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

With no annotations, the description carries full burden. It discloses the tool modifies the cart by adding items and returns a detailed response. It does not cover potential side effects like cart limits or authentication, but it is transparent about the core 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 well-structured with an arguments section and return value documentation. It is slightly long but every sentence adds value, and the main 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?

Given the presence of an output schema (though not shown), the description adequately explains return values and parameters. It covers all necessary information for using the tool effectively, given the context of sibling tools.

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

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

Schema description coverage is 0%, but the description compensates exceptionally well. It explains product_slug, quantity, and variation_attributes with examples and context on how to obtain them, adding significant meaning beyond the schema.

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

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

The description clearly states the tool adds a product to the Tuma250 shopping cart. It specifies the product slug and mentions variable products, distinguishing it from siblings like get_cart or 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 provides guidance on when to use the tool, such as using product slug from search_products or get_order_details, and advises on variation_attributes for variable products. It lacks explicit when-not-to-use instructions but is otherwise 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 provided, so description bears full burden. It details the return structure (items, totals, shipping) and implies a read-only operation. However, it lacks disclosure on authentication requirements or potential side effects (though unlikely).

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 concise, front-loaded with purpose, and uses a bulleted list for return fields. Every sentence adds value, with no redundancy or 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 zero parameters and existing output schema, the description provides rich context on the return value structure. It is mostly complete, though it could mention prerequisites (e.g., login) or state that cart persists per session.

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 zero parameters (100% schema coverage), so the description correctly adds no parameter info. The high schema coverage places baseline at 4, and the description does not need to add more.

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 the 'current contents of the Tuma250 shopping cart'. It uses a specific verb and resource, and clearly distinguishes from sibling tools like add_to_cart or list_recent_orders.

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 viewing cart contents after adding items, but does not explicitly state when to use it or when not to use it compared to siblings. 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 are provided, so the description must fully disclose behavioral traits. The description states that the tool fetches data and returns a dict with specific fields. It implies a read-only operation but does not explicitly confirm no side effects, authentication needs, or rate limits. The description is adequate for a simple read operation but stops short of full behavioral transparency.

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

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

The description is concise: one sentence for purpose, then an Args section and Returns section. No redundant words. The structure front-loads the main action and uses clear formatting. 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 that an output schema exists (signaled in context), the description still usefully outlines the return structure including fields like order_id, items, and their subfields. This provides enough detail for an agent to understand what to expect. The tool is simple (one required parameter, no undefined behavior), so the description is 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?

The input schema only defines the parameter 'order_id' as a required string. The description adds essential context: 'The WooCommerce order ID (from list_recent_orders).' This tells the agent where to obtain the ID and reassures its format. Since schema description coverage is 0%, the description compensates well by providing this critical usage hint.

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 'Fetch the line items for a specific Tuma250 order.' It uses a specific verb ('fetch') and resource ('line items for a specific order'), and the tool name 'get_order_details' aligns perfectly. Among siblings like 'list_recent_orders' and 'get_cart', this tool's purpose is distinctly to get detailed order information for a single order.

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 a clear usage hint by specifying that the order_id should come from 'list_recent_orders'. This implies a workflow sequence. However, it does not explicitly state when not to use this tool or mention any alternatives, so it misses explicit exclusions. The context signals show sibling tools that help define boundaries, but the description lacks a direct 'when to use' vs 'when not to use' statement.

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

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

With no annotations, the description fully describes the return format (list of variation objects with specific fields) and edge case behavior (returns empty list for simple products). It does not mention authentication needs or error handling, but the core behavioral traits are well covered.

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

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

The description is concise with no wasted words. It uses clear section headers (Args, Returns) and front-loads the purpose and usage context. Every sentence adds value.

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

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

Given the output schema exists and annotations are missing, the description provides a thorough explanation of the return values and their structure. It covers the tool's usage context, input source, and behavior for both variable and simple products, making it complete for this tool's needs.

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 explains the product_url parameter as 'Full product page URL (from search_products result["url"])', adding significant meaning beyond the schema's basic property definition.

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 available variants for a variable WooCommerce product, with a specific verb ('Return') and resource ('available variants'). It distinguishes itself from sibling tools by indicating it should be called after 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 states when to use this tool ('when search_products returns a product and you need to know which size/weight options exist before adding it to the cart'). It also provides context on the input (product_url from search_products result). It lacks explicit when-not or alternatives, but the context is clear and 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?

Without annotations, the description describes the return structure adequately but does not disclose behavioral traits like ordering (presumably by date), side effects, or prerequisites (e.g., login required).

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?

Concise, front-loaded purpose, followed by clearly labeled Args and Returns sections with 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?

Given the output schema is described and only one parameter, the description is mostly complete but lacks mention of ordering or authentication requirements.

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 description adds 'Maximum number of orders to return' to the limit parameter, which is not present in the schema's title/type alone, fully explaining its 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 clearly states the verb 'list' and resource 'recent orders from the Tuma250 My Orders page', distinguishing it from siblings like get_order_details (single order) and other 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?

No guidance on when to use this tool versus alternatives such as get_order_details for specific orders, or whether authentication via login is required.

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?

Discloses key behaviors: logs in only if not already authenticated, auto-login for other tools, returns success/message. Without annotations, this is sufficient, though could mention error handling more explicitly.

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?

Extremely concise: three sentences covering purpose, behavior, and return format. 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?

Complete for a simple authentication tool with zero parameters and a return dict. Output schema is implicitly described in the description text.

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

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

With no parameters and 100% schema coverage, the description adds no param info but doesn't need to. Baseline 4 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?

Clearly states that the tool ensures an authenticated session, explains it logs in using configured credentials if not already authenticated, and notes optionality. This distinguishes it from sibling tools which are all product/cart/order related.

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

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

Explicitly says when to use: optional because subsequent tool calls auto-login as needed. Provides clear guidance that calling this tool is not necessary in most cases.

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

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

No annotations are provided, so the description must disclose behavioral traits. It covers the return format and default behavior but does not explicitly state that the operation is read-only or mention authentication requirements. Given sibling tools include login, this is a notable gap, though the read-only nature is implied.

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

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

The description is well-structured with a header, Args, and Returns sections. It is concise but includes necessary details; each sentence adds value. Minor redundancy: 'list of product objects' could be inferred from 'each containing,' but overall efficient.

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

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

Given the tool's simplicity (2 params, no nested objects, output schema exists), the description covers purpose, parameters with examples, and return fields. It lacks error handling or edge case info, but for a straightforward search, 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?

With 0% schema coverage, the description fully compensates. It explains 'query' as a free-text search string with concrete examples, and 'max_results' as a maximum with default 10, adding meaning beyond the schema's titles 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?

The description explicitly states 'Search for products on the Tuma250 grocery site,' providing a clear verb (search) and resource (products) with site specificity. This distinguishes it from sibling tools like get_product_variations or login, which have 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 gives usage guidance with parameter examples ('e.g. "butter 500g" or "rice 5kg"') and explains the max_results default. However, it does not explicitly state when to use this tool versus alternatives, such as when a product ID is known (use get_product_variations). This omission prevents a higher score.

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