Lowvyn

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

With no annotations, the description carries full burden. It discloses that the tool uses verified UPC matches, suggesting reliability. It implies a read-only operation with no destructive effects. However, it does not explicitly state authorization needs, rate limits, or behavior on missing products.

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 with two sentences; the first sentence immediately states the purpose and input. No unnecessary words, and it is 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 simplicity (one parameter, no output schema, no annotations), the description adequately covers what the tool does, how it works (UPC matches), and what the output contains. Minor omission: no mention of error handling or return format details.

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 only parameter 'idOrUrl' is already described in the schema. The description merely repeats that input is a Lowvyn ID or retailer URL without adding further meaning or examples. With 100% schema coverage, baseline is 3.

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

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

The description clearly states the tool's purpose: given a product identifier, return cheaper alternatives on other Canadian retailers. It distinguishes itself from sibling tools like 'get_product' (single product info) and 'search_products' (searching for products) by focusing on price comparison.

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 implicitly guides when to use this tool: when you have a specific product ID or URL and want to compare prices across retailers. It does not provide exclusions or alternatives explicitly, but the context of sibling tools makes its use case clear.

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 implies a read-only operation but does not explicitly confirm idempotency or side-effect-free behavior. The description could be more explicit about the output.

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 with no unnecessary words. It front-loads the main purpose and adds a usage hint.

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 annotations, the description adequately covers the tool's purpose and a use case. However, it could describe the return format (e.g., 'returns list of category names with item counts') 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?

The tool has no parameters, and schema coverage is 100%. The description adds value by confirming the tool requires no filtering inputs, implying it lists all categories.

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 lists product categories with item counts, using a specific verb ('List') and resource ('product categories'). It also hints at its relationship to search_products, distinguishing it from sibling 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 indicates the tool is useful for narrowing search_products calls, providing context for when to use it. However, it does not explicitly state when not to use it or mention 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?

No annotations are provided, so the description carries the full burden. It accurately states the tool returns daily price history but does not disclose behaviors like error handling, return format details, or any rate limits. The description adds some context beyond the schema but is not comprehensive.

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-loading the core purpose and then providing a use case. There is no unnecessary information, making it concise 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 absence of an output schema and annotations, the description could be more complete. It does not specify the exact structure of the returned pairs (e.g., objects with date and price fields) or ordering. While adequate for a simple tool, it 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?

Schema coverage is 100%, with both parameters described in the schema. The description adds no additional meaning beyond what is already in the schema, merely restating the days constraint. 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 returns daily price history as (date, price) pairs, up to N days. It uses a specific verb and resource, and the mention of verifying sale genuineness distinguishes it from sibling tools like find_cheaper or verify_deal.

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 tells the agent to use this tool to verify whether a sale is genuine or if the price was higher before. While it does not list alternatives, the context of sibling tools and the specific use case provide clear guidance.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns specific fields (title, price, score, etc.) and implies a read-only operation. However, it does not mention error handling, rate limits, or authentication requirements.

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, focused and front-loaded. The first sentence states the main purpose and inputs, and the second lists the outputs. 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 the tool's simplicity (one parameter, no output schema), the description is complete. It explains both input and output in sufficient detail for an agent to understand how to invoke it and what to expect.

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%, but the description adds value by specifying the exact supported retailer domains (amazon.ca, walmart.ca, bestbuy.ca) beyond the schema's general description. This clarifies the acceptable URL formats.

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 'Look up a product by Lowvyn ID OR retailer URL' with a specific verb and resource. It lists the exact returned fields and distinguishes itself from siblings like search_products (for searching) and get_price_history (for trends).

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 have a known ID or URL and need product details with score/verdict, but it does not explicitly state when not to use it or provide alternatives like search_products for unknown products or get_price_history for historical data.

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. 'List' clearly indicates a read-only operation, and no side effects are implied. The description is straightforward and consistent with expected behavior.

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

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

The description is a single sentence with no redundant words, front-loading the key information: 'List the Canadian retailers'.

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 sufficiently covers the return value (list of retailers with counts and timestamps). It does not mention pagination or ordering, but for a simple list tool, this 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?

There are no parameters (schema coverage 100%), so the description adds value by specifying the output contents (item counts and timestamps) 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 clearly identifies the action ('List') and the resource ('Canadian retailers Lowvyn currently tracks'), and specifies included data (item counts, last-update timestamps). It distinguishes itself from siblings like 'search_products' 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 implies usage context (when a list of retailers is needed) but provides no explicit when-to-use or when-not-to-use guidance compared to sibling tools. No exclusions or alternatives 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?

No annotations provided, so description carries full burden. It discloses return limit of 20 products and output fields but lacks details on ordering, case sensitivity, authentication, or error behavior. Adequate but not comprehensive.

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 efficiently conveys purpose, filters, and output. No redundancy or 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 the complexity (4 params, no output schema, no annotations), the description is missing details like result ordering, pagination beyond limit, and error handling. Adequate but notable gaps.

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

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

Schema description coverage is 100%, and the tool description adds minimal value beyond the schema. It summarizes filters (category slug, max price, retailer) but does not provide additional context beyond what the schema already contains.

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 'Search the Canadian product catalogue' with specific filters (category, max price, retailer) and output (up to 20 products with price and Lowvyn Score). It distinguishes itself from siblings like 'get_product' (single product) and 'find_cheaper' (price comparison).

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 for broad product search but does not explicitly state when to use versus alternatives like 'get_product' or 'verify_deal'. No when-not or exclusion criteria are given.

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

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

No annotations are provided, so the description carries full burden. It discloses that it compares against Lowvyn's price history and returns one of five verdicts, which is transparent about the internal logic. However, it does not explicitly state that the operation is read-only or note any prerequisites (e.g., authentication), but the nature of 'verify' implies no 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?

The description is exceptionally concise: two sentences that cover purpose, inputs, output format, and the comparison logic. Every sentence adds value, and the core action is 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 tool with only two parameters and no output schema, the description provides all necessary context: what inputs are needed, what the tool does internally, and the possible output verdicts. No critical information is missing for correct 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?

The input schema already provides 100% coverage with good descriptions for both parameters. The description does not add significant new semantic information beyond restating the parameters' roles. It does, however, explain the output verdicts, which aids understanding but is not parameter-specific.

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 action: given a product URL and claimed price, it returns a deal verdict. It lists the possible verdicts, making the purpose unambiguous. Compared to siblings like search_products or get_price_history, this tool's unique function is immediately apparent.

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 verifying a specific deal, but it does not explicitly state when to use this tool versus alternatives (e.g., using get_price_history for price trends or search_products to find deals). No exclusion criteria or best-use context is provided, leaving room for agent misinterpretation.

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