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

Annotations already provide readOnlyHint=true, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds valuable context beyond annotations: it specifies that content is 'cleaned' (behavioral trait), mentions case-insensitivity and underscore/space handling, and describes the return structure. No contradiction with annotations exists.

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 front-loaded with the core purpose, followed by well-structured sections for Args and Returns. Every sentence adds value: the first states the action, the Args section details parameters clearly, and the Returns section explains output. No wasted words.

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

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

Given the tool's moderate complexity, rich annotations, and the presence of an output schema (implied by the Returns section), the description is complete. It covers purpose, parameters, return values, and behavioral nuances like cleaning and formatting, leaving no significant gaps for the agent.

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

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

With 0% schema description coverage, the description fully compensates by explaining both parameters: 'name' is clarified as a page title with examples and formatting notes, and 'max_chars' is defined as a soft cap with a default value. This adds essential meaning beyond the bare 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 specific action ('Fetch the cleaned content') and resource ('an aesthetic's wiki page'), distinguishing it from sibling tools like get_aesthetic_images (which likely fetches images only) or search_aesthetic (which searches rather than fetches a specific page). The verb+resource combination is precise and unambiguous.

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 what it fetches (cleaned wiki content), but doesn't explicitly state when to use this tool versus alternatives like search_aesthetic or list_related. No exclusions or prerequisites are mentioned, leaving the agent to infer context from the tool name and description 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?

The description adds valuable behavioral context beyond what annotations provide: it specifies that the tool 'Excludes tiny icons and SVG placeholders' (filtering behavior not indicated by annotations) and mentions the return format. Annotations cover read-only, idempotent, and open-world characteristics, but the description supplements with practical implementation 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 perfectly structured and front-loaded: the first sentence states the core purpose, followed by clearly labeled sections for Args and Returns. Every sentence earns its place by providing necessary information without redundancy or fluff.

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

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

Given the tool's moderate complexity, rich annotations (readOnlyHint, idempotentHint, openWorldHint), and the presence of an output schema, the description is complete enough. It explains what the tool does, provides parameter semantics, describes key behavioral traits (filtering exclusions), and references the return structure—all without needing to duplicate schema information.

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

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

With 0% schema description coverage, the description fully compensates by providing clear semantics for both parameters: 'name' is explained as 'Page title (e.g. "Cottagecore", "Dark Academia")' with examples, and 'limit' as 'Max number of images (1-50). Default 12.' This adds essential meaning beyond the bare 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 specific action ('Get image URLs') and resource ('from an aesthetic's wiki page'), with the phrase 'perfect for moodboards' providing practical context. It distinguishes this tool from siblings like 'get_aesthetic' (likely returns general info) and 'search_aesthetic' (likely searches for aesthetics) by focusing specifically on image extraction.

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 this tool ('perfect for moodboards'), but does not explicitly state when not to use it or name alternatives among sibling tools. The agent can infer usage from the purpose, but lacks explicit guidance on tool selection scenarios.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds useful behavioral context by specifying the return format (dict with source and related lists) and the default limit, which enhances understanding beyond the annotations.

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

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

The description is appropriately sized and front-loaded, with a clear purpose statement followed by well-structured sections for Args and Returns. Every sentence earns its place 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 low complexity, rich annotations, and the presence of an output schema (which covers return values), the description is complete enough. It effectively explains purpose, parameters, and usage context without needing to detail outputs.

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

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

With 0% schema description coverage, the description fully compensates by explaining both parameters: 'name' as the source page title with an example, and 'limit' with its range and default value. This adds essential meaning beyond the bare schema.

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

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

The description clearly states the tool's purpose with a specific verb ('List') and resource ('aesthetics linked from a given page'), and distinguishes it from siblings by focusing on neighbor discovery rather than direct retrieval, search, or random selection.

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 usage ('useful for discovering neighbors'), but does not explicitly state when not to use it or name specific alternatives among the sibling tools, such as when to prefer search_aesthetic over this tool.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=false, and openWorldHint=true, covering safety and data behavior. The description adds value by specifying the source ('wiki') and the random nature of retrieval, which isn't captured in annotations. It doesn't contradict annotations, as 'Get' aligns with read-only, and it provides useful context beyond structured data.

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 front-loaded with the core purpose, followed by structured sections for Args and Returns. Every sentence earns its place: the opening line sets context, and the bullet points efficiently document parameters and output without redundancy. It's appropriately sized for the tool's complexity.

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 nested objects), the description is complete. It explains the purpose, parameter semantics, and return format. With annotations covering behavioral traits and an output schema implied by the Returns section, no additional details are needed 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?

Schema description coverage is 0%, so the description carries the burden. It clearly explains the 'count' parameter: 'Number of random pages (1-10). Default 1.', adding meaning beyond the schema's basic type and title. This compensates well for the low coverage, though it doesn't detail other potential parameters if they existed.

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 one or more random aesthetics from the wiki — great for inspiration.' This specifies the verb ('Get'), resource ('aesthetics'), and source ('wiki'), with a helpful usage context ('inspiration'). However, it doesn't explicitly differentiate from sibling tools like 'get_aesthetic' or 'search_aesthetic', which likely retrieve specific rather than random aesthetics.

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

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

The description implies usage for inspiration and randomness, but doesn't explicitly state when to use this tool versus alternatives like 'get_aesthetic' or 'search_aesthetic'. It provides some context ('great for inspiration') but lacks clear guidance on exclusions or direct comparisons to sibling tools.

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

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

Annotations already declare readOnlyHint=true (safe read), idempotentHint=true (repeatable), and openWorldHint=true (dynamic data). The description adds value by specifying the search scope ('pages matching a query') and return format details (dict with results list structure), which are not covered by annotations. However, it does not disclose additional behavioral traits like rate limits, authentication needs, or pagination, so a 3 is appropriate.

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 front-loaded with the core purpose in the first sentence, followed by structured sections for Args and Returns. Every sentence adds value: the purpose statement, parameter explanations with examples, and return format details. There is no wasted text, and the structure enhances readability.

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 (2 parameters, simple search), rich annotations (readOnly, idempotent, openWorld), and the presence of an output schema (implied by Returns section), the description is complete enough. It covers purpose, parameters, and return values adequately without needing to explain annotations or output schema details, making it sufficient for the context.

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

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

Schema description coverage is 0%, so the description must compensate. It effectively adds meaning: it explains 'query' as free-text search with examples ('cottagecore', 'dark academia', 'y2k') and 'limit' as max results with range (1-50) and default (10), which are not in the schema. This covers both parameters well, but lacks details on query syntax or error handling, preventing a perfect 5.

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 action ('Search'), target resource ('the Aesthetics Wiki for pages'), and scope ('matching a query'), distinguishing it from siblings like get_aesthetic (likely retrieves a specific page), get_aesthetic_images (likely fetches images), list_related (likely lists related pages), and random_aesthetic (likely returns a random page). The verb+resource+scope combination is precise and 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 implies usage context (searching for pages based on a query) but does not explicitly state when to use this tool versus alternatives like get_aesthetic (for specific pages) or random_aesthetic (for random selection). It provides clear parameter guidance (e.g., query examples, limit range) but lacks explicit when/when-not statements or named alternatives, keeping it at a 4.

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