Korean News Hub

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 only mentions what the briefing combines, but does not describe output format, whether it fetches live data, potential rate limits, or any side effects. This is a significant gap for a tool with no annotation support.

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

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

The description is two sentences, front-loaded with the main action, and every word earns its place. It efficiently communicates purpose and content without any redundancy.

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

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

For a zero-parameter, simple briefing tool, the description is mostly complete. It explains what the briefing contains and its daily nature. The presence of an output schema reduces the need to describe return values, though the description would benefit from a note on the output format or intended use frequency.

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 fully described by default. The description adds relevant context about the contents of the briefing, but there is no parameter-specific semantics to clarify. Baseline of 4 is appropriate for a no-parameter tool.

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: generating a comprehensive daily news briefing. It distinguishes itself from siblings by explicitly listing the combined content categories (Korean headlines, AI/tech news, Claude/Anthropic news), making its composite nature clear.

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 use when a combined daily briefing is needed, covering multiple news domains in one call. It does not explicitly name alternatives or exclusions, but the content list naturally sets it apart from sibling tools dedicated to single categories (korean_news, tech_news).

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 burden of behavioral disclosure. It does mention the count default and maximum, which is a constraint, but it does not disclose whether articles are returned as full text or just headlines, nor any recency or language specifics beyond 'Korean 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 extremely concise, consisting of a single-line purpose and a clear two-item list for args. Every sentence is informative and there is no waste.

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

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

For a simple tool with only two parameters and an output schema, the description is adequately complete. It covers the core behavior and parameter constraints; additional context like return format is not required due to the output schema, but a note on news recency could improve completeness.

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

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

The description explains both parameters, listing valid options for category and the default/max for count, which compensates for the schema's lack of parameter descriptions. This adds meaningful value over the input 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 'Get Korean news by category' clearly states the action (get) and resource (Korean news) with a specific scope (by category). This distinguishes it from sibling tools like tech_news, which focuses on tech, and news_search, which implies searching rather than category-based retrieval.

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

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

No guidance is provided on when to use this tool versus alternatives such as news_search or trending. The description only lists arguments without any context on appropriate use cases or exclusions.

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

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

No annotations are provided, so the description carries the full burden. It does not disclose behavioral traits such as whether it is read-only, how results are sorted, or any rate limits. It does mention a max count of 20, but this is a parameter constraint, not a behavioral disclosure.

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 well-structured: a one-line summary followed by a clean Args list. Every sentence/line is informative without waste.

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

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

Given the output schema exists, return values are adequately covered. However, the description lacks context about when to use this tool versus siblings, and it does not mention any prerequisites or broader usage context. It is adequate for a simple search but incomplete in situational guidance.

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%, but the description thoroughly compensates by explaining each parameter: query includes examples, language specifies allowed values ('ko'/'en'), and count provides default and max. This adds significant meaning beyond the raw 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 'Search news by keyword', which is a specific verb and resource. However, it does not differentiate from sibling tools like korean_news or tech_news, which also deal with news searching. It is clear but lacks sibling differentiation.

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

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

There is no guidance on when to use this tool versus the sibling tools. No exclusions, alternatives, or preferred use cases are mentioned. The description only lists parameters, offering no usage context.

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 disclosure. It mentions 'Read and extract' which implies read-only behavior, but does not address potential side effects, auth requirements, rate limits, or error handling. The behavioral transparency is minimal.

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 exceptionally concise, consisting of one clear sentence plus a brief argument list. Every word earns its place, and it is front-loaded with the primary 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 one parameter and an output schema, so the description covers the basic invocation. However, it lacks usage guidance and behavioral context, which would make it truly complete. It is adequate but has clear gaps.

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

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

Schema description coverage is 0%, so the description's 'url: The article URL to read' adds meaning beyond the raw schema. However, it is minimal and largely restates the obvious from the parameter name and type, offering only slight context about it being an article URL.

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 'Read and extract' with a resource 'article content from a URL', clearly stating the tool's function. It does not explicitly differentiate from sibling tools, but the context of news-related siblings makes the distinction self-evident.

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, no prerequisites, and no usage context. It simply states what the tool does without explaining when it is appropriate to invoke it.

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 tool's basic function and parameter defaults, without revealing any additional behavioral traits such as rate limits, response format beyond the output schema, language handling, or ordering of articles. The 'global' scope is mentioned but not elaborated.

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, front-loaded with the main purpose, and uses a clean Args section for parameter details. Every sentence adds value, with no 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?

The tool is simple (two optional params) and has an output schema, so the description need not explain return values. It covers the essential parameters and defaults. However, it lacks contextual information about when to use this tool versus siblings, which is a minor gap for completeness.

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

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

The description significantly enhances parameter understanding beyond the schema. It enumerates valid topic values (AI, Claude, OpenAI, MCP, OpenClaw, 스타트업, 개발, 클라우드) and specifies that count has a default of 10 and a maximum of 20. This is especially valuable given that the schema has 0% description coverage.

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

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

The description clearly states the action ('Get') and resource ('global AI/tech news by topic'), providing a specific and unambiguous purpose. However, it does not explicitly distinguish itself from sibling tools like korean_news or news_search, relying on the 'global' qualifier to imply differentiation.

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

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

The description provides no explicit guidance on when to use this tool versus alternatives. It only mentions the topic and count parameters, but does not discuss use cases, exclusions, or relationships to sibling tools like daily_briefing or news_search.

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

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

No annotations are provided, so the description carries the full burden. It only implies a read operation via 'Get' and provides parameter meanings, but it does not disclose output details, pagination, rate limits, or any side effects. The description is too thin to establish a clear behavioral profile.

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

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

The description is extremely concise: one lead sentence stating the purpose, followed by a clean Args block explaining the scope parameter. Every sentence earns its place; there is no redundancy or padding.

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 one optional parameter and an output schema, so missing return-value details are acceptable. However, given the existence of sibling tools like korean_news and tech_news, the description lacks guidance on when to select this tool over them, leaving a selection gap.

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

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

The schema provides no description for the only parameter 'scope' (0% coverage), but the description fully compensates by explicitly listing the two allowed values ('korea' and 'tech') with their meanings. This gives the agent complete understanding of the parameter without needing additional schema info.

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 current trending/headline news' and defines the two scope values ('korea' and 'tech'), giving a specific verb+resource+scope. It does not explicitly name sibling alternatives, but the scope parameter meaning partially differentiates it from korean_news and tech_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 explains what the scope values mean, implying usage for Korean headlines or tech trends, but it gives no guidance on when to use this tool versus siblings like daily_briefing, korean_news, tech_news, or news_search. No exclusions or alternative recommendations are provided.

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