NewzAI News MCP server

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

The description does not add behavioral traits beyond the annotations (readOnlyHint=true, destructiveHint=false). It mentions the return of metadata like title, source, and publication date, which is mildly helpful but does not disclose error handling, rate limits, or side effects. Annotations already cover safety, so 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?

The description is two sentences with no unnecessary words. It efficiently conveys the tool's purpose and output. 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?

Given the presence of an output schema, the description adequately covers the return value. It does not discuss constraints like article existence or language translation behavior, but it is sufficient for a simple fetch tool with clear annotations. Slight deduction for missing usage 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?

The input schema already provides descriptions for both parameters (news_id and language), covering 100%. The description adds no additional semantic meaning beyond what the schema offers. 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 fetches the full article content for a given news item ID, specifying the verb 'Fetches' and the resource 'full article content'. It also mentions the return of metadata, which distinguishes it from sibling tools like get_news_headlines that likely return only summaries.

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 when not to use it or suggest sibling tools like get_news_headlines for shorter summaries. The description focuses solely on what the tool does without 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?

Annotations already declare readOnlyHint=true, so description adds value by clarifying that language is not a filter and that news in other languages may be included. Does not contradict 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?

Four sentences, no wasted words, front-loaded with purpose. Highly concise and well-structured.

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 (indicated by context signals), the description sufficiently covers the tool's behavior and parameters. No missing information for a simple fetch operation.

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%, so baseline is 3. Description adds meaningful context by explaining the roles of region and language, particularly that language is output-only and not a filter.

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?

Clearly states it fetches news for a predefined category with full details, specifying the returned fields. Distinguishes from siblings like `get_news_headlines` by mentioning 'predefined category' and 'full details', but does not explicitly differentiate.

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?

Provides guidance on asking for region if missing and notes that language is not a filter, but does not compare to alternative tools like `search_news` or `get_related_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 aligns with annotations (readOnlyHint true, destructiveHint false) and adds the behavioral constraint that login is required. It does not disclose other traits, but annotations already cover the safety profile, so the added context is valuable.

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 sentences, zero unnecessary words, front-loaded with the core action. Information is efficiently packed: what it does, what the preference entails, prerequisite, and requirement. Ideal conciseness for a simple tool.

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 an output schema present, return values are covered structurally. The description mentions prerequisite and authentication, providing sufficient context for a read-only retrieval tool. Minor gap: no mention of error cases or missing preferences, but acceptable for simplicity.

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 parameter descriptions. The description adds context that the preference defines category, region, and language, which helps understand preference_id, but does not elaborate on k or last_n_hours beyond what the schema already says. Thus minimal added value beyond the 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 the tool fetches news for a saved user preference by ID, specifying verb and resource. It distinguishes from sibling tools by referencing the prerequisite get_user_preferences, but doesn't explicitly contrast with similar tools like get_news_by_category. This is clear but not fully differentiated.

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 tells users to use get_user_preferences first to obtain valid IDs and notes that login is required. This provides clear when-to-use guidance, though it doesn't specify when not to use or alternative scenarios.

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 destructiveHint=false. The description adds that it returns only title and source (no summary) and implies language parameter behavior, but does not fully cover potential edge cases or error conditions.

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: first states the action and output, second gives usage guidance. Front-loaded, 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 tool with few parameters, output schema, and clear annotations, the description covers what the tool does, what it returns, and when to use alternatives.

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% so baseline is 3. The description does not add meaning beyond the schema for the region parameter, and the language parameter is not mentioned in the description, so no additional value.

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 fetches the latest headlines with title and source only, for a specified region, and distinguishes from siblings that provide full article details.

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?

Explicitly tells when to use this tool (for headlines only) and when to use get_news_by_category or search_news (for full details), providing clear decision 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 indicate read-only and non-destructive behavior. The description adds login requirement and return structure (related_news and close_news with full details), providing useful behavioral context beyond 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 concise (three sentences), front-loaded with purpose, and efficiently covers input requirements, behavior, and output without unnecessary detail.

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 complexity (5 parameters, output schema exists but not provided), the description is complete: covers input requirements, output structure, and authentication. It fully equips the agent to use 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?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining the two modes (by_id vs by_category) and that by_id bases results on that item's content, which goes beyond schema descriptions.

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 news related to a topic or specific news item, using either by_id or by_category. It distinguishes from sibling tools like get_news_by_category by emphasizing the 'related' aspect.

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 specifies required input (by_id or by_category, at least one) and notes login is required. It does not explicitly list when not to use or alternatives, but the context of siblings implies different use cases.

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 destructiveHint=false, indicating a safe read operation. The description adds the login requirement, which is valuable behavioral context. No contradiction with 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?

Two sentences, front-loaded with purpose, no unnecessary words. Every sentence earns its place by stating function and a critical condition (login required).

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 zero parameters, rich annotations, and an output schema, the description is complete. It mentions all relevant output fields and the authentication requirement, leaving no 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?

No parameters are defined, so schema coverage is 100%. The description adds meaning by listing the fields in the output (e.g., news category, region, language), which exceeds the baseline of 4 for zero-parameter tools.

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 'Returns all saved news preferences for the authenticated user' with a specific verb and resource. It lists the fields included and distinguishes from sibling tools like set_user_preferences and update_user_preferences.

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 a clear condition: 'Login is required to access this tool.' While it doesn't explicitly state when not to use it or compare to alternatives, the context from sibling tools implies it's for retrieving all preferences.

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 indicate readOnlyHint=true and destructiveHint=false. The description adds useful context: multi-query behavior, region requirement with user interaction needed, and language not being a filter. No contradictions.

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 paragraph that is dense with essential information. No redundant sentences; every sentence adds value. It is front-loaded with 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?

Given the tool's complexity (7 parameters, output schema exists), the description covers all necessary usage aspects: how to invoke, required parameters, optional settings with defaults, and behavioral notes. It is complete for effective agent use.

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 good descriptions. The description adds value beyond schema by explaining multi-query format and emphasizing that language is output language not a filter. This helps the agent understand nuances not captured in 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 the tool searches news for free-form topics or keywords and returns details. It does not explicitly differentiate from siblings like get_news_headlines or get_news_by_category, but the verb 'search' and mention of multi-query imply a general search capability.

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?

Provides explicit guidance: when to use (free-form topic), how to perform multi-query (separated by 'or'), that region is required and must be asked if missing, language as output not filter, and to leave search_type as auto by default. This covers when-to-use and when-not-to-use.

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 readOnlyHint=false and destructiveHint=false, and the description adds key behavioral context: non-destructive append behavior and login requirement. It does not disclose rate limits or error handling, but the annotations already cover safety 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 concise and front-loaded: first sentence states purpose, then parameter breakdown, followed by behavioral note and requirement. Every sentence adds value without 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?

The tool is relatively simple with one array parameter. The description covers core behavior and appending semantics. It does not explain return values, but an output schema exists (not shown). Could mention duplicate handling, but overall sufficient.

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 descriptions for all properties. The description adds value by clarifying that 'category' can also be a search parameter and recommending to leave search_type as 'auto' for automatic classification. This aids the agent in proper usage.

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 states a specific verb ('Adds'), resource ('news preferences'), and user scope ('authenticated user'). It clearly distinguishes from sibling update_user_preferences by noting that existing preferences are appended, not replaced.

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 context: 'Existing preferences are not removed — new ones are appended.' This implies when to use (append) versus update (replace). It also mentions login requirement. However, it does not explicitly name the alternative tool for replacing preferences.

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 a write operation (readOnlyHint=false) and non-destructive. Description adds login requirement, which is useful. It does not detail what happens after save (e.g., side effects on current session) but is consistent with 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 two sentences, no fluff, with purpose stated first. Every word contributes valuable 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?

With an output schema present and low complexity, the description adequately covers purpose, usage timing, and login requirement. Could mention return value or error behavior 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?

Schema coverage is 100% with clear examples for both parameters. Description mentions 'language and region' but does not add extra meaning beyond the schema, meeting the baseline.

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 saves the user's preferred news language and region. It uses a specific verb 'Save' and resource 'preferred news language and region'. While this distinguishes it from general preference tools, it could explicitly differentiate from sibling set_user_preferences.

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 a clear usage context: call after user confirms preferences. It also notes login requirement. However, it lacks guidance on when not to use this tool or mention of alternatives like set_user_preferences.

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 value beyond annotations by stating that login is required and explaining the behavior of the search_type parameter. It aligns with the readOnlyHint=false (write operation) and destructiveHint=false (non-destructive). No contradictions.

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 with four sentences, front-loading the purpose. It efficiently conveys key information without redundancy, though a bit more brevity could be achieved by combining some sentences.

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 complexity of the nested object and multiple optional parameters, the description covers the main components (category, region, language, optional fields) and addresses authentication. The output schema exists, so return values are not needed. It is contextually adequate.

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 supplements the 100% schema coverage by advising on the search_type default and recommending 'auto' for automatic classification. It adds context about the role of optional parameters like last_n_hours and enable_decay, going beyond the schema definitions.

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 'Update news preferences' for the authenticated user, specifying the resource as news preferences defined by category, region, and language. It distinguishes from sibling tools like 'get_user_preferences' (read) but does not explicitly differentiate from 'set_user_preferences', leaving some ambiguity.

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 mentions 'Login is required' as a prerequisite and advises to leave search_type as auto. However, it does not provide explicit guidance on when to use this tool versus alternatives like 'set_user_preferences', nor does it specify when not to use it.

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