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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds meaningful behavioral detail: it ranks events, relies on publisher-supplied summaries, provides source corroboration, and may return partial-feed warnings. This goes beyond the structured hints.

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 with no fluff. The core action is front-loaded, and the return payload is listed concisely. Every clause carries 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 rich input schema, full parameter descriptions, an output schema, and a complete set of safety annotations, the description covers the essential behaviors including rankings, source corroboration, and partial-feed warnings. Nothing critical is missing for a correct call.

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 parameters are fully self-documenting. The description does not add significant meaning beyond the schema; it only mentions corroboration and ranking, which loosely relate to the sources and maxStories parameters. Baseline 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 ('Fetch and rank') and a clear resource ('important recent events from official BBC News and Sky News RSS feeds'). It also states what is returned, which distinguishes it from siblings like search_news and list_news_feeds.

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 this tool is for getting ranked news summaries from BBC and Sky, but it does not explicitly contrast with search_news or list_news_feeds. There is no when-to-use or when-not-to-use guidance, leaving the agent to infer 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?

Annotations already declare the operation read-only, idempotent, and non-destructive, so the description carries less burden. It adds useful context by specifying the feeds are official BBC/Sky News endpoints and that the list is limited to what 'this server can query,' but does not describe other behaviors such as output format or ordering.

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, focused sentence with no redundant wording. It states the action and scope immediately and earns its place 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?

For a zero-parameter, read-only listing tool with an output schema and comprehensive annotations, the description is complete. It tells the agent exactly what the tool returns and is sufficient to invoke correctly without additional 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?

There are no parameters, so the input schema carries no semantics to clarify. The description provides the relevant context about what will be listed, making parameter documentation unnecessary. A baseline of 4 is appropriate for a zero-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 action ('List') and the exact resource ('official BBC News and Sky News RSS endpoints and categories this server can query'). This differentiates it from sibling tools like search_news and get_news_summary, which operate on news content rather than enumerating available feeds.

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 this tool is the discovery mechanism for available endpoints and categories before querying news. However, it does not explicitly name sibling tools or state when to use this tool instead of them, so the guidance is clear but not fully spelled out.

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 establish that this is a read-only, idempotent, non-destructive operation. The description adds useful behavioral context beyond that: it searches recent RSS stories, returns 'ranked and attributed matches,' and covers multiple news sources. No contradictions with the annotations are present.

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, well-structured sentence with no wasted words. It front-loads the core purpose, names the sources, describes the query type, and states the output nature all in one pass.

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 read-only search tool with a rich input schema, full parameter documentation, and an output schema present, this description is complete enough. It communicates the domain, freshness, output format, and ranking behavior, while the schema and annotations cover the remaining operational details.

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 input schema already fully documents every parameter, including defaults, constraints, and meanings. The description itself adds no parameter-level detail beyond implying topical search, but it doesn't need to because the schema carries that weight.

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 action ('Search'), the resource ('BBC News and Sky News RSS stories'), and the intended use case ('for a specific person, place, organisation, or event'). It also describes the output as 'ranked and attributed matches,' making it distinct from the sibling tools, which seem to summarize feeds or list them rather than perform targeted searches.

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 clear context for when to use the tool: when you need recent news stories about a specific topic or entity. It doesn't explicitly mention the sibling tools or state when not to use them, but the phrasing implies a search-oriented use case that is different from listing or summarizing feeds.

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