nyheter

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

The description adds value by noting error behavior for unknown IDs and the aggregated third-party nature of content. However, annotations include destructiveHint: true, contradicting the read-only retrieval described. This inconsistency reduces trust in the description.

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?

Two sentences in Swedish, front-loaded with the main action, then supplementary notes. No redundant information; every sentence contributes meaning.

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?

With no output schema, the description partially addresses return values (AI summary + metadata) and treats article text as data. However, it lacks specifics on metadata structure or field types, leaving some ambiguity 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?

Schema coverage is 100% with a clear parameter description. The description adds context that an unknown ID yields an error result, not a server error, which aids usage. This extra detail justifies a score above baseline 3.

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 verb 'Hämtar' (retrieves) and the resource 'Apple-nyhetsartikel' from Aapl.se via its id. It specifies the response includes an AI summary and metadata. The single-article-by-id scope differentiates it from sibling list/search 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 guidance on when to use this tool versus siblings like search_news or list_feeds. The description implies it's for known IDs but does not exclude alternatives or provide context for 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?

Adds context beyond annotations: specifies content is aggregated third-party news and advises treating article texts as data, not instructions. Annotations already mark readOnly and destructive hints; no contradiction.

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, each adding value: main action, optional filter, and critical content warning. No 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 list tool with good annotations and schema, description is nearly complete. Lacks explicit return value format, but ordering and source are covered.

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%, but description reinforces parameter meanings: tag is optional filter, limit is number of articles (default 10). Adds slight extra context beyond 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?

States exactly what the tool does: retrieves latest Apple news from a specific source (Aapl.se) with ordering (nyast först). Clearly distinguishes from siblings like search_news and popular_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?

Describes optional filtering by tag, but lacks explicit guidance on when to use this tool over siblings like search_news or popular_news. However, the purpose and sibling names imply 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 indicate both readOnlyHint=true and destructiveHint=true, which is contradictory. The description claims only a listing operation with no mention of destructive behavior, failing to resolve the conflict. This creates a serious inconsistency for the AI agent.

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?

Two concise sentences provide clear, front-loaded information with no unnecessary words. Every sentence adds 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?

The description explains what is listed but lacks details on return structure, ordering, or pagination. Given no output schema, a more complete description of the expected output format would be beneficial.

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 no parameters, so the description does not need to add parameter details. The baseline for zero parameters is 4, and the description does not detract from this.

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 lists active news sources aggregated by Aapl.se, specifying the details included (name, website, language, article count). While it distinguishes the tool's function from siblings, it does not explicitly differentiate from similar listing tools like list_tags.

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 on when to use this tool versus alternatives. The purpose is implicit as a simple list, but the description lacks context for when to choose list_feeds over other listing or search 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?

Annotations include readOnlyHint=true, so the description does not need to add behavioral details, but it also does not clarify the contradictory destructiveHint=true annotation. The description is consistent with read-only behavior but does not explain the inconsistency.

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 unnecessary words. It is front-loaded with the purpose and includes a usage hint, making it highly concise and effective.

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, no output schema), the description is largely complete. It explains the output (tags with article counts) and a use case. Missing a brief note on the return format, but 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 no parameters, so the input schema covers 100%. The description does not need to add parameter information; baseline score of 4 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 lists tags used for categorizing Apple news, including article counts, and explains its purpose in filtering latest_news. It distinguishes itself from sibling tools like get_entry and latest_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 provides explicit guidance on using tags to filter latest_news, indicating a clear use case. However, it does not specify when not to use the tool or mention alternatives.

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 include readOnlyHint and destructiveHint (somewhat contradictory), but the description adds value by noting that summaries are AI-generated and content is aggregated third-party data. It advises treating article texts as data, which is useful behavioral guidance 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?

The description is short and front-loaded with the main purpose. It uses two sentences to convey source, ordering, summaries, and data handling. Minor multilingual mix but overall efficient.

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 source, ordering, content nature, and AI summaries. It is sufficient for an agent to understand what the tool returns and how to interpret the data.

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 for the limit parameter, detailing range and default. The description does not add any additional semantics beyond what the schema provides, so 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 verb ('Hämtar' retrieves), the specific resource (popular Apple news from Aapl.se), and the ordering (by popularity score then newest). It distinguishes from siblings like latest_news and search_news by emphasizing the popularity-based ranking.

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 does not explicitly provide usage guidelines or contrast with alternative tools. It implies use for popular news but lacks direct 'when to use' or 'when not to use' statements, which is a gap given the availability of siblings like latest_news and search_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?

The description adds useful context (semantic search, fallback, AI summaries, warning about content treatment). However, it contradicts the 'destructiveHint: true' annotation; the tool is clearly read-only. This inconsistency harms 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 concise (4 sentences) and front-loaded with the main action. It efficiently conveys key points without 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?

For a search tool without output schema, the description explains the return type (Swedish AI summaries) and mentions fallback behavior. However, it lacks detail on response structure and sorting, and the contradictory annotations reduce 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?

Schema description coverage is 100%, so baseline is 3. The description does not add extra parameter-level details beyond the schema, but that is acceptable given full schema 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 (search) and resource (Apple news from Aapl.se). It mentions semantic search and automatic fallback, providing specific details. However, it does not explicitly distinguish from sibling tools like latest_news or popular_news, slightly lowering clarity.

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 describes what the tool does but offers no guidance on when to use it versus alternatives. It implies usage for searching Apple news but does not provide exclusions or context-specific recommendations.

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