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 this is a read operation ('get'), but doesn't disclose any behavioral traits like rate limits, authentication requirements, response format, pagination, or error conditions. For a news retrieval tool with zero annotation coverage, 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 a single, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple retrieval 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?

Given no annotations, no output schema, and multiple sibling tools, the description is incomplete. It doesn't explain what the tool returns (news format, structure, or limitations), how it differs from other news category tools, or any operational constraints. For a tool with contextual complexity, this leaves significant 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 description adds no parameter information beyond what the schema provides. With 100% schema description coverage (the 'lr' parameter is fully documented in the schema), the baseline is 3. The description doesn't compensate with additional context about parameter usage or effects.

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 business news from Google News' with a specific verb ('get') and resource ('business news'). It distinguishes from siblings by specifying the business news domain, though it doesn't explicitly contrast with other news category tools like 'entertainment' or 'technology'.

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 sibling tools for different news categories (entertainment, health, science, etc.), there's no indication of when business news is appropriate versus other categories or the 'search' tool for broader queries.

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 'gets' news, implying a read-only operation, but doesn't specify whether it requires authentication, has rate limits, returns paginated results, or details the response format. 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 fluff. It's appropriately sized and front-loaded, with every word earning its place. There's no wasted verbiage, 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 low complexity (1 parameter, no nested objects) and high schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it lacks details on behavioral traits (e.g., response format, error handling) and doesn't guide usage relative to siblings. It meets the bare minimum but has clear gaps in 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?

The input schema has 100% description coverage, with the 'lr' parameter fully documented as 'language region, ex: en-US.' The description adds no additional parameter information beyond what the schema provides. According to the rules, when schema coverage is high (>80%), the baseline score is 3, as the schema does the heavy lifting and the description doesn't compensate with extra semantics.

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 entertainment news from Google News.' It specifies both the verb ('get') and the resource ('entertainment news'), and distinguishes it from siblings like 'business' or 'sport' by focusing on entertainment content. However, it doesn't explicitly differentiate from 'latest' or 'search,' which might also retrieve news, so it's not a perfect 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. It doesn't mention when to choose 'entertainment' over siblings like 'latest' (which might include entertainment news) or 'search' (which could filter for entertainment topics). There's no context on exclusions or prerequisites, leaving the agent to infer usage 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 only states what the tool does ('get health news') without adding context such as rate limits, authentication needs, or what the return format looks like. For a tool with no annotations, this is insufficient to inform the agent about operational traits.

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 and wastes no space, 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 the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., news articles, summaries, or error handling), and with no behavioral context, it fails to provide enough information for an agent to use it effectively in complex scenarios.

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 parameter 'lr' documented as 'language region, ex: en-US.' The description adds no additional meaning beyond this, as it doesn't mention parameters at all. According to the rules, with high schema coverage (>80%), the baseline is 3, which applies here.

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 health news from Google News.' It specifies the verb ('get') and resource ('health news'), making the function unambiguous. However, it doesn't differentiate from sibling tools like 'business' or 'science,' which likely fetch news in other categories, so it's not a perfect 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. It doesn't mention sibling tools like 'search' or 'latest,' which might overlap in functionality, nor does it specify any context or exclusions for usage. This lack of comparative information limits its helpfulness.

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 tool 'gets' news, implying a read-only operation, but doesn't clarify aspects like rate limits, authentication needs, or response format (e.g., pagination, data structure). For a tool with no annotations, 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, clear sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and efficient, making it easy for an agent to parse quickly. Every part of the sentence earns its place by conveying 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?

Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on usage context, behavioral traits, or how it differs from siblings. Without an output schema, it doesn't explain return values, which is a gap, but the simplicity of the tool makes this less critical.

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 'lr' parameter fully documented as 'language region, ex: en-US.' The description doesn't add any parameter details beyond this, such as explaining why 'lr' is required or how it affects the news retrieval. Given the high schema coverage, a baseline score of 3 is appropriate, as the description 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: 'get the latest news from Google News.' It specifies the verb ('get') and resource ('latest news'), making the function unambiguous. However, it doesn't differentiate from sibling tools like 'business' or 'world,' which likely also retrieve news but with different filters or categories.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'business' or 'world,' which might be for specific news categories, nor does it specify if this tool is for general or unfiltered news. Without such context, the agent lacks direction on 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?

With no annotations, the description carries the full burden of behavioral disclosure. It states it 'gets' news (implying a read-only operation) but doesn't mention rate limits, authentication needs, response format, pagination, or potential errors. This leaves significant gaps for an AI agent to understand how to interact with it effectively.

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. It's appropriately sized and front-loaded with the core purpose, though it could be slightly more structured by including key usage details without adding unnecessary length.

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 doesn't explain what the return value looks like (e.g., list of articles, error handling), behavioral traits, or how it integrates with siblings. For a tool with no structured metadata, more context is needed to guide proper 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 one parameter 'lr' documented as 'language region, ex: en-US'. The description adds no additional parameter information beyond what the schema provides, so it meets 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 states the tool's purpose ('get science news from Google News') with a clear verb and resource, but it doesn't distinguish it from sibling tools like 'business', 'health', or 'technology' which likely fetch different news categories. The purpose is understandable but generic within the context of similar 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 like 'search' or other category-specific tools (e.g., 'technology'). The description implies it's for science news, but it doesn't specify scenarios, exclusions, or how it differs from siblings beyond the category name.

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 the mandatory 'keyword' parameter but doesn't describe what the search returns (e.g., article list, summaries), any limitations (e.g., result count, pagination), rate limits, authentication needs, or error conditions. For a search 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 appropriately concise with two sentences that directly address the tool's function and key parameter. It's front-loaded with the main purpose. However, the second sentence slightly repeats schema information without adding significant new value, keeping it from a perfect score.

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 search operation with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., news articles, metadata), how results are structured, any sorting/filtering options beyond parameters, or error handling. For a tool that likely returns varied data, more context is needed for effective agent 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 both parameters ('keyword' and 'lr') with descriptions. The description adds minimal value by restating that 'keyword' is mandatory but doesn't provide additional context like search syntax examples, keyword formatting, or how 'lr' affects results 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: 'search for news from Google News based on keywords.' It specifies the verb ('search'), resource ('news from Google News'), and mechanism ('based on keywords'). However, it doesn't explicitly differentiate from sibling tools like 'latest' or 'world' which might also retrieve news content.

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 sibling tools like 'business', 'entertainment', and 'world' that appear to be news category-specific, there's no indication whether 'search' is for general keyword searches while others are for predefined categories, or how they relate. No explicit when/when-not instructions or alternatives are mentioned.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'gets sport news' but doesn't reveal any behavioral traits such as rate limits, authentication needs, data freshness, pagination, or error handling. For a read operation with no annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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 sport news'), making it easy to parse. Every element earns its place by directly stating what the tool does.

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 doesn't address key contextual aspects like what format the news is returned in (e.g., headlines, full articles, links), how results are sorted or limited, or whether there are any usage constraints. For a tool that fetches dynamic data like news, 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?

The input schema has 100% description coverage, with the single parameter 'lr' documented as 'language region, ex: en-US'. The description adds no additional meaning about parameters beyond what the schema provides, such as explaining why this parameter is required or how it affects the news results. With high 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 as 'get sport news from Google News' with a specific verb ('get') and resource ('sport news'), making it immediately understandable. However, it doesn't explicitly differentiate itself from sibling tools like 'business', 'entertainment', or 'world' which likely serve similar news-fetching functions for different categories.

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

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'search', 'latest', and category-specific tools (e.g., 'business', 'health'), there's no indication whether this tool is for general sports news, breaking sports news, or how it differs from a broader search function. No 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 the tool returns a 'JSON response containing a list of relevant autocomplete suggestions,' which is helpful, but lacks details on rate limits, authentication needs, error handling, or how suggestions are generated (e.g., based on popularity or 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 appropriately sized and front-loaded, with the first sentence clearly stating the purpose. However, the second sentence is slightly redundant ('You can send a request...') and could be more streamlined, though overall 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 the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic function and response format but lacks details on usage context, behavioral traits, or how to interpret the output, which would be helpful for 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?

Schema description coverage is 100%, so the schema already documents both parameters ('keyword' and 'lr'). The description adds some context by explaining that 'keyword' represents 'partial text entered by the user,' but doesn't provide additional meaning beyond what the schema offers, such as 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 tool's purpose: 'get autocomplete suggestions or query predictions as a user types a search query.' It specifies the verb ('get') and resource ('autocomplete suggestions'), but doesn't explicitly differentiate it from sibling tools like 'search' or 'latest', which likely serve 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 alternatives. It mentions the tool's function but doesn't specify scenarios where it's preferred over sibling tools like 'search' or indicate any 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 states the tool retrieves a list, implying a read-only operation, but doesn't specify details like response format, pagination, rate limits, or authentication needs. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.

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 key information ('retrieve a list of supported languages and regions') with zero waste. It's appropriately sized for a simple tool with no parameters, 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 the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate for conveying the basic purpose. However, it lacks details on output format or behavioral traits, which could be helpful for an agent to understand what to expect from the retrieval, making it only minimally viable.

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 the schema description coverage is 100%, meaning there are no parameters to document. The description doesn't need to add parameter semantics, so it meets the baseline expectation for such cases, though it doesn't go beyond that since there's nothing to explain.

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 ('retrieve') and resource ('list of supported languages and regions'), making it immediately understandable. However, it doesn't differentiate this from sibling tools (like 'search' or 'suggest'), which could have overlapping functionality, so it doesn't reach the highest 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, such as the sibling tools listed (e.g., 'search' or 'suggest'). It lacks explicit context, exclusions, or comparisons, leaving the agent to infer usage based on the name alone, which 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 full burden. It only states what the tool does (gets news) without disclosing behavioral traits like rate limits, authentication requirements, response format, pagination, or error handling. For a read operation with no annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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 with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential information 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 lack of annotations and output schema, the description is incomplete. It doesn't explain what format the news is returned in, how many results to expect, whether there are limitations, or how it differs from sibling tools. For a news retrieval tool with no structured behavioral information, the description should provide more context about the operation.

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 fully documents the single parameter (lr). The description adds no parameter-specific information beyond what's in the schema. With high schema coverage, the baseline score of 3 is appropriate since the description doesn't need to compensate for 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 as 'get technology news from Google News', specifying both the action (get) and resource (technology news). It distinguishes from siblings by focusing on technology news specifically, though it doesn't explicitly contrast with other news categories like business or science.

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. With 10 sibling tools including other news categories (business, health, science, etc.) and general search tools, the description offers no context about when technology news is appropriate versus using 'search' or other category-specific endpoints.

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 only mentions that a parameter is optional but doesn't describe what the tool returns, any rate limits, authentication needs, or error conditions. The incomplete sentence further reduces its usefulness.

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 technically short but structurally flawed due to the incomplete sentence. The first part is somewhat useful, but the second part is nonsensical and wastes space without 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?

For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'world news' means in context of sibling tools, what format results come in, or any operational constraints. The incomplete sentence makes it particularly inadequate.

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 'lr' parameter with an example value. The description attempts to mention an optional parameter but fails to complete the thought, adding no meaningful semantic information beyond what the schema provides.

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 states 'get world news from Google News' which provides a basic verb+resource combination, but it's incomplete and ends abruptly with 'The optional parameter that can be used is "' without finishing the sentence. This makes it functionally tautological with the tool name 'world' while being grammatically broken.

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 about when to use this tool versus the 10 sibling tools listed (business, entertainment, health, etc.). The description doesn't mention any context, prerequisites, or alternatives, leaving the agent with no usage framework.

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