vonage-documentation-mcp

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 behavioral disclosure. While it mentions the tool provides 'a direct link or detailed information,' it doesn't specify what format the information comes in, whether it's a summary or full documentation, authentication requirements, rate limits, or error handling. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 appropriately sized with two sentences that each serve a clear purpose: the first states what the tool does, the second provides usage guidance. It's front-loaded with the core functionality and avoids 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?

Given the tool has a simple single parameter with full schema coverage and no output schema, the description is reasonably complete for its complexity level. However, with no annotations and no output schema, it could benefit from more detail about what information is actually returned (e.g., URL, documentation excerpt, structured data) to help the agent understand what to expect.

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 description coverage is 100%, so the schema already documents the single 'query' parameter. The description doesn't add any additional semantic information about the parameter beyond what's in the schema. With high schema coverage, 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's purpose: 'Provides a direct link or detailed information from the Vonage API reference documentation for a specific API endpoint.' It includes a specific verb ('provides') and resource ('API reference documentation'), but doesn't explicitly differentiate from sibling tools like 'vonage_docs_search' or 'vonage_sdk_info'.

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 context on when to use this tool: 'Use this when the user's query is highly technical and related to a specific endpoint, like API parameters, request bodies, or response schemas.' However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling 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?

No annotations are provided, so the description carries the full burden. It describes the output behavior ('generates a complete, runnable code snippet'), but lacks details about limitations (e.g., code quality, error handling), authentication requirements, or rate limits. It's adequate but has gaps for a code generation tool.

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 purpose, followed by usage guidelines. Every sentence adds value without redundancy, making it efficient 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 tool's complexity (code generation), lack of annotations, and no output schema, the description does well by clarifying purpose and usage. However, it could better address behavioral aspects like output format or limitations to be fully complete for this 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?

Schema description coverage is 100%, so the schema already documents the single parameter. The description adds context by explaining what the query should contain ('a given Vonage API task'), but doesn't provide additional syntax or format details beyond what the schema specifies. 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 clearly states the tool's purpose with specific verbs ('generates a complete, runnable code snippet') and resources ('for a given Vonage API task'), and distinguishes it from siblings by specifying it's for code generation rather than reference, documentation, troubleshooting, or examples.

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 states when to use this tool ('when the user explicitly asks for a code snippet, example, or code in a specific language') and provides examples of trigger phrases, clearly differentiating it from sibling tools that serve other purposes like API reference or documentation 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the tool's purpose and scope well but lacks details about behavioral traits such as rate limits, authentication requirements, pagination, or response format. It doesn't contradict any annotations (none exist), but it doesn't provide comprehensive behavioral context beyond basic functionality.

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 front-loaded with the core purpose in the first sentence and follows with usage guidance in the second. Both sentences earn their place by providing essential clarity and context without any wasted words or 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?

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is mostly complete for its purpose. It clearly defines what the tool does and when to use it, though it could benefit from more behavioral details (e.g., response format or limitations) to fully compensate for the lack of annotations and output schema.

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 description coverage is 100%, with the single parameter 'query' fully documented in the schema. The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline of 3 for adequate coverage without adding extra 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 the specific action ('searches') and resource ('official Vonage developer documentation'), specifying the types of content it searches for ('guides, tutorials, and API references'). It distinguishes this tool from its siblings by positioning it as the 'primary tool for general queries' about Vonage's offerings.

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 states when to use this tool ('when the user asks for information, documentation, or how-to guides') and implicitly distinguishes it from siblings by calling it the 'primary tool for general queries,' suggesting alternatives (like the more specific sibling tools) might be better for specialized needs.

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 describes what information is retrieved, which adds value beyond the schema, but lacks details on behavioral traits such as error handling, rate limits, or authentication needs. This is adequate for a read-only tool but misses some context.

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, with two sentences that efficiently convey the tool's purpose and scope. Every sentence earns its place by providing essential information without redundancy, making it highly 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 low complexity (1 parameter, no output schema, no annotations), the description is mostly complete, covering purpose and usage context. However, it could be more thorough by including details on return values or error cases, slightly reducing 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 the schema already documents the single parameter 'query' as the programming language. The description does not add any parameter-specific semantics beyond what the schema provides, such as examples or constraints, resulting in the baseline score of 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 tool's purpose with a specific verb ('Retrieves') and resource ('information about a specific Vonage SDK'), including details like 'installation instructions, supported features, and version numbers'. It explicitly distinguishes from siblings by stating 'not the underlying APIs', which helps differentiate from tools like 'vonage_api_reference'.

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 context for when to use this tool ('for queries focused on the SDKs themselves'), which implicitly suggests alternatives like 'vonage_api_reference' for API-related queries. However, it does not explicitly name when-not-to-use scenarios or list all sibling alternatives, keeping it at a 4.

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 behavioral disclosure. It states what the tool does (provides troubleshooting advice) but lacks details on behavioral traits such as whether it's read-only or mutative, any rate limits, authentication requirements, or the format of the output. For a tool with no annotations, this is a significant gap, as it doesn't explain how the tool behaves beyond its basic function.

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 appropriately sized and front-loaded, consisting of two concise sentences that directly state the purpose and usage guidelines without any fluff. Every sentence earns its place by providing essential information, making it efficient and easy to understand.

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 (a troubleshooting tool with one parameter) and the lack of annotations and output schema, the description is moderately complete. It covers the purpose and usage but lacks details on behavioral aspects and output format. It's adequate as a minimum viable description but has clear gaps in transparency and completeness 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?

The input schema has 100% description coverage, with the 'query' parameter well-documented in the schema. The description adds no additional meaning beyond what the schema provides, such as examples or constraints on the query content. With high schema coverage, the baseline is 3, as the schema does the heavy lifting, and the description doesn't compensate with extra insights.

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 purpose: 'Provides troubleshooting steps, common error code explanations, and debugging advice for Vonage API issues.' It specifies the verb ('provides') and resource ('troubleshooting steps... for Vonage API issues'), making the function evident. However, it doesn't explicitly differentiate from siblings like 'vonage_docs_search' or 'vonage_api_reference', which might also help with issues, so it's not a 5.

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 context for when to use it: 'Use this when the user is reporting a problem, error, or something not working as expected.' This gives explicit guidance on the triggering condition. However, it doesn't mention when not to use it or name specific alternatives among the sibling tools, such as using 'vonage_docs_search' for general documentation instead of troubleshooting, so it falls 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'finds and provides a link,' implying a read-only search operation, but doesn't cover critical aspects like authentication requirements, rate limits, error handling, or what happens if no tutorial is found. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 purpose and followed by usage context. Every word earns its place—there's no redundancy or fluff. It efficiently communicates essential information 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 tool's moderate complexity (a search tool with one parameter), no annotations, and no output schema, the description is partially complete. It covers purpose and usage but lacks behavioral details (e.g., response format, error cases) and output information. This makes it adequate but with clear gaps for an agent to rely on.

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, with the 'query' parameter documented as 'The topic of the tutorial or guide.' The description adds no additional parameter semantics beyond this, such as formatting examples or constraints. With high schema coverage, the baseline is 3, as the schema already provides adequate parameter information.

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 purpose: 'Finds and provides a link to a step-by-step tutorial or a blog post on the Vonage Developer blog.' It specifies the verb ('finds and provides'), resource ('tutorial or blog post'), and source ('Vonage Developer blog'). However, it doesn't explicitly differentiate from siblings like 'vonage_docs_search' or 'vonage_use_case_examples', which might also provide educational content.

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 context for when to use this tool: 'when the user asks for a 'tutorial' or a 'guide' on a specific topic.' This gives explicit usage triggers. However, it doesn't mention when not to use it (e.g., vs. 'vonage_docs_search' for general documentation or 'vonage_api_reference' for API details) or name specific alternatives, keeping it from a perfect score.

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 behavioral disclosure. It mentions what the tool does ('finds and describes') but lacks details on how it operates (e.g., search methodology, result format, limitations). For a tool with no annotations, this is a moderate gap in 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 front-loaded and concise, consisting of two sentences that directly address purpose and usage without unnecessary details. Every sentence adds value, making it efficient 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 tool's moderate complexity (single parameter, no output schema, no annotations), the description is adequate but could be more complete. It explains what the tool does and when to use it, but lacks details on behavioral aspects like result format or limitations, which would be helpful for an AI 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?

The schema description coverage is 100%, with the single parameter 'query' documented as 'The Vonage product (e.g., 'Video API', 'Voice API', 'Messages API').' The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline for high 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 tool's purpose with specific verbs ('finds and describes') and resources ('real-world use cases or customer stories for a specific Vonage product'). It distinguishes itself from siblings like 'vonage_docs_search' or 'vonage_api_reference' by focusing on practical applications rather than technical documentation.

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 states when to use this tool: 'when the user asks for examples of how a product is used in a specific industry or for a particular purpose.' This provides clear context and distinguishes it from alternatives like 'vonage_tutorial_finder' or 'vonage_code_generator' which might serve different needs.

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