight lb, use_case with enum values). This adds meaning beyond the schema, though it doesn't describe constraints like minimum values.

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: given an item's L/W/D, find the right packaging. It also mentions alternative names like 'box-vs-mailer' and 'Uline-by-size', which distinguishes it from siblings such as check_inventory and search_products.

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 the user has an item's L/W/D and needs the right box or mailer', providing a clear context. It does not list when not to use or contrast with siblings, but the given 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 already indicate readOnlyHint=true and openWorldHint=true, so the description is consistent. It adds value by noting the tool 'returns a tracked URL', which is behavioral context not in annotations. 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?

The description is two sentences, directly stating what the tool does and when to use it. No extraneous words; each sentence serves a purpose.

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

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

Given 7 parameters and no output schema, the description provides essential context: purpose, condition, and output type. The schema handles parameter details. It is complete enough for an agent to understand when to invoke this 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 description coverage is 100%, so the schema already documents all parameters. The description does not add additional meaning beyond mentioning 'exact requested packaging spec or SKU', which maps to existing schema descriptions. 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 verb 'Return' and the resource 'tracked Packrift bulk quote URL', and specifies the condition 'for an exact requested packaging spec or SKU'. It also distinguishes from siblings by mentioning 'bulk/procurement review'.

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 when to use this tool: 'Use when there is no exact match or the buyer needs bulk/procurement review.' This provides clear context and implies when not to use (e.g., when an exact match exists).

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 readOnly and openWorld hints. Description adds significant behavioral context: what the response contains (arguments, records, links, live-confirmation sequence) and that it's AI-filtered and priority-based.

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 packs all essential information, but could benefit from structured breakdown for easier parsing by an AI agent. 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?

Covers purpose, input options, and output contents, including the live-confirmation sequence. Slightly incomplete regarding limit behavior and pagination, but adequate for the tool's complexity.

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

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

Schema coverage is high (67%), so baseline is 3. Description does not add additional meaning or constraints beyond the schema for parameters like sku, limit, or family.

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?

Clearly states it returns priority AI-approved SKUs ready for handoff, including specific elements like create_cart_url arguments and links, distinguishing it from sibling tools like check_inventory 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?

Implied usage for selecting SKUs ready for cart handoff exploration, but lacks explicit alternatives or when-not-to-use guidance. Context is clear enough.

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 readOnlyHint=true and openWorldHint=true. Description adds context about real-time and no caching, which aligns with annotations. 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: first states purpose, second adds key attribute. No wasted words, 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?

Missing output schema means description should clarify return structure. Only mentions 'price and available quantity' without detail. Does not explain how quantity input relates. Incomplete guidance for agent.

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

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

Schema coverage is 0%, so description must compensate. It explains variant_ids but completely omits the 'quantity' parameter, leaving agent unaware of its purpose and default 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?

Clearly states it returns real-time price and available quantity for variant IDs. Distinguishes from siblings like check_inventory and get_product by focusing on pricing and live data.

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

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

Implies usage when live, uncached data is needed via 'Live, never cached,' but provides no explicit instructions on when to use versus alternatives like 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 indicate safe read-only behavior (readOnlyHint, openWorldHint). The description adds context on what data is returned (variants, dimensions, etc.), which is valuable 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?

Single sentence that is front-loaded and efficient, containing no filler words. Every word contributes to understanding the tool's function.

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

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

For a simple tool with one parameter and no output schema, the description adequately conveys the purpose and output scope. Could mention return format but 'full product detail' suffices.

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% and the description only mentions 'by handle' without defining what a handle is or giving format examples. It adds minimal meaning beyond the parameter name.

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 'Full product detail by handle' with specific fields (variants, dimensions, weight, inventory), distinguishing it from sibling tools like check_inventory and get_pricing which focus on specific aspects.

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

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

The description implies use when a product handle is known and full details are needed. While it doesn't explicitly compare to siblings, the unique purpose is clear given the sibling tool names.

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=true and openWorldHint=true, so the description is not required to disclose safety. The description adds that it returns URLs and text, which is consistent with read-only. No behavioral traits beyond what annotations imply are described, but 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 two sentences, front-loaded with the primary action and result. No redundant words; every sentence adds value for the agent.

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 presence of 5 optional parameters and no output schema, the description provides enough context for the intended use case. However, it lacks details on parameter precedence (sku vs handle) and the exact structure of the returned data, which could be helpful.

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 all parameters. The description does not add further meaning to parameters, so 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 it returns a reorder URL, product URL, and procurement spec text for a PKU or handle. It specifies the context of AI_APPROVE and workflows (repeat-buy, procurement handoff), distinguishing it from siblings like get_product or get_pricing.

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 for repeat-buy and procurement handoff workflows,' which provides clear context for when to use the tool. However, it does not mention when not to use it or name alternative tools for different scenarios.

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

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

Annotations already declare readOnlyHint and openWorldHint, so the description adds limited behavioral context beyond mentioning the underlying Shopify API. It does not discuss rate limits, error conditions, or data freshness, but it does not contradict the 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 two sentences long, front-loaded with the core purpose, and each sentence adds value. No unnecessary words or repetition.

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 read-only estimate tool with three required parameters and no output schema, the description provides adequate but minimal context. It explains the input parameters at a high level and indicates the output type (shipping rate options), but lacks details on output format, pagination, or error handling.

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 should compensate by explaining parameter meaning and constraints. It only vaguely mentions 'cart of variants and quantities,' which maps to items but does not detail the structure or required fields. The country enum is self-explanatory, but destination_postal_code format is not addressed.

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 'Returns available shipping rate options to a destination postal code for a cart of variants and quantities.' It uses a specific verb and resource, and the purpose is distinct from sibling tools which cover inventory, pricing, products, 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 provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or constraints like required authentication or data availability. It only states what it does without contextual usage advice.

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 readOnlyHint and openWorldHint. The description adds valuable detail on return fields (Shopify total, available-for-sale, warehouse quantities, fulfillment summary). This provides sufficient behavioral 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, concise sentence that front-loads the core purpose ('Live inventory exploration'). It packs multiple return elements without being verbose, earning its length.

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?

While output details are well-covered, input specification is incomplete. The description does not explain how to use the four parameters together, nor does it note that 'quantity' is optional with a default. No output schema is provided, but the description compensates partially.

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 50% schema coverage, the description does not clarify parameter semantics. It does not explain the role of 'sku', 'handle', 'quantity', or 'variant_ids' in specifying inventory scope, leaving the agent to rely solely on the limited 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 is for live inventory exploration of AI_APPROVE variants, listing specific return data. However, it does not differentiate from similar sibling tool 'check_inventory', so it lacks sibling distinction.

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 'check_inventory'. The description does not mention use cases, 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?

The description adds value beyond the annotations (readOnlyHint, openWorldHint) by explaining the operational behavior: it calculates dimensions, ranks candidates, and gives guidance. This gives the agent context that the tool is exploratory and not final, which aligns with the annotations indicating safe, open-world results.

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 concise, consisting of two sentences that front-load the primary function. However, it could be slightly more structured (e.g., bullet points) to improve readability, though it remains 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?

The description is incomplete given the tool's complexity (7 params, no output schema). It does not describe the return value structure, leaving the agent unsure what to expect. The omission of output details and parameter semantics hinders effective invocation.

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

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

With 0% schema description coverage, the description should compensate by explaining the parameters' roles. It mentions 'item dimensions and weight' but does not describe individual parameters like 'limit', 'use_case', or 'padding_in'. The agent lacks guidance on how these parameters affect the calculation or ranking.

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 is an exploration tool for item dimensions and weight, calculating inside dimensions, ranking Packrift box/mailer candidates, and providing void-fill guidance. It distinguishes itself from sibling tools by specifying it is used 'before live price/inventory confirmation', setting it apart from pricing and inventory tools.

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

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

The description provides clear context on when to use this tool ('before live price/inventory confirmation' and as an 'exploration tool'), implying it should be used to assess packaging options before committing to a final selection. However, it does not explicitly state when not to use it or name specific 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?

Annotations (readOnlyHint=true) already declare safety. The description adds behavioral context: returns up to limit products with specific fields (price range, stock state, etc.). No contradictions. It doesn't cover pagination or ordering details, but adds value 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?

Two sentences with no waste. The verb and resource are front-loaded. Every word adds value: keyword search, return fields, limit behavior.

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

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

The tool is simple (2 params). Description covers return fields (price range, stock state, image, URL) which is adequate despite no output schema. It could mention sorting or error behavior, but for a search tool it's reasonably 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% (query described). The description adds meaning for 'limit' by stating it controls number of results. For 'query', it restates schema info. Overall, it compensates somewhat for the uncovered parameter but adds no new format or constraints beyond schema defaults.

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 'Search the Packrift catalog by keyword', specifying the verb (search) and resource (catalog). It distinguishes from siblings like 'get_product' (single product by ID) and 'check_inventory' (stock level). The return details (up to limit products with specific fields) further clarify its 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 implies when to use (keyword search) but lacks explicit guidance on alternatives like 'get_product' for exact matches or 'check_inventory' for stock details. It mentions returns up to limit products, hinting at listing usage, but no 'when-not-to-use' statements.

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