global-news-intelligence-mcp

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

With no annotations, the description must disclose behavioral traits. It only restates the tool's purpose without detailing return format, pagination, sorting, or any limitations. The verb 'Get' implies a read but adds no valuable context beyond the name.

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 no redundant words. It is front-loaded and directly states the tool's core 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?

For a simple, parameterless news retrieval tool with an output schema, the description covers the essential purpose. It lacks sibling differentiation, but that is more a usage guideline issue. Overall, it is minimally sufficient but could benefit from a note on scope.

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, so the schema is trivially covered. The description adds no param info, but baseline is 4 for 0-param tools. No additional meaning is needed.

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 function: retrieving the latest artificial intelligence news. The verb 'Get' and specific resource 'artificial intelligence news' distinguish it from sibling tools like get_technology_news or get_news.

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. The description simply states the action without mentioning contexts, exclusions, or alternative 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?

With no annotations available, the description carries the full burden of behavioral disclosure. It reveals only that news comes from Chinese sources, but does not clarify aspects like language, geographic scope ('domestic' could be ambiguous), pagination, or response format. This is minimal useful behavioral information.

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, concise sentence with no redundant words. It earns its place by stating the core function clearly. There is no fluff or filler.

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 absence of annotations and parameters, the description is too minimal to provide complete context. It does not explain what 'domestic' means, whether results are in Chinese, what typical use cases are, or how this differs from other news categories beyond the name. The presence of an output schema helps, but the description alone leaves significant gaps for an 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 tool has zero parameters, so the description does not need to explain any arguments. Per the rubric, a baseline of 4 is appropriate when there are no parameters to describe. The schema already covers everything implicitly.

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 function: retrieving domestic China news from Chinese sources. The verb 'Get' and specific resource 'domestic China news from Chinese sources' make it distinct from sibling tools like get_international_news and get_world_news.

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. There is no mention of exclusions, prerequisites, or recommendations. The description simply states what the tool does without helping the agent decide between this and similar news-fetching 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 burden of behavioral disclosure. It only states the purpose without mentioning any limitations, return format, or side effects. For a read-only getter, this is minimal disclosure, offering no additional behavioral context beyond the name.

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, concise sentence that immediately conveys the tool's purpose and key topics. It is front-loaded with the verb and resource, with zero 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?

For a simple tool with no parameters and an existing output schema, the description sufficiently covers the main scope. It could be slightly more complete by mentioning what type of news items (e.g., headlines, summaries) are returned, but the presence of an output schema mitigates the need to explain return values.

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, and the baseline for 0 parameters is 4. The description adds some context by listing energy sub-topics, which helps the agent understand the scope of the news returned.

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 uses an explicit verb 'Get' with a specific resource 'energy sector news' and lists sub-topics (oil, gas, renewables, policy). This clearly distinguishes it from sibling tools like get_technology_news or get_ai_news.

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 energy-related news through its speciality, but it does not explicitly state when to use this tool versus alternatives like get_news or other category-specific tools. No exclusions or explicit alternative guidance is provided.

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 'Get entertainment industry news' without mentioning return format, output structure, pagination, rate limits, or any side effects. The verb 'get' implies a read operation, but that is not explicitly disclosed.

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, short sentence with no redundant words. It is perfectly concise 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?

An output schema exists to handle return values, and this is a zero-parameter tool, so the minimal description might be sufficient. However, it lacks usage context and behavioral transparency, leaving the agent with questions about how this tool compares to siblings and what to expect. It is adequate but not fully complete.

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

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

There are zero parameters, making schema coverage trivially 100%. Per the baseline for 0-parameter tools, a score of 4 is appropriate. The description adds nothing about parameters, but none are needed.

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 uses a specific verb 'get' and identifies the resource 'entertainment industry news', clearly distinguishing it from sibling news tools like get_technology_news or get_politics_news. It is instantly obvious what this tool does.

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 when to prefer it over generic get_news or other category-specific news tools, nor does it state any exclusions or prerequisites.

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 primary behavior (retrieving finance news) but does not disclose additional traits such as sorting, recency, rate limits, or whether results are filtered. For a simple read-only tool, the description is adequate but not rich.

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 concise sentence with a clear structure: verb, resource, and topic examples. No unnecessary 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?

For a zero-parameter news-fetching tool with an output schema, the description is complete: it clearly identifies the news category (finance/business) and the scope. The sibling list provides context for differentiation. No missing critical 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?

The tool has zero parameters and the schema is empty with 100% coverage. With no parameters to document, the baseline is 4; the description adds no parameter semantics because there are none.

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 uses a specific verb ('Get') with a clear resource ('finance and business news') and scope ('stocks, economy, markets'), which distinguishes it from sibling tools like get_technology_news or get_politics_news. It clearly identifies what this tool does.

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 when to use the tool (when finance/business news is needed) but does not explicitly contrast with alternatives or state when not to use it. No direct mention of sibling tools or exclusions, so usage guidance is implied rather than explicit.

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 restates the topic and gives no details about how the tool behaves (e.g., read-only nature, return format, filtering, or limitations). This is particularly sparse for a zero-parameter 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 sentence, concise, and front-loaded with the main action. Every part adds value, and there is no wasted text.

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?

The tool is simple with zero parameters and an output schema present, so the description does not need to explain return values. However, given the large set of sibling news tools, some additional usage context would improve completeness. Still, the description is adequate for a basic retrieval 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 tool has zero parameters, so the schema fully covers parameter semantics. The description adds no parameter information, but none is needed; the baseline of 4 applies.

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 uses a specific verb ('Get') and clearly identifies the resource ('hardware news') with a list of covered topics (CPUs, GPUs, chips, semiconductors, devices). This makes the tool's purpose obvious and distinguishes it from siblings like get_technology_news.

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 the tool is used for hardware news by listing relevant topics, but it does not explicitly state when to use this tool over alternatives or any exclusions. With many sibling news tools, more explicit guidance would be helpful.

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 that it gets news from global sources, but does not explain whether it returns a list, whether it requires authentication, or what constitutes 'major' vs 'minor'. This is minimal transparency beyond the name itself.

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 concise sentence that is front-loaded with the verb and resource. It is not verbose and contains no filler.

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 zero parameters and presence of an output schema, the description need not explain return formats. However, it is incomplete because it fails to differentiate itself from the closely named sibling get_world_news, and offers no context for selection. It is minimally viable but leaves ambiguity.

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 zero parameters, so there are no parameters to document. Per the rubric, baseline for 0 params is 4, and the description does not need to add parameter details. No deduction is warranted.

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 function: 'Get major international news from global sources' with a specific verb and resource. However, it does not distinguish this from siblings like get_world_news or get_news, so it does not fully meet the level of explicit 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?

There is no guidance on when to use this tool versus alternatives. The sibling list includes many overlapping news tools (e.g., get_world_news, get_top_news), and the description provides no context like 'Use for international coverage instead of domestic' or any exclusion 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?

No annotations are provided, so the description must carry the full burden. It merely restates the tool's purpose and offers no behavioral details such as read-only status, rate limits, or output behavior. This leaves the agent without meaningful transparency beyond the name.

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 concise sentence, 'Get military and defense news.', with no unnecessary wording. It is front-loaded and immediately communicates 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 tool with no parameters and an output schema, the one-sentence description is nearly sufficient. However, it lacks any context about its scope or how it differs from the broader get_news tool, making it slightly incomplete when many sibling tools are present.

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 zero parameters and 100% schema coverage, so the description has no additional parameter details to provide. Per the rubric, a zero-parameter tool with high schema coverage receives a baseline of 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 uses the specific verb 'Get' and identifies the resource as 'military and defense news', clearly stating what the tool does. It distinguishes itself from sibling news tools by naming a specific category, though it does not explicitly mention 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?

No guidance is provided on when to use this tool versus similar news tools like get_news, get_top_news, or get_international_news. The description omits any use cases, exclusions, or alternative recommendations.

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 for behavioral disclosure, but it only states 'Get news by category' and lists categories. It does not mention whether this is a read-only operation, any rate limits, authentication needs, or how results are returned. The verb 'get' implies read-only, but the description adds no deeper behavioral context beyond the name.

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 compact and well-structured: purpose first, then usage, then the category values list. Every sentence contributes, and the long list of categories is necessary since it defines the parameter's allowed values. No 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 there are 2 optional parameters, an output schema, and many sibling tools, the description covers the main purpose and category values but lacks explicit mention of defaults (category defaults to 'technology', limit to 10) and does not clarify how this tool relates to the category-specific siblings. These gaps make it incomplete for an agent that might need to choose between get_news and get_ai_news.

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 lists the allowed values for the category parameter, adding meaning beyond the schema (which only specifies a string with a default). However, it says nothing about the limit parameter, and the overall schema coverage is low, so the description only partially compensates for the missing 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 function with a specific verb and resource: 'Get news by category.' It also hints at distinguishing from siblings by mentioning 'specific domain,' but it does not explicitly compare against the many category-specific sibling tools, so it misses the full 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 gives a clear usage context (when the user asks for a specific domain) and lists valid categories, which is helpful. However, it does not mention when not to use it or suggest alternatives like get_top_news or get_ai_news, leaving room for ambiguity.

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 the action ('Get a summary') but does not explain what happens with invalid URLs, whether content is fetched live, error behavior, or what constitutes a summary. This is minimal 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 a single concise sentence that is front-loaded with the key information. Every word contributes meaning, and there is no redundancy or filler.

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?

The tool is simple (one parameter, output schema exists), so the description is minimally adequate. However, it lacks usage context, behavioral notes, and any distinction from sibling tools beyond the URL scope, leaving gaps that could confuse an agent selecting between news tools.

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

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

Schema description coverage is 0%, and the description only adds 'by URL' to clarify the article_url parameter. It does not explain format, constraints, or how the URL should be provided. The description adds minimal meaning beyond the schema's parameter name and type.

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 'Get a summary of a specific article by URL' – a specific verb and resource with a defining scope (by URL). This distinguishes it from sibling tools that fetch news lists or categories rather than a single article summary.

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

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

The description gives no explicit or implied guidance on when to use this tool versus alternatives. It does not mention that this is for retrieving a summary for a specific article URL, as opposed to browsing lists, nor does it mention any prerequisites 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?

With no annotations, the description carries full burden for behavioral disclosure. It only states the purpose and does not mention any behavioral traits such as return format, sorting, pagination, or data scope. This is a significant gap for a tool that fetches external news.

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, concise sentence that immediately states the tool's purpose. There is no fluff or redundant information, and it is front-loaded with the action verb.

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 (no parameters, straightforward news retrieval) and the existence of an output schema, the description is essentially complete for what it does. However, it could benefit from specifying that it returns a list or the latest news, but this is not 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 tool has zero parameters, so the baseline is 4. The description adds no parameter details, but none are needed since the schema is empty and additionalProperties is false.

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

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

The description clearly states the tool retrieves open source and developer community news, which is a specific resource and distinguishes it from sibling tools that fetch other news categories. The verb 'Get' is direct 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?

No guidance is provided on when to use this tool versus alternatives. It does not mention sibling tools like get_ai_news or get_technology_news, nor does it explain the specific context for this news category.

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 disclosing behavioral traits. It does not mention read-only nature, output format, data source, rate limits, or any potential side effects. The simple statement 'Get political news' adds no behavioral context beyond the name.

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 concise sentence with no wordiness, making it appropriately sized for a simple tool. However, it is extremely minimal and could be considered under-specified, though it does contain 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?

The tool is simple with zero parameters and an output schema, so the basic invocation is clear. However, given the lack of annotations and minimal description, there is a gap in behavioral context and usage guidance. It is adequate for a trivial getter but not comprehensive.

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, so the baseline is 4 per the rubric. The description does not need to explain parameter semantics because there are none to explain. The schema shows no properties, and the description adds no parameter-related meaning.

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

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

The description clearly states the tool retrieves political news, using a specific verb ('get') and resource ('political news'). It distinguishes itself from sibling tools like get_technology_news by naming the category, but adds no additional scope or filtering details beyond what the tool name already implies.

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 such as get_news or get_top_news. There is no mention of intended use cases, exclusions, or relationships 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?

No annotations are present, but the description clearly indicates a read-only operation and defines the content scope. It adds context about the types of news included, and no unexpected behaviors or side effects are suggested.

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, front-loaded sentence with no unnecessary words. It efficiently conveys the tool's purpose and 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?

For a zero-parameter, category-specific news getter with an output schema, the description is complete. It names the exact news category and subcategories, making it sufficient for selection among many siblings.

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, so the baseline is 4. The description's mention of missions, science, and technology provides useful context but is not necessary for parameter understanding since the schema is empty and fully covered.

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 'Get space and aerospace news' with a specific verb and resource, and further specifies subcategories (missions, science, technology). This distinguishes it from sibling news category 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 explicit usage guidance or mention of alternatives is provided. The category-specific name and description imply when to use it, but there is no direct comparison to sibling news 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 must disclose behavioral traits. It only lists content topics and does not mention read-only nature, data freshness, pagination, or any other behavior. This lacks the necessary transparency for a tool with no structured 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 a single concise sentence that efficiently enumerates the coverage areas. Every word adds value, with no redundancy or irrelevant details.

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 zero-parameter schema and the presence of an output schema, the description is largely sufficient. It clearly defines the tool's scope, though it could have explicitly differentiated itself from the narrower sibling tools to avoid ambiguity in tool selection.

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 zero parameters, so the baseline for this dimension is 4. The description adds no parameter information, but none is needed since there are no parameters to clarify.

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 function: retrieving technology news covering specific subcategories (AI, chips, software, hardware, open source). This distinguishes it from siblings like get_ai_news or get_hardware_news by indicating a broader scope.

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 the tool is used for general technology news with the listed topics, but it does not explicitly say when to use this instead of the more specific sibling tools (e.g., get_ai_news). No exclusions or alternatives are mentioned, leaving the decision to the agent's inference.

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 reveals a selection behavior (most important, tech/AI prioritized) and a temporal aspect ('right now'), but does not disclose potential limitations like number of results, ordering specifics, or whether it is read-only. For a simple getter, this is adequate but not rich.

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, immediately front-loading the core purpose. It avoids unnecessary words and every sentence contributes meaning: the first defines the output, the second adds a key prioritization detail. This is an model of efficiency.

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 no-parameter tool with an output schema, the description covers the essential selection criteria. However, given the large set of sibling tools, it would benefit from clarifying its relationship to get_news (e.g., 'top stories vs. all news'). The gap is minor but present, so a 4 is appropriate.

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, making schema coverage trivially 100%. The description does not need to add parameter details, and the baseline for 0 params is 4. The description's mention of 'Tech/AI prioritized' provides some context about what the tool returns without needing to reference parameters.

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 fetches the most important global news, with a specific verb+resource (Get + top news). It adds a distinguishing feature 'Tech/AI prioritized' that differentiates it from generic news tools, though it doesn't explicitly compare to siblings like get_technology_news or get_news.

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 obtaining top global news but provides no explicit guidance on when to use this tool versus alternatives like get_news or category-specific tools. There are no exclusions or comparative examples, leaving the selection decision to the agent based solely on the name and vague 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 exist, and the description does not disclose any behavioral details such as return format, scope definition of 'major', or whether it aggregates the listed categories. It adds little beyond the name itself.

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, front-loaded sentence that directly communicates the tool's purpose. No unnecessary words or repetition.

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?

The tool is simple and has an output schema, so return values are covered. However, the description fails to address the significant overlap with sibling tools or provide usage criteria, making the context incomplete for an agent selecting among many similar news 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?

The tool has zero parameters, so the description does not need to explain parameter meanings. The baseline of 4 applies due to the absence of parameters.

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

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

The description clearly states the tool retrieves major world news and lists the covered areas (international, politics, finance, military). It uses a specific verb and resource, but does not distinguish from overlapping sibling tools like get_international_news or get_politics_news.

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. The description only states what it does, without exclusions or alternative references, leaving the agent to infer appropriate use.

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