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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions adding a contact section but doesn't clarify whether this is a write operation, what permissions are needed, if it's idempotent, or what happens on failure. For a tool that likely modifies content, this is a significant gap.

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 directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded with the core action.

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 9 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain the return value, error conditions, or behavioral nuances like whether the contact section is appended or inserted at a specific position. The context demands more completeness for a content-creation tool.

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

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

The schema description coverage is 100%, so all parameters are documented in the schema itself. The description adds no additional parameter semantics beyond implying the tool creates a structured contact section, which is already evident from the parameter names. Baseline 3 is appropriate when the schema does the heavy lifting.

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 action ('Add a contact section') and the resource type ('with contact information and optional form placeholder'), making the purpose understandable. However, it doesn't explicitly differentiate this from sibling tools like 'add_cta' or 'add_features' beyond the contact-specific nature.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'add_cta' or 'add_features', nor does it mention prerequisites (e.g., needing an existing page). It only describes what the tool does, not when it's 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?

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Add' implies a write/mutation operation, but the description doesn't specify whether this requires specific permissions, what happens if the page_id doesn't exist, whether the CTA is appended or inserted at a specific position, or what the response looks like. For a mutation tool with zero annotation coverage, this is a significant gap in 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 maximally concise at just 5 words ('Add a call-to-action section'), with zero wasted words. It's front-loaded with the core action and resource, making it immediately scannable and understandable. Every word earns its place in conveying the essential 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?

For a mutation tool with 5 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't address behavioral aspects like error conditions, positioning within pages, visual characteristics, or how this integrates with the broader system of sibling tools. The agent lacks context about what 'success' looks like or potential pitfalls.

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 5 parameters with basic descriptions. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain relationships between parameters (e.g., how heading and subheading work together), format requirements, or constraints. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 'Add a call-to-action section' clearly states the verb ('Add') and resource ('call-to-action section'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'add_hero' or 'add_features' which also add sections, leaving room for confusion about what specifically distinguishes a CTA section from other section types.

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. With many sibling tools like 'add_hero', 'add_features', and 'insert_element', there's no indication of whether this is for specific page types, contexts, or how it relates to other section-adding tools. The agent must infer usage from the tool name alone.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. 'Add a FAQ section' implies a write/mutation operation, but it doesn't specify permissions required, whether it's idempotent, how errors are handled, or what the output looks like (e.g., success confirmation or new element ID). This leaves significant gaps for an agent to understand the tool's behavior beyond basic intent.

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 ('Add a FAQ section') that is front-loaded and wastes no words. It directly conveys the core action without unnecessary elaboration, making it easy to parse quickly.

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

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

Given the complexity of a mutation tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain the return value, error conditions, or integration with other tools (e.g., how this relates to 'get_page_structure' or 'update_element'). For a tool that modifies content, more context is needed to use it effectively.

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 input schema fully documents parameters ('page_id', 'heading', 'faqs') with descriptions. The description adds no additional meaning beyond what's in the schema (e.g., no examples, formatting rules, or constraints), meeting the baseline score of 3 for high schema coverage without extra 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 'Add a FAQ section' clearly states the verb ('Add') and resource ('FAQ section'), but it's vague about what this entails compared to siblings like 'add_contact' or 'add_testimonial'. It doesn't specify whether this creates a new page element, modifies an existing one, or how it integrates with the page structure, making it less distinct from other 'add_' 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 is provided on when to use this tool versus alternatives. For example, it doesn't mention prerequisites like needing an existing page (implied by 'page_id' but not stated), or how it differs from other content-adding tools in the sibling list. The description lacks context about typical use cases or exclusions.

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

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

No annotations are provided, so the description carries the full burden. It describes layout behavior ('magazine' places images beside text, 'grid' stacks images below) and notes that 'image_prompt' is 'REQUIRED for magazine layout,' which adds useful operational context. However, it doesn't cover other behavioral aspects like error handling, permissions, or rate limits, leaving gaps for a mutation tool.

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

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

The description is appropriately sized and front-loaded, starting with the core purpose. Every sentence adds value: the first states the action, the second provides critical layout guidance, and the third reinforces usage context. It's efficient with no wasted words, though it could be slightly more structured for a 5.

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 (5 parameters, no annotations, no output schema), the description is adequate but incomplete. It covers layout semantics and usage context well, but as a mutation tool, it lacks details on permissions, side effects, or response format. It's minimally viable but has clear gaps in behavioral transparency.

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 baseline is 3. The description adds value by emphasizing the importance of the 'layout' parameter and providing semantic context: it explains that 'magazine' is 'BEST for articles, blog posts, and content pages' and details how layouts affect image placement. This goes beyond the schema's enum descriptions, justifying a 4.

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: 'Add a features/content section.' It specifies the resource (features/content section) and the action (add), making the purpose explicit. However, it doesn't distinguish this tool from sibling tools like 'add_contact' or 'add_faq' beyond the general 'features/content' focus, which is why it doesn't reach a 5.

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 for when to use the 'magazine' layout ('for content with images,' 'best for articles, blog posts, and content pages') and contrasts it with 'grid' layout. It doesn't explicitly mention when to use 'bento' or when to choose this tool over other 'add_' siblings, but the layout guidance is strong enough for a 4.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool adds a section, implying a write/mutation operation, but doesn't clarify permissions needed, whether the addition is reversible, potential side effects, or error conditions. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence that front-loads the core action and resource. There's no wasted verbiage, and it directly communicates the tool's function without redundancy. Every word earns its place, making it easy to parse quickly.

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

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

For a mutation tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like success/failure responses, idempotency, or integration with other tools (e.g., how it relates to 'create_page'). The agent lacks sufficient context to use this tool effectively beyond basic parameter filling.

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 mentions 'grid layout', which hints at the 'columns' parameter, but doesn't add meaningful semantics beyond what the schema already provides. With 100% schema description coverage, the baseline is 3, as the schema fully documents all parameters (page_id, heading, images, columns, lightbox). The description doesn't compensate with additional context like format examples or constraints.

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 action ('Add') and resource ('image gallery section with grid layout'), making the purpose evident. It distinguishes itself from siblings like 'add_contact' or 'add_hero' by specifying the type of content being added. However, it doesn't explicitly differentiate from other content-adding tools in terms of when to choose a gallery over alternatives.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'add_features' or 'add_team'. It lacks context about prerequisites (e.g., needing an existing page), exclusions, or comparisons with sibling tools. The agent must infer usage from the tool name and parameters alone.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions automatic text color adaptation and default gradient backgrounds, which adds some context. However, it lacks critical details like whether this is a mutation (likely, given 'add'), permission requirements, rate limits, or what happens on success/failure.

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, well-structured sentence that efficiently lists layout options and key features (automatic contrast, default gradient). Every part earns its place with no wasted words, making it front-loaded and easy to parse.

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 (8 parameters, mutation likely), no annotations, and no output schema, the description is moderately complete. It covers layout types and some behavioral traits but misses mutation implications, error handling, and output details. It's adequate but has clear gaps for a tool of this nature.

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 8 parameters thoroughly. The description adds minimal value beyond the schema—it mentions layout types and automatic contrast adjustment, but these are already implied or covered in the schema's enum and descriptions. Baseline 3 is appropriate when schema does the heavy lifting.

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 premium hero section' with specific layout options, which is a specific verb+resource combination. It distinguishes from siblings like 'add_contact' or 'add_features' by focusing on hero sections, though it doesn't explicitly contrast with similar layout tools (none exist in the sibling list).

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

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

No explicit guidance on when to use this tool versus alternatives like 'add_cta' or 'add_features' is provided. The description mentions layout types but doesn't indicate scenarios where one layout would be preferred over another or prerequisites for 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool adds a section but doesn't cover critical aspects: whether this is a mutation (likely, given 'add'), what permissions are required, if it's idempotent, how errors are handled, or what the output looks like. For a tool that presumably modifies content, this lack of transparency is a significant gap.

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 directly states the tool's function without fluff. It's front-loaded with the core action ('Add a pricing section') and includes the key constraint ('with 2-3 pricing tiers'), making it easy to parse quickly. Every word 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 the tool likely performs a mutation (adding content) with no annotations and no output schema, the description is insufficient. It doesn't address behavioral risks, expected outcomes, or error conditions. For a tool with 4 parameters and complex nested structures in 'tiers', more context is needed to ensure safe and effective use by an AI 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 description mentions '2-3 pricing tiers', which aligns with the 'tiers' parameter in the schema, but adds no further semantic context beyond what the 100% schema coverage already provides. It doesn't explain the relationship between parameters (e.g., that 'tiers' contains nested objects) or offer usage examples. With high schema coverage, the baseline is met but not exceeded.

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 action ('Add a pricing section') and specifies the content ('with 2-3 pricing tiers'), making the purpose immediately understandable. It distinguishes from siblings like 'add_contact' or 'add_faq' by focusing on pricing tiers, though it doesn't explicitly contrast with similar tools like 'add_features' or 'add_hero' beyond the subject matter.

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

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

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a page created first), nor does it explain how it differs from other 'add_' tools like 'add_features' or 'add_cta' in context. The description is purely functional without contextual 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?

With no annotations, the description carries the full burden of behavioral disclosure. It states 'add' implying a write operation, but doesn't clarify permissions, side effects (e.g., whether it modifies page structure irreversibly), or error handling. No rate limits, authentication needs, or response format are mentioned, leaving significant gaps for a mutation tool.

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

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

The description is a single, efficient sentence that front-loads the core action ('add a team section') and key feature ('with member cards'). There is zero wasted text, and it directly communicates the tool's function without redundancy.

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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't address behavioral aspects like what happens on success/failure, whether the section is editable later, or how it integrates with sibling tools (e.g., 'update_element'). Given the complexity of nested 'members' data, more context would help an agent use it correctly.

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

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

Schema description coverage is 100%, so the schema fully documents all 4 parameters and nested structures. The description adds no additional parameter semantics beyond what's in the schema (e.g., no examples for 'members' array size beyond the schema's '2-4 recommended'). Baseline 3 is appropriate as the schema does the heavy lifting.

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 action ('add a team section') and resource ('with member cards'), making the purpose understandable. It distinguishes from siblings like 'add_contact' or 'add_testimonial' by specifying team content, though it doesn't explicitly contrast with them. The verb 'add' is specific enough for a creation tool.

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

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

No guidance is provided on when to use this tool versus alternatives like 'add_contact' or 'add_features'. The description lacks context about prerequisites (e.g., needing a valid page_id) or exclusions (e.g., not for updating existing sections). Usage is implied only through the tool name and parameters.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Add' which implies a write/mutation operation, but doesn't specify permissions required, whether changes are reversible, or any side effects like rate limits or confirmation steps. This is inadequate for a mutation tool with zero annotation coverage.

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 with a single phrase ('Add a testimonial/quote section'), which is front-loaded and wastes no words. It efficiently conveys the core purpose without unnecessary elaboration.

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 involves a mutation (adding content) with no annotations and no output schema, the description is insufficient. It lacks details on behavioral traits, expected outcomes, error conditions, or how it integrates with sibling tools, making it incomplete for safe and effective use.

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 parameters are well-documented in the schema itself. The description adds no additional meaning beyond implying that 'testimonial/quote section' relates to the parameters, but doesn't clarify relationships or usage nuances. This meets the baseline for high schema 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 action ('Add') and the resource ('testimonial/quote section'), making the purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'add_contact' or 'add_faq' beyond the specific type of content being added, which slightly limits its distinctiveness.

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, such as other 'add_' tools for different content types or tools like 'update_element' for modifying existing testimonials. There's no mention of prerequisites, context, or exclusions, leaving usage unclear.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool applies a preset but doesn't explain what 'apply' entails operationally - whether this modifies existing content, requires specific permissions, has side effects, or what happens to existing styling. For a mutation tool with zero annotation coverage, this is insufficient 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 extremely concise - just two sentences with zero wasted words. The first sentence states the purpose, the second provides critical usage guidance. Every element earns its place, and the structure is front-loaded with the core functionality.

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 single-parameter tool with good schema coverage but no annotations or output schema, the description provides adequate but minimal context. It explains what the tool does and when to use it, but lacks details about the mutation behavior, side effects, or what 'applying' a preset actually means operationally. The completeness is borderline adequate.

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

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

The input schema has 100% description coverage with a clear enum for the single parameter. The description doesn't add any parameter-specific information beyond what the schema already provides (no syntax details, format explanations, or usage examples). With complete schema coverage, the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'Apply a style preset to ensure consistent, professional design.' It specifies the action (apply) and resource (style preset) with a quality goal (consistent, professional design). However, it doesn't distinguish this from sibling tools like 'detect_style_preset' or 'get_active_preset', which are related but different operations.

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

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

The description provides explicit usage guidance: 'ALWAYS use this before creating sections.' This gives clear temporal context (when to use) and implies it's a prerequisite for other operations. While it doesn't name specific alternatives, the 'ALWAYS' directive provides strong operational 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates a page, implying a write operation, but doesn't cover permissions, side effects, error handling, or response format. This is inadequate for a mutation tool with zero annotation coverage.

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 directly states the tool's purpose without unnecessary words. It's front-loaded and appropriately sized, making it easy to parse quickly.

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

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

For a creation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, return values, and usage context, which are critical for an agent to invoke this tool effectively in a complex environment with many 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 100%, so the schema fully documents both parameters ('title' and 'status'). The description adds no additional meaning beyond what's in the schema, such as formatting details or constraints, resulting in the baseline score 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 action ('Create') and resource ('new WordPress page with Elementor'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'add_contact' or 'add_faq', which also create content but for different resource types, so it misses full 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, when to choose this over other creation tools (e.g., 'add_contact'), or any context-specific usage rules, leaving the agent with no explicit direction.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool performs a deletion, implying it's destructive, but doesn't mention critical details like whether the deletion is permanent, requires specific permissions, or has side effects (e.g., affecting page structure). This leaves significant gaps in understanding the tool's 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, direct sentence that efficiently conveys the core action without unnecessary words. It's front-loaded with the key information ('Delete an element'), making it highly concise and well-structured for quick understanding.

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 destructive nature, lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral risks, return values, or usage context, which are essential for safe and effective operation. This is inadequate for a deletion tool with potential side effects.

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 mentions deleting 'by its ID', which aligns with the 'element_id' parameter in the schema, but adds no additional meaning beyond what the schema already provides (e.g., format or constraints for IDs). With 100% schema description coverage, the baseline score of 3 is appropriate, as the schema adequately documents the parameters without extra value from the description.

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

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

The description clearly states the action ('Delete') and resource ('an element from a page'), making the purpose understandable. However, it doesn't distinguish this tool from the sibling 'delete_elementor_element', which likely serves a similar purpose but for Elementor-specific elements, leaving some ambiguity about when to use one versus the other.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'delete_elementor_element' or 'delete_page'. It lacks context about prerequisites, such as needing an existing page and element, or exclusions, making it minimally helpful for decision-making.

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 states the tool performs a deletion, which implies a destructive mutation, but it doesn't disclose behavioral traits such as permissions required, whether the deletion is reversible, error handling, or any rate limits. This is a significant gap for a mutation tool with zero annotation coverage.

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 front-loads the core action and includes the alias information without unnecessary details. Every word earns its place, making it highly concise and well-structured for quick understanding.

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 is a destructive mutation with no annotations and no output schema, the description is incomplete. It lacks critical context such as what happens post-deletion, error scenarios, or return values, which are essential for safe and effective use. The high schema coverage doesn't compensate for these behavioral 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?

The input schema has 100% description coverage, with clear parameter names and descriptions, so the baseline is 3. The tool description does not add any meaning beyond what the schema provides (e.g., it doesn't explain parameter formats or interactions), so it meets but does not exceed the minimum viable level.

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 action ('Delete') and resource ('Elementor element from a page'), making the purpose specific and understandable. It also mentions it's an alias for 'delete_element', which helps distinguish it from other deletion tools like 'delete_page'. However, it doesn't fully differentiate from 'delete_element' beyond the alias note, keeping it from a perfect score.

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 by specifying it deletes an element from a page, but it lacks explicit guidance on when to use this tool versus alternatives like 'delete_element' (beyond noting it's an alias) or other deletion tools. No context on prerequisites or exclusions is provided, leaving usage somewhat ambiguous.

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 of behavioral disclosure. While 'Delete' implies a destructive mutation, the description lacks critical details such as whether deletion is permanent or reversible, what permissions are required, if there are confirmation prompts, or what happens to associated data. This is a significant gap for a destructive operation.

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

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

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly without unnecessary elaboration.

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 destructive nature and lack of annotations or output schema, the description is incomplete. It doesn't cover behavioral aspects like permanence, error handling, or response format, which are crucial for safe and effective use. The schema covers parameters well, but overall context is insufficient.

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, with the 'page_id' parameter clearly documented as 'ID of the page to delete'. The description doesn't add any additional semantic context beyond this, such as format examples or sourcing tips, but the schema provides adequate baseline information.

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 'Delete a WordPress page' clearly states the verb ('Delete') and resource ('WordPress page'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'delete_element' or 'delete_elementor_element', which also perform deletion operations on different resources.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing the page ID), exclusions (e.g., not for posts or other content types), or comparisons with sibling deletion tools like 'delete_element', leaving the agent without contextual usage information.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'automatically detect' but lacks details on how the detection works (e.g., algorithm, criteria), what 'best' means (e.g., based on what metrics), or potential limitations (e.g., accuracy, response format). This leaves significant gaps for an AI agent to understand the tool's 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, efficient sentence that front-loads the core functionality ('Automatically detect the best style preset') and includes the key input ('based on business description'). There is no wasted text, making it appropriately concise and well-structured for its 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 the complexity of style detection (which likely involves subjective judgments) and the lack of annotations and output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., a preset name, ID, or settings), how results are determined, or any prerequisites, leaving the AI agent with incomplete context for effective use.

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, with the 'description' parameter documented as 'Business description or keywords'. The tool description adds minimal value beyond this, as it only restates 'based on business description' without providing additional context like format examples or usage tips. This meets the baseline for high schema 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 as 'Automatically detect the best style preset based on business description', which specifies the action (detect), resource (style preset), and input basis (business description). However, it doesn't explicitly differentiate from sibling tools like 'get_active_preset', 'list_style_presets', or 'apply_style_preset', which reduces it from a perfect score.

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. It doesn't mention when it's appropriate (e.g., for initial setup vs. updates) or when not to use it (e.g., if a preset is already applied), nor does it reference sibling tools like 'apply_style_preset' or 'list_style_presets' for comparison.

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 of behavioral disclosure. While 'find and replace' implies a mutation operation, the description doesn't clarify critical aspects such as permissions required, whether changes are reversible, potential side effects (e.g., affecting SEO or links), or error handling. This leaves significant gaps in understanding the tool's behavior beyond its basic function.

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 short sentences that front-load the core purpose. There's no unnecessary verbiage, and it efficiently communicates the tool's utility. However, it could be slightly improved by integrating usage guidance more seamlessly, but overall, it's well-structured and to the point.

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 complexity of a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., safety, permissions), output format, error conditions, and differentiation from sibling tools. While the schema covers parameters well, the overall context for safe and effective use is insufficient, especially for a tool that modifies content.

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, clearly documenting all four parameters (post_id, find, replace, case_sensitive). The description adds no additional parameter semantics beyond what's in the schema, such as examples, constraints, or usage tips. With high schema coverage, the baseline score of 3 is appropriate, as the schema adequately handles parameter documentation.

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 with a specific verb ('find and replace') and resource ('text in a post/page content and title'), making it easy to understand what the tool does. However, it doesn't explicitly distinguish this tool from potential siblings like 'update_post' or 'search_content', which might have overlapping functionality for content modification.

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 minimal guidance with 'useful for bulk text updates', which implies a use case but doesn't specify when to use this tool versus alternatives like 'update_post' or 'search_content'. There's no explicit mention of prerequisites, exclusions, or comparisons with sibling tools, leaving the agent with insufficient context for optimal tool selection.

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

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

No annotations are provided, so the description carries the full burden. It states the tool returns internal and external links with anchor text and URLs, which is useful behavioral context. However, it lacks details on permissions, rate limits, error handling, or whether it's a read-only operation (implied but not explicit). For a tool with no annotations, this is a moderate gap.

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 zero waste. It front-loads the purpose and efficiently explains the return value, making it easy to scan and understand quickly.

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

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

Given no annotations, no output schema, and a simple input schema, the description is minimally adequate. It covers the basic purpose and return format, but for a tool with no structured safety or output details, it could benefit from more behavioral context (e.g., read-only nature, error cases).

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 the 'post_id' parameter. The description adds no additional parameter semantics beyond what's in the schema (e.g., format examples or constraints). Baseline 3 is appropriate as the schema handles the heavy lifting.

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: 'Find all links in a post/page' specifies the verb (find) and resource (links), with the scope (post/page). It doesn't explicitly distinguish from siblings like 'search_content' or 'update_link', but the focus on link extraction is clear and non-tautological.

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. It doesn't mention siblings like 'search_content' (which might find links among other content) or 'update_link' (which modifies links), nor does it specify prerequisites or exclusions for 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states what the tool does ('Check which style preset is currently active') but doesn't describe what the return value looks like, potential errors, or any side effects. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded with the core function and wastes no space, making it highly concise and well-structured.

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

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

Given the lack of annotations and output schema, the description is incomplete for a tool that presumably returns information about the active style preset. It doesn't explain the return format, potential values, or how to interpret the result, leaving the agent with insufficient context to use the tool effectively.

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

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

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description appropriately doesn't mention parameters, which aligns with the schema. A baseline of 4 is given since no parameters exist and the description doesn't need to compensate for any gaps.

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 with a specific verb ('Check') and resource ('which style preset is currently active'), making it immediately understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'detect_style_preset' or 'list_style_presets', which prevents a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'detect_style_preset' or 'list_style_presets', nor does it mention any prerequisites or exclusions. It's a basic statement of function without contextual usage information.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a 'Get' operation, implying read-only behavior, but doesn't specify permissions required, rate limits, error handling, or what the returned data looks like (e.g., format, structure). This is a significant gap for a tool with no annotation coverage.

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—a single sentence that efficiently conveys the core purpose and alias relationship. It's front-loaded with the main action and resource, with no wasted words or 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?

Given the tool's complexity (data retrieval with one parameter) and lack of annotations or output schema, the description is incomplete. It doesn't explain what 'Elementor data' includes, the return format, or any behavioral aspects like errors or dependencies. For a tool in a server with many siblings, more context is needed to guide proper use.

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 no parameter-specific information beyond what the schema provides. With 100% schema description coverage (the 'page_id' parameter is documented as 'Page ID'), the baseline is 3. The description doesn't elaborate on what constitutes a valid page ID or how to obtain one, so it doesn't compensate but also doesn't detract.

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 as 'Get Elementor data for a page', specifying the verb 'Get' and resource 'Elementor data'. It distinguishes from siblings by mentioning it's an alias for 'get_elementor_elements', but doesn't explain what Elementor data entails or how it differs from other data-retrieval tools like 'get_page' or 'get_seo_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?

No explicit guidance is provided on when to use this tool versus alternatives. The alias mention implies it's equivalent to 'get_elementor_elements', but there's no context on why one might choose this over that sibling or other data-fetching tools like 'get_page_structure'. Usage is implied only by the tool name and description.

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 states it's a list operation, implying read-only behavior, but doesn't disclose any behavioral traits like pagination, rate limits, error conditions, or what happens with invalid page IDs. For a tool with no annotations, this leaves significant gaps in understanding its operation.

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, zero waste, front-loaded with the core action. Every word earns its place by specifying the resource and scope without redundancy.

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 annotations and no output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., list format, element details) or address potential complexities like handling nested elements. For a tool with rich sibling context, more completeness is needed.

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%, with the single parameter 'page_id' documented as 'Page ID'. The description adds no additional meaning beyond the schema, such as format examples or constraints. Baseline 3 is appropriate since the schema does the heavy lifting.

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 ('all Elementor elements on a page'), specifying the types of elements included (sections, columns, widgets). It distinguishes from siblings like get_page (which retrieves page metadata) or get_elementor_data (which might return raw Elementor data rather than structured elements).

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. It doesn't mention when not to use it (e.g., for non-Elementor pages) or compare to siblings like get_page_structure (which might provide similar structural info). The context is implied but not articulated.

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 ('get'), but doesn't disclose behavioral traits such as authentication needs, error handling (e.g., if page_id is invalid), rate limits, or what the return format might be (e.g., JSON with fields). This is inadequate for a tool with no annotation coverage.

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

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

The description is a single, efficient sentence with zero waste—'Get details of a specific page' is front-loaded and appropriately sized for a simple retrieval tool, making it easy for an agent to parse quickly.

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

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

Given no annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't explain what 'details' include, potential response structure, or error conditions, which are critical for an agent to use the tool effectively. This is a significant gap for a tool in a complex sibling set.

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%, with the single parameter 'page_id' documented as 'ID of the page'. The description adds no additional meaning beyond this, such as format examples (e.g., numeric ID) or context (e.g., where to find the ID). Baseline 3 is appropriate since the schema does the heavy lifting.

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

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

The description 'Get details of a specific page' clearly states the action (get) and resource (page), distinguishing it from siblings like 'get_pages' (list) or 'create_page' (write). However, it doesn't specify what 'details' include, leaving some ambiguity compared to tools like 'get_page_structure' or 'get_seo_data' that target 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?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't clarify if this should be used for retrieving basic page info versus more specialized tools like 'get_page_structure' for layout details or 'get_seo_data' for SEO metrics, leaving the agent to infer usage from tool names alone.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a list operation, implying read-only behavior, but doesn't cover critical aspects like pagination, rate limits, authentication needs, or what 'existing' means (e.g., excludes trashed pages). This leaves significant gaps for a tool with potential complexity.

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

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

The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly without unnecessary elaboration.

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 annotations, no output schema, and 2 parameters with full schema coverage, the description is minimally adequate. It covers the basic purpose but lacks behavioral details (e.g., return format, error handling) and usage context, making it incomplete for optimal agent operation despite the simple schema.

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, clearly documenting both parameters with defaults and enums. The description adds no parameter semantics beyond implying a list operation, so it meets the baseline of 3 where the schema does the heavy lifting without compensating 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 the verb ('List') and resource ('existing Elementor pages'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_page' (singular) or 'search_content' which might also retrieve pages, missing full 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention siblings like 'get_page' for single pages or 'search_content' for filtered searches, leaving the agent with no usage context or exclusions.

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

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

No annotations are provided, so the description carries the full burden. It mentions the tool retrieves JSON structure for understanding layout, but lacks details on permissions, rate limits, side effects, or response format. This is a significant gap for a tool that likely involves data access without behavioral context.

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

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

The description is a single, efficient sentence that front-loads the core purpose. It avoids unnecessary words, but could be slightly improved by adding brief context or differentiation, though it earns its place without waste.

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 annotations and no output schema, the description is incomplete. It doesn't explain what the JSON structure contains, how it's formatted, or any behavioral traits like error handling. For a tool with potential complexity in layout data, this leaves the agent under-informed.

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%, with the single parameter 'page_id' well-documented in the schema. The description adds no additional meaning beyond implying the page is inspected, so it meets the baseline of 3 without compensating for any gaps, as there are none in schema 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 action ('Get') and resource ('Elementor JSON structure of a page'), specifying it's for understanding the current layout. However, it doesn't differentiate from sibling tools like 'get_elementor_data' or 'get_elementor_elements', which might offer similar functionality, leaving some ambiguity about uniqueness.

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 is provided. The description implies usage for inspecting page layout, but it doesn't mention prerequisites, exclusions, or compare to siblings like 'get_elementor_data', leaving the agent to infer context without clear direction.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what data is returned but does not address critical behavioral aspects such as authentication requirements, error handling (e.g., what happens if post_id is invalid), rate limits, or whether the operation is idempotent. For a read operation with zero annotation coverage, this leaves significant gaps.

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 front-loads the core purpose and details the included content without any wasted words. Every part of the sentence contributes directly 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?

Given the tool's moderate complexity (single parameter, read operation) and lack of annotations and output schema, the description is partially complete. It specifies what content is retrieved but omits behavioral details and output structure. For a tool with no output schema, more information on return values would be beneficial, though the description covers the basic purpose adequately.

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%, with the single parameter 'post_id' clearly documented in the schema as 'Post or page ID'. The description does not add any additional meaning or context beyond what the schema provides, such as format examples or constraints, so it meets the baseline for high schema 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 specific verb 'get' and resource 'full content of a WordPress post or page', distinguishing it from siblings like get_page (which might return metadata only) or get_seo_data (which focuses on SEO aspects). It explicitly lists what content is included: raw HTML, word count, link count, and editor type.

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

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

No guidance is provided on when to use this tool versus alternatives like get_page, get_pages, or search_content. The description does not mention prerequisites, exclusions, or specific contexts where this tool is preferred over others in the sibling list.

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 of behavioral disclosure. It mentions what data is retrieved but does not describe behavioral traits such as read-only nature (implied by 'Get'), error handling, permissions required, rate limits, or response format. This is a significant gap for a tool with no annotation coverage.

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 lists key data fields, making it front-loaded and easy to scan. However, it could be slightly more structured by separating the purpose from the data list for better clarity, but it avoids unnecessary verbosity.

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 annotations and no output schema, the description is incomplete. It specifies what data is retrieved but lacks details on return format, error cases, or behavioral context. For a tool with 1 parameter and no structured output information, more guidance is needed to ensure proper agent usage.

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, with 'post_id' clearly documented. The description adds minimal value beyond the schema by implying the parameter is used to fetch SEO data for a specific post/page, but does not provide additional context like format examples or constraints. Baseline 3 is appropriate as the schema handles most of the parameter documentation.

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: 'Get Rank Math SEO data for a post/page' with specific data fields listed (SEO title, meta description, etc.). It uses a specific verb ('Get') and resource ('Rank Math SEO data'), but does not explicitly distinguish it from sibling tools like 'get_seo_status', which might be related but not clearly differentiated.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'get_seo_status' or 'update_seo_data', nor does it specify prerequisites, contexts, or exclusions for usage, leaving the agent to infer based on the name alone.

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 of behavioral disclosure. It mentions checking activation status and retrieving stats, implying a read-only operation, but does not specify permissions, rate limits, or potential side effects. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and constraints.

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: 'Check if Rank Math SEO is active and get overall SEO stats (posts with scores, posts with focus keywords).' It is front-loaded with the core purpose and uses parentheses to clarify the stats, avoiding any wasted words. Every part of the sentence earns its place by adding 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 tool's complexity (simple read operation with no parameters) and lack of annotations or output schema, the description is minimally adequate. It explains what the tool does but does not cover return values, error handling, or integration context. For a tool with no structured output, more detail on expected results would improve completeness, but it meets the basic threshold.

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 no parameters (0 params, 100% coverage), so the description does not need to add parameter semantics. It appropriately focuses on the tool's purpose without redundant parameter details. The baseline for zero parameters is 4, as the description compensates by explaining what the tool does without unnecessary complexity.

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: 'Check if Rank Math SEO is active and get overall SEO stats (posts with scores, posts with focus keywords).' It specifies the verb ('check' and 'get') and resource ('Rank Math SEO' and 'overall SEO stats'), making the action explicit. However, it does not differentiate from sibling tools like 'get_seo_data', which might offer similar or overlapping functionality, preventing a score of 5.

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, such as 'get_seo_data' or other SEO-related tools in the sibling list. It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage based on the purpose alone. This minimal guidance is insufficient for optimal tool selection.

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

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

No annotations are provided, so the description carries the full burden. It discloses that this is a read operation ('Get') and mentions the source of the data (presets or user customization), which adds useful context. However, it lacks details on permissions, rate limits, or error handling, leaving behavioral gaps for a tool with zero annotation coverage.

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 core purpose and followed by clarifying details. Every sentence earns its place by adding context without redundancy, making it efficient and well-structured for quick understanding.

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 0 parameters, no annotations, and no output schema, the description does a good job explaining what the tool retrieves and its relevance. However, it could be more complete by specifying the return format or any limitations, as there's no output schema to fall back on, leaving some contextual 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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by explaining what 'style settings' encompass (colors, design, spacing) and their origin, which provides semantic context beyond the empty schema. A baseline of 4 is appropriate as it compensates for the lack of parameters with meaningful information.

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 'Get' and the resource 'current style settings', specifying what they include (colors, design, spacing). It distinguishes this from siblings by explaining these are actual values used in generation, not presets or templates, which helps differentiate from tools like 'get_active_preset' or 'list_style_presets'.

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 by stating these settings are used when generating sections and can come from presets or user customization, which implies usage for retrieving applied styles. However, it does not explicitly state when to use this versus alternatives like 'get_active_preset' or 'detect_style_preset', missing explicit exclusions or comparisons.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions checking 'connection' and 'plugin status' but doesn't specify what constitutes a successful check, whether authentication is required, what happens on failure, or what format the status information returns. For a diagnostic tool with zero annotation coverage, this leaves significant behavioral gaps.

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 immediately states the tool's purpose without unnecessary words. It's appropriately sized for a zero-parameter diagnostic tool and front-loads the essential 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 zero-parameter diagnostic tool with no output schema, the description is minimally adequate but incomplete. It identifies what's being checked but doesn't explain what information will be returned or how to interpret results. Given the complexity is low (no parameters) but annotations are absent, it should provide more behavioral context about the check's scope and 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?

The tool has zero parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and it doesn't need to compensate for any schema gaps.

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 with specific verbs ('Check connection' and 'plugin status') and identifies the target resource ('WordPress'). It distinguishes from siblings by focusing on system health rather than content manipulation or SEO operations. However, it doesn't explicitly differentiate from potential diagnostic siblings that might not exist in this set.

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. It doesn't mention prerequisites (e.g., when connection issues are suspected), exclusions, or relationships to other tools like get_seo_status or detect_style_preset that might provide overlapping diagnostic information.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool performs an insertion (a write operation) but doesn't mention permissions required, whether the operation is idempotent, error handling (e.g., invalid parent_id), or what happens on success (e.g., returns new element ID). For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence that front-loads the core action ('Insert a widget element') followed by the key context ('at a specific position within an existing column or section'). There is no wasted verbiage, and every word contributes to understanding the tool's 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?

For a mutation tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It lacks behavioral details (e.g., side effects, error cases), usage prerequisites, and differentiation from siblings. While concise, it doesn't compensate for the missing structured data, leaving the agent under-informed about critical aspects of tool 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?

Schema description coverage is 100%, so the schema already documents all 5 parameters thoroughly. The description adds minimal value beyond the schema—it implies 'position' and 'widget_type' usage but doesn't provide additional context like format examples or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.

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 action ('Insert'), the resource ('a widget element'), and the location context ('at a specific position within an existing column or section'). It distinguishes from sibling tools like 'update_element' or 'delete_element' by specifying insertion rather than modification or removal. However, it doesn't explicitly differentiate from 'add_*' tools which might serve similar purposes in different contexts.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'update_element', 'add_*' tools (e.g., 'add_hero'), or 'create_page'. It mentions the context ('within an existing column or section') but doesn't specify prerequisites (e.g., needing an existing page structure) or exclusions (e.g., not for creating new pages).

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 of behavioral disclosure. It states the action is to 'List', which implies a read-only operation, but does not specify any behavioral traits such as permissions required, rate limits, pagination, or the format of the returned data. This is a significant gap for a tool with no annotation coverage.

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 front-loads the core purpose ('List available layout patterns') and provides specific examples. There is no wasted verbiage, making it highly concise and well-structured.

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

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

Given the lack of annotations and output schema, the description is incomplete. It does not explain what the tool returns (e.g., a list of pattern objects with details), any limitations, or error conditions. For a tool with no structured output information, the description should provide more context about the expected results.

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, with the single parameter 'category' fully documented in the schema (including its enum values). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 for high schema 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 verb 'List' and the resource 'available layout patterns', and enumerates the specific pattern types (Bento, Masonry, Zigzag, Grid). However, it does not explicitly differentiate this tool from its many siblings (e.g., list_style_presets, list_templates), which are also listing tools but for different resources.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, context for usage, or comparisons to sibling tools like list_style_presets or list_templates, leaving the agent to infer usage based on the tool name alone.

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 implies this is a read-only operation (listing presets), which is appropriate, but doesn't disclose behavioral traits like whether it requires authentication, how results are formatted (e.g., pagination), or if there are rate limits. The description adds some context about industry categorization but lacks operational details.

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

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

The description is two sentences with zero waste: the first states the purpose, and the second provides usage guidelines. It is front-loaded with the core function and efficiently adds necessary context without redundancy.

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 (0 parameters, no output schema, no annotations), the description is complete enough for a listing operation. It explains what is listed and when to use it. However, without an output schema, it doesn't describe return values (e.g., format of the style presets), which is a minor gap in contextual 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 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter semantics, but this is acceptable given the lack of parameters. A baseline of 4 is appropriate as it doesn't need to compensate for any gaps.

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 ('available style presets for different industries'), making the purpose specific and unambiguous. It distinguishes this tool from siblings by focusing on style presets rather than elements, pages, or other content types.

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 this to select a cohesive design style before creating pages.' It provides a clear context (pre-creation of pages) and distinguishes it from other tools like 'apply_style_preset' or 'get_active_preset' by focusing on listing options rather than applying or retrieving current ones.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. 'List available section templates' implies a read-only operation but doesn't specify whether this returns all templates or paginated results, what format the output takes, or any authentication/rate limiting considerations. For a tool with zero annotation coverage, this is insufficient behavioral context.

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

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

The description is a single, efficient sentence that states exactly what the tool does without any wasted words. It's front-loaded with the core functionality and appropriately sized for a simple listing operation.

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 operation with one optional parameter and no output schema, the description is minimally adequate. However, without annotations and with many sibling tools, it should ideally provide more context about what 'section templates' are and how this differs from other listing operations. The lack of output information is a notable gap.

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 100% description coverage with the single parameter 'category' clearly documented as an optional filter with enumerated values. The description doesn't add any parameter information beyond what's in the schema, which is acceptable given the high schema coverage. The baseline score of 3 reflects adequate but not enhanced parameter documentation.

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 ('available section templates'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'list_patterns' or 'list_style_presets' - all three are list operations for different resources without clear differentiation in the description.

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. With multiple 'list_' siblings and many content-related tools in the server, there's no indication of when this specific template listing is appropriate versus other listing or content retrieval 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Get the preview URL' which implies a read-only operation, but doesn't specify if this requires authentication, has rate limits, returns a temporary or permanent URL, or what happens on errors. For a tool with no annotation coverage, this leaves significant behavioral gaps.

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, clear sentence with zero wasted words. It's front-loaded with the core purpose ('Get the preview URL'), making it immediately understandable. Every word earns its place by specifying the action and target.

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 low complexity (1 parameter, no output schema, no annotations), the description is minimally complete. It states what the tool does but lacks behavioral details and usage context. Without annotations or output schema, the description should ideally cover more about the return value (e.g., URL format) and operational constraints, but it's adequate for basic 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 description coverage is 100%, with the single parameter 'page_id' documented as 'Page ID' in the schema. The description doesn't add any meaning beyond this—it doesn't explain what constitutes a valid page ID, where to find it, or provide examples. With high schema coverage, the baseline is 3, and the description doesn't compensate with additional 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 verb ('Get') and resource ('preview URL for a page'), making the purpose understandable. It distinguishes from siblings like 'get_page' (which likely retrieves page data) by focusing specifically on the preview URL. However, it doesn't explicitly mention what distinguishes it from tools like 'get_page_structure' or 'get_post_content', so it's not fully specific about sibling differentiation.

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. With siblings like 'get_page', 'get_pages', and 'get_page_structure', there's no indication of when a preview URL is needed instead of other page-related data. No context, 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions what the tool returns but doesn't cover important aspects like pagination behavior (implied by 'per_page' but not explained), error conditions, authentication requirements, rate limits, or whether this is a read-only operation. The description is insufficient for a tool with mutation siblings like 'update_post'.

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 perfectly concise - two sentences that efficiently convey the action, target, and return format. Every word earns its place with no redundancy or unnecessary elaboration. It's front-loaded with the core 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?

For a search tool with 3 parameters and no output schema, the description adequately covers the basic purpose and return format. However, given the lack of annotations and the presence of many mutation siblings, it should provide more context about safety, limitations, and how results are structured. The description doesn't explain what 'excerpts' contain or how pagination works despite the 'per_page' parameter.

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 description coverage is 100%, so all parameters are documented in the schema. The description adds minimal value beyond the schema - it mentions 'by keyword' which relates to the 'query' parameter, but doesn't provide additional context about search syntax, ranking, or how different post types affect results. Baseline 3 is appropriate when the schema does the heavy lifting.

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'), resource ('WordPress posts and pages'), and scope ('by keyword'). It distinguishes this tool from siblings like 'get_pages' or 'get_post_content' by specifying it's a search operation rather than a direct retrieval.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'find_and_replace' or 'get_pages'. It doesn't mention prerequisites, limitations, or scenarios where this search is preferred over other content retrieval methods available in the sibling list.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Update' which implies mutation, but doesn't specify permissions required, whether changes are reversible, error handling, or response format. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence that front-loads the core action and resource without unnecessary words. It's appropriately sized for the tool's complexity, with zero waste or redundancy.

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 (mutation with 3 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It doesn't cover behavioral aspects like side effects, error cases, or return values, leaving the agent with insufficient context for reliable use.

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 input schema already documents all parameters (page_id, element_id, settings) with descriptions. The description adds no additional meaning beyond what the schema provides, such as explaining the structure of 'settings' or usage examples. Baseline 3 is appropriate when the schema does the heavy lifting.

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 action ('Update') and resource ('a specific element on the page by its ID'), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'update_elementor_widget' or 'update_post', which also perform updates on related resources, so it doesn't fully differentiate from alternatives.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'update_elementor_widget' or 'update_post', nor does it mention prerequisites such as needing an existing element ID. It lacks explicit when/when-not instructions or context for selection among similar update 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?

No annotations are provided, so the description carries the full burden. It states the tool updates a widget, implying a mutation, but does not disclose behavioral traits such as permissions needed, whether changes are reversible, or error handling. This is inadequate for a mutation tool with zero annotation coverage.

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 directly states the tool's purpose and alias. It is front-loaded with no unnecessary words, making it highly concise and well-structured.

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

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

Given this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects like side effects, return values, or error conditions, which are critical for safe and effective use. The alias note adds some context but does not compensate for these 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%, so the schema documents all parameters (page_id, element_id, settings). The description does not add any meaning beyond what the schema provides, such as explaining the 'settings' object or widget context. Baseline 3 is appropriate as the schema handles parameter documentation.

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 action ('Update a widget on the page') and resource ('widget'), making the purpose understandable. However, it does not distinguish this tool from its sibling 'update_element' beyond noting it's an alias, which slightly reduces clarity about unique functionality.

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 mentions this is an alias for 'update_element', implying an alternative, but does not provide explicit guidance on when to use this tool versus 'update_element' or other update-related tools like 'update_post'. No context or exclusions are specified, leaving usage ambiguous.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool performs a replacement operation, implying mutation, but doesn't address critical aspects like permissions needed, whether changes are reversible, error handling, or what happens if the old URL isn't found. This leaves significant gaps for a mutation tool.

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

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

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action, making it easy to understand quickly.

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

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

For a mutation tool with no annotations and no output schema, the description is inadequate. It lacks details on behavioral traits, error conditions, return values, and differentiation from siblings. Given the complexity of modifying content, more context is needed for safe and effective use.

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 fully documents the three parameters. The description adds minimal value by implying the tool finds and replaces URLs, but doesn't provide additional context like format requirements or edge cases beyond what's in the 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 action ('Replace') and target ('a specific link URL in a post/page'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'find_and_replace' or 'update_post', which could have overlapping functionality.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'find_and_replace' or 'update_post', nor does it mention prerequisites or exclusions. It only describes what the tool does, not when it's 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?

No annotations are provided, so the description carries the full burden. It discloses that this is a mutation tool ('Update'), but doesn't mention behavioral traits like permission requirements, whether changes are reversible, rate limits, or what happens to unspecified fields. The partial update guidance is helpful but insufficient for a mutation tool without 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, front-loaded with the core purpose and followed by a key usage constraint. Every word earns its place with zero waste, making it highly efficient and easy to parse.

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 annotations and no output schema, the description is adequate for a basic update tool but lacks completeness. It covers the purpose and partial update behavior but misses critical context like error handling, response format, or side effects. For a mutation tool with 6 parameters, more behavioral disclosure would be beneficial.

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 thoroughly. The description adds minimal value by listing the updatable fields, which mirrors the schema properties. It provides the partial update constraint ('Only provide the fields you want to change'), which is useful but doesn't significantly enhance parameter understanding 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 action ('Update') and resource ('post/page'), and lists specific fields that can be modified (title, content, excerpt, status, slug). It distinguishes from siblings like 'create_page' by focusing on updates rather than creation. However, it doesn't explicitly differentiate from other update tools like 'update_element' or 'update_seo_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 provides implied usage guidance by stating 'Only provide the fields you want to change,' which suggests a partial update pattern. However, it doesn't explicitly state when to use this tool versus alternatives like 'update_element' or 'update_seo_data,' nor does it mention prerequisites such as needing an existing post ID.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Update' implying a mutation, but doesn't disclose critical behaviors: whether it overwrites all fields or partial updates, if it requires specific permissions, what happens on success/failure (e.g., returns updated data or just confirmation), or any rate limits. The description lists fields but lacks operational context.

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

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

The description is a single, efficient sentence that front-loads the action ('Update Rank Math SEO data') followed by a comma-separated list of fields. It avoids redundancy and wastes no words, though it could be slightly more structured (e.g., grouping related fields). Every part earns its place by specifying the scope.

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 complexity (9 parameters, mutation operation) and lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., success status, updated SEO data), error conditions, or behavioral nuances like partial updates. For a mutation tool with rich parameters, more context is needed to guide effective use.

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 9 parameters thoroughly (e.g., post_id as 'Post or page ID', seo_description with character recommendations). The description adds minimal value by listing field names like 'SEO title, meta description' but doesn't provide additional syntax, constraints, or examples beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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 'Update' and resource 'Rank Math SEO data', listing specific fields like SEO title, meta description, focus keyword, etc. It distinguishes from sibling tools like 'get_seo_data' by specifying an update operation, but doesn't explicitly differentiate from other update tools like 'update_element' or 'update_post' beyond the SEO focus.

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

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

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid post_id), when not to use it (e.g., for non-SEO updates), or refer to sibling tools like 'get_seo_data' for checking existing data before updating. The description assumes context without explicit instructions.

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