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 the crawling mechanism (tree-like expansion) and some controls, but lacks critical details like rate limits, authentication needs, error handling, or what the output looks like (e.g., format, structure). For a complex tool with 11 parameters, this is insufficient.

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 and front-loaded, stating the core purpose in the first sentence. Each subsequent sentence adds relevant context about crawling behavior and controls without unnecessary fluff. However, it could be slightly more structured by explicitly mentioning key parameters.

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 (11 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the output format, potential side effects (e.g., network usage), or error scenarios. For a web crawler with many controls, more behavioral and output 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 parameters thoroughly. The description adds minimal value by mentioning depth, breadth, and focusing on site sections, which loosely relates to max_depth, max_breadth, and categories/select_paths, but doesn't provide additional syntax or usage context beyond the schema.

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

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

The description clearly states the tool's purpose as initiating a structured web crawl from a base URL, following internal links like a tree, with control over depth and breadth. It specifies the verb 'crawl' and resource 'web pages' but doesn't explicitly distinguish it from sibling tools like tavily-extract or tavily-map, which likely have different functions.

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 its siblings (tavily-extract, tavily-map, tavily-search). It mentions controlling depth and width and focusing on site sections, but this is more about parameter usage rather than contextual application or alternatives.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'powerful web content extraction' and 'retrieves and processes raw content' but lacks critical details like rate limits, authentication requirements, error handling, or what 'processes' entails beyond what the parameters specify.

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 and front-loaded with the core purpose in the first clause. The second clause adds use cases without redundancy. However, the phrase 'ideal for data collection, content analysis, and research tasks' is somewhat generic and could be more specific.

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 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks behavioral context (e.g., performance, limitations), doesn't explain the output format or structure, and provides no sibling differentiation, leaving gaps for an AI agent 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 schema fully documents all parameters. The description adds no additional parameter semantics beyond what's in the schema, such as explaining interactions between parameters or edge cases. Baseline 3 is appropriate when 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 tool's purpose: 'retrieves and processes raw content from specified URLs' with specific verbs and resources. It distinguishes from siblings by focusing on extraction rather than crawling, mapping, or searching, though it doesn't explicitly name the 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 its siblings (tavily-crawl, tavily-map, tavily-search). It mentions general use cases like 'data collection, content analysis, and research tasks' but offers no explicit when/when-not instructions or alternative selection criteria.

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. While it mentions the tool 'creates a structured map' and is 'perfect for site audits,' it lacks critical behavioral details: what format the output takes (structured how?), whether it's a read-only operation (implied but not stated), performance characteristics, error handling, or any limitations beyond what parameters suggest. For a complex 9-parameter web crawling tool with no annotations, this is inadequate.

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 concise with two sentences that efficiently communicate core functionality and use cases. The first sentence defines the tool's purpose, and the second provides application contexts. There's no wasted language, though it could be slightly more front-loaded with explicit differentiation from siblings.

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 complex web mapping tool with 9 parameters, no annotations, and no output schema, the description is incomplete. It doesn't address what the output looks like (critical since there's no output schema), doesn't explain behavioral constraints or performance implications, and offers minimal guidance on parameter usage beyond what the schema provides. The agent would struggle to use this tool effectively without trial and error.

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. The description adds no specific parameter semantics beyond implying general mapping behavior. It doesn't explain how parameters like 'categories' or 'instructions' integrate with the mapping process, nor does it provide context for parameter interactions. 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 tool's purpose as creating structured maps of website URLs for analysis of site structure, content organization, and navigation paths. It specifies the verb 'creates' and resource 'structured map of website URLs' with clear use cases (site audits, content discovery, website architecture). However, it doesn't explicitly differentiate from sibling tools like tavily-crawl or tavily-extract, which likely 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 its siblings (tavily-crawl, tavily-extract, tavily-search). It mentions general use cases like 'site audits, content discovery, and understanding website architecture' but offers no explicit when/when-not criteria or alternative selection guidance. The agent must infer usage 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?

With no annotations provided, the description carries full burden of behavioral disclosure. While it mentions 'real-time results' and 'customizable parameters,' it doesn't address important behavioral aspects like rate limits, authentication requirements, error conditions, or what format the results come in. For a complex 14-parameter search tool, 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 efficiently structured in two sentences that convey core functionality and ideal use cases. It's appropriately sized and front-loaded with the main purpose, though could be slightly more concise by combining related concepts.

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 complex search tool with 14 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the output looks like, doesn't mention rate limits or authentication, and provides minimal behavioral context. The description should do more to compensate for the lack of structured metadata.

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 14 parameters thoroughly. The description mentions 'customizable parameters for result count, content type, and domain filtering' which aligns with some parameters but doesn't add significant meaning 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 tool's purpose as 'web search' with specific details: it uses Tavily's AI search engine, provides real-time results, and returns relevant web content. It distinguishes from siblings by focusing on search rather than crawling, extraction, or mapping.

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 ('gathering current information, news, and detailed web content analysis'), but doesn't explicitly mention when NOT to use it or directly compare to sibling tools like tavily-crawl or tavily-extract. The guidance is helpful but lacks explicit alternatives.

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