news-mcp-server

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds valuable behavioral details: it enumerates the return fields (title, summary, URL, timestamp, byline) and states the 24-hour recency limit, which helps set expectations beyond the annotations.

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

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

Three concise sentences serve distinct purposes: purpose, output fields, and usage guidance. There is no redundant wording, and the most important information is front-loaded.

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 one optional parameter and no output schema, the description covers all necessary context: what it does, what it returns, when to use it, and its recency limitation. Combined with annotations, the agent has enough information to select and invoke the tool correctly.

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 has 100% coverage for the single parameter max_results, including default and max values. The description doesn't mention the parameter directly, so it adds no extra semantic meaning. Baseline of 3 is appropriate when schema fully documents the parameter.

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 (fetch breaking news and headlines) and the resource (Associated Press/AP News), and identifies it as a leading global news agency. This distinguishes it from sibling tools like get_bbc_news or get_hacker_news by specifying the exact news source.

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

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

The description provides clear usage context: 'Use for current events coverage, news monitoring, or building newsfeeds' and 'Best for recent breaking stories published within 24 hours.' It doesn't explicitly mention alternatives or exclusions, but the temporal constraint and use cases give practical guidance.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds value by listing exact return fields (headline, synopsis, article URL, publish date, section) and enumerating sections (world/uk/business/tech). It does not mention rate limits or pagination, but the read-only nature is covered by annotations, and the added output details are useful.

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 three concise sentences with no wasted words. It front-loads the primary purpose, then adds usage guidance, then lists output specifics, all in a logical structure. Every sentence contributes unique 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 simple read-only news retrieval tool with one optional parameter and no output schema, the description covers purpose, usage, and return fields sufficiently. It lacks explicit ordering/pagination details, but the schema covers max_results behavior, and the overall context is complete enough for an agent to invoke correctly.

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 coverage is 100% with the single parameter max_results having a clear description. The tool description does not reference the parameter or add additional meaning beyond the schema, so the baseline 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 it retrieves latest BBC News stories, specifying the resource (BBC News) and the action (retrieve). It distinguishes from sibling tools by focusing on BBC and listing the return fields (headline, synopsis, URL, publish date, section), making the tool's scope obvious.

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 explicitly says 'Use for UK perspective on international news or UK-focused stories', providing clear contextual guidance for when this tool is appropriate. This implicitly contrasts with siblings like AP/NPR for other news perspectives, fulfilling the when-to-use requirement.

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

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

The annotations already declare readOnlyHint=true and openWorldHint=true, lowering the bar. The description adds meaningful context by explaining the output fields and that results are 'Ranked by community engagement.' This goes beyond the annotations without contradicting them.

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 core action and result, followed by usage guidance. No filler or redundant repetition of the name or annotations. Every sentence provides 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 simple tool with one optional parameter, the description is complete. It explains what data is returned (six specific fields) and the ranking principle, compensating for the lack of an output schema. Annotations cover safety, and the usage note completes the picture.

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% (the only parameter, max_results, is fully described with default and behavior). The tool description does not add any additional meaning about the parameter, so 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 uses a specific verb ('Pull') and clearly identifies the resource ('top trending stories from Hacker News (Y Combinator community)'). It distinguishes this tool from sibling news tools by focusing on a specific source and content type, and enumerates the exact return fields.

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

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

The description provides clear usage context: 'Use for tech news, startup stories, and developer-relevant content.' This tells the agent when to select this tool over other news sources. It does not mention exclusions or explicitly name alternatives, so it stops short of a 5.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the agent knows it's a safe read operation. The description adds return payload details (headline, summary, link, metadata) but doesn't disclose behavioral traits like rate limits, pagination, or ordering. With annotations lowering the bar, a mid score is appropriate.

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

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

Three well-structured sentences: purpose, return values, and usage guidance. No fluff or redundancy; every sentence contributes 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 simple read-only tool with one parameter and no output schema, the description adequately covers what it returns and when to use it. It could mention edge cases (e.g., empty results) but is sufficiently complete given the low complexity.

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 has 100% description coverage for the single parameter (max_results), including default and purpose. The description adds no additional parameter-specific meaning, so it meets the baseline but doesn't exceed it.

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 a specific verb+resource: 'Access curated news stories from NPR' with focus on US news, science, and culture. It distinguishes from sibling tools like get_ap_news and get_bbc_news by naming NPR and its niche.

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?

It provides clear context: 'Use for journalistic depth and alternative perspectives on major news events.' This implies when to select NPR over other sources, but it doesn't explicitly exclude alternatives or name sibling tools, so it's not a full 5.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds useful behavioral details: the return structure (headline, source, URL, date, relevance score) and sorting by recency. This goes beyond what annotations provide, though it omits rate limits or pagination details.

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

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

Four concise sentences, each with a distinct purpose: action, return fields, use case, and sorting. No filler 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?

Given the simple 2-parameter schema, read-only and open-world annotations, and no output schema, the description fully covers what the tool does, what it returns, and when to use it. It is complete for an agent to select and invoke correctly.

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%, with both parameters (query and max_results) well-described including examples and defaults. The tool description adds no additional parameter-specific meaning, so 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 queries Google News for articles matching keywords/topics, lists the exact return fields, and distinguishes itself from source-specific siblings by covering global news sources.

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?

It explicitly says 'Use for targeted research on specific topics, people, or events,' which provides clear context. It doesn't explicitly exclude alternatives or mention when not to use, but the sibling tools are source-specific, making the usage boundary implicit.

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