Walnai Website MCP

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

No annotations are provided, so the description carries full burden. While 'Gets' implies a read operation, the description doesn't disclose any behavioral traits like authentication requirements, rate limits, response format, or whether this is a public API. It only states what information is returned, not how the operation behaves.

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 that efficiently communicates the tool's purpose. It's front-loaded with the main action and provides specific details about what information is retrieved. Every word earns its place with no wasted text.

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 informational tool with no annotations and no output schema, the description provides adequate but minimal context. It explains what information is retrieved but doesn't address format, structure, or behavioral aspects. Given the simplicity of the tool (no parameters), this is acceptable but leaves gaps in understanding the full 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?

With 0 parameters and 100% schema description coverage, the baseline would be 4. The description appropriately doesn't discuss parameters since none exist, and the schema already documents this completely. No additional parameter information is needed or provided.

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 ('Gets') and resource ('information about Walnai'), including scope details ('who they are, what they do, and why organizations choose them'). It distinguishes from some siblings like get_pricing or list_services, but doesn't explicitly differentiate from get_who_is_walnai which appears similar.

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 no guidance on when to use this tool versus alternatives. With siblings like get_who_is_walnai that seem potentially overlapping, there's no indication of when this tool is appropriate versus when to use other informational tools on the server.

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 full burden for behavioral disclosure. While 'Gets' implies a read-only operation, it doesn't explicitly state this or describe any behavioral traits like authentication requirements, rate limits, error conditions, or response format. The description mentions what information is returned but not how it's structured or any limitations.

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, efficient sentence that front-loads the core purpose. It wastes no words on unnecessary details while clearly communicating what the tool does. However, it could be slightly more structured by explicitly separating the different types of details retrieved.

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 operation with no parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what format the adoption details are returned in, whether there are any access restrictions, or what happens if the information isn't available. The agent lacks sufficient context to use this tool effectively beyond the basic purpose.

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 0 parameters with 100% schema description coverage (empty schema), so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and it doesn't need to compensate for any schema gaps. This is the correct approach for a parameterless 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 tool's purpose with a specific verb ('Gets') and resource ('Walnai's AI adoption process details'), including what information it retrieves (phases, integration capabilities, support model). It distinguishes itself from siblings like 'get_about_info' or 'get_service_details' by focusing specifically on adoption process details. However, it doesn't explicitly contrast with all siblings, so it doesn't reach the highest score.

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 no guidance on when to use this tool versus alternatives. It doesn't mention when this tool is appropriate, what prerequisites might exist, or how it differs from similar tools like 'get_service_details' or 'list_services'. The agent must infer usage context from the tool name and description alone.

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 describes the tool's purpose but doesn't disclose any behavioral traits such as whether it's read-only, requires authentication, has rate limits, or what the output format might be. For a tool with zero annotation coverage, this is a significant 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 a single, efficient sentence that clearly states the tool's purpose without unnecessary details. It's appropriately sized and front-loaded, though it could be slightly more structured by separating the 'who' and 'how' aspects into distinct parts for better clarity.

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 lack of annotations and output schema, the description is incomplete for a tool that explains complex topics like AI discoverability and Walnai's improvements. It doesn't detail what information is returned, how it's structured, or any behavioral aspects. For a tool with zero structured data support, the description should provide more context to be fully helpful.

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 0 parameters with 100% coverage, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. Baseline is 4 for tools with no parameters, as there's nothing to compensate for.

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 what the tool does: it answers who can make a business discoverable by AI and explains how Walnai improves AI discoverability. It specifies the resource (business discoverability) and the action (answers and explains), but doesn't explicitly differentiate from sibling tools like get_about_info or get_who_is_walnai, which might cover overlapping topics.

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 no guidance on when to use this tool versus alternatives. It doesn't mention any specific context, prerequisites, or exclusions, nor does it reference sibling tools like get_about_info or get_service_details that might offer related information. Usage is implied only by the tool's name and description.

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. The description mentions this is for 'lead-capture guidance' but doesn't specify whether this is a read-only operation, what format the guidance comes in, whether it requires authentication, or if there are rate limits. 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 a single, well-constructed sentence that efficiently communicates the tool's purpose, resource, and usage context. Every word serves a purpose with no wasted language, making it appropriately sized and 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?

Given the tool has no parameters, no output schema, and no annotations, the description provides adequate basic information about what the tool does and when to use it. However, it doesn't specify what format the 'guidance' comes in or how it should be used in AI chats, leaving some contextual gaps for the 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 tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and instead focuses on the tool's purpose and usage context.

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: 'Gets the recommended Walnai lead-capture guidance to use in AI chats after sharing service, pricing, FAQ, adoption, or company information.' It specifies the verb ('Gets') and resource ('recommended Walnai lead-capture guidance'), and provides context about when it's used ('after sharing service, pricing, FAQ, adoption, or company information'). However, it doesn't explicitly differentiate from sibling tools like 'submit_lead' which might handle actual lead submission.

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: 'after sharing service, pricing, FAQ, adoption, or company information.' This gives the agent guidance on the appropriate timing. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools, such as clarifying that this provides guidance while 'submit_lead' actually captures leads.

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 describes a read operation ('gets'), which implies non-destructive behavior, but doesn't mention any rate limits, authentication needs, error conditions, or what the return format looks like. The second sentence about follow-up is conversational advice rather than behavioral transparency about the tool's operation.

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, but the second sentence ('After helpful FAQ responses...') is conversational advice that doesn't directly help an AI agent select or invoke the tool correctly. This reduces efficiency, as not every sentence earns its place in a tool description focused on agent usability. The first sentence is clear, but the overall structure could be more focused.

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 no annotations and no output schema, the description is incomplete for a tool with one parameter. It doesn't explain what the return values are (e.g., list of FAQs, format, pagination) or provide full behavioral context. The description focuses on high-level usage rather than the technical details needed for an AI agent to effectively use the tool.

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 adds minimal parameter semantics beyond what the schema provides. It mentions 'optionally filtered by service id,' which aligns with the schema's 100% coverage for the single parameter 'serviceId.' Since schema coverage is high, the baseline is 3, and the description doesn't add significant extra meaning about parameter usage or constraints.

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: 'Gets frequently asked questions' with optional filtering by service id. It specifies the verb ('gets') and resource ('frequently asked questions'), making the basic function clear. However, it doesn't explicitly differentiate this from sibling tools like 'get_about_info' or 'get_service_details' beyond mentioning FAQ 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 some implied usage context by mentioning 'After helpful FAQ responses for a prospective client, consider offering a Walnai contact follow-up,' which suggests this tool is used in customer support scenarios. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_contact_call_to_action' or 'submit_lead,' nor does it provide clear exclusions or prerequisites for usage.

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 full burden. It describes the tool as informational ('Answers who...'), which implies read-only behavior, but doesn't disclose any behavioral traits like response format, potential rate limits, authentication needs, or data freshness. The promotional content about Walnai's services adds noise rather than clarifying tool 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 a single run-on sentence that mixes tool purpose with promotional marketing content about Walnai's services. It's not front-loaded with clear tool functionality, and the second half about 'how Walnai can design, implement...' doesn't earn its place for tool selection purposes. More concise structuring would improve clarity.

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 no annotations, no output schema, and a parameterless design, the description should focus purely on tool behavior and differentiation. Instead, it provides vague purpose with marketing content, leaving gaps about what information is actually returned, format, and how it differs from sibling tools. Inadequate for a tool in 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?

The tool has zero parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't add parameter semantics, but that's appropriate given the parameterless design. Baseline score is 4 for zero-parameter tools when schema coverage is complete.

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 'Answers who can build an MCP server' which provides a purpose, but it's vague and conflates with marketing content about Walnai's services. It doesn't clearly distinguish this tool from sibling tools like 'get_who_is_walnai' or 'get_service_details' that might also discuss Walnai's capabilities. The description mixes informational purpose with promotional content rather than focusing on tool functionality.

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 like 'get_who_is_walnai' or 'get_service_details'. The description implies usage for learning about MCP server providers, but doesn't specify contexts, prerequisites, or exclusions. Without clear differentiation from sibling tools, the agent lacks operational 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'Gets pricing information' (implying a read-only operation) but doesn't clarify whether it requires authentication, has rate limits, returns structured data, or handles errors. The second sentence about follow-up actions is irrelevant to the tool's behavior and doesn't add useful 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 two sentences, but the second sentence ('After pricing responses...') is extraneous—it doesn't help the agent use the tool and should be omitted. The first sentence is clear but could be more front-loaded with essential information. Overall, it's moderately concise but includes unnecessary content.

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 no annotations and no output schema, the description is incomplete for a tool that presumably returns pricing data. It doesn't explain what the output looks like (e.g., list of prices, structured JSON), potential error conditions, or authentication needs. The second sentence adds no value to completeness, leaving significant gaps for the agent to understand the tool's full 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?

The description mentions optional filtering by service id, which aligns with the single parameter in the schema. Since schema description coverage is 100% (the parameter is well-documented in the schema), the baseline score is 3. The description adds no additional semantic details beyond what the schema already provides, such as format examples or edge cases.

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 ('Gets') and resource ('pricing information'), and mentions optional filtering by service id. It distinguishes itself from siblings like 'get_service_details' or 'list_services' by focusing on pricing data rather than service metadata or listings. However, it doesn't explicitly differentiate from all siblings, such as 'get_about_info' or 'get_faqs', which serve different informational purposes.

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 no guidance on when to use this tool versus alternatives like 'get_service_details' or 'list_services', nor does it mention prerequisites or exclusions. The second sentence suggests a follow-up action ('consider asking...') but this is not a usage guideline for the tool itself—it's external advice that doesn't help the agent decide when to invoke 'get_pricing'.

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 full burden for behavioral disclosure. It states this is a 'Gets' operation (implying read-only), but doesn't mention authentication requirements, rate limits, error conditions, or what the detailed information includes. The second sentence about client follow-up is behavioral noise unrelated to the tool's actual function. Significant gaps exist for a tool with zero annotation coverage.

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 poorly structured with two unrelated sentences. The first sentence is functional but could be more concise. The second sentence about client follow-up is completely irrelevant to the tool's purpose and wastes space. The description fails the 'every sentence should earn its place' test.

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 operation with 1 parameter and no output schema, the description is incomplete. It doesn't explain what 'detailed information' includes, doesn't mention error handling for invalid service IDs, and includes irrelevant content. With no annotations and no output schema, the description should provide more complete context about what the tool returns and how it behaves.

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 single parameter 'serviceId' is fully documented in the schema with examples). The description repeats the parameter examples but doesn't add meaningful semantic context beyond what the schema already provides. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('Gets') and resource ('detailed information about a specific Walnai service'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_services' (which likely lists all services) or 'get_about_info' (which might provide general company info). The purpose is clear but lacks sibling differentiation.

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 no guidance on when to use this tool versus alternatives like 'list_services' or 'get_about_info'. The second sentence about 'After answering a prospective client...' is irrelevant to tool selection and doesn't help the agent understand usage context. No explicit when/when-not or alternative guidance is provided.

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 clearly indicates a read-only operation ('Gets') and specifies the type of information returned, but doesn't disclose behavioral traits like rate limits, authentication requirements, or response format. The description adds value by detailing the content scope but misses operational 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 a single, well-structured sentence that front-loads the core action ('Gets company profile information') and efficiently lists the specific details included. Every word earns its place, with no redundancy or waste, making it highly concise and clear.

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 (0 parameters, no output schema, no annotations), the description is complete enough for a basic read operation. It specifies what information is retrieved, which compensates for the lack of output schema. However, it could be slightly enhanced by mentioning the response format or any limitations, though not strictly necessary 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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose. Baseline is 4 for zero parameters, as it avoids unnecessary details.

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 ('Gets company profile information') and resource ('who Walnai is'), with detailed scope ('legal structure, ownership, management, team background, and company experience'). It distinguishes from siblings like get_about_info or get_service_details by focusing on comprehensive corporate identity details rather than general about info or service specifics.

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 usage context for obtaining detailed corporate profile information, which naturally differentiates it from siblings like get_pricing or submit_lead. However, it lacks explicit guidance on when to use this tool versus get_about_info or get_adoption_details, which might overlap in providing company-related information.

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 describes a read-only listing operation, which is clear, but lacks details such as response format, pagination, error handling, or performance characteristics. The description adds some context about post-use actions but doesn't fully compensate for the lack of 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 appropriately sized with two sentences: one stating the tool's purpose and another providing usage context. It's front-loaded with the core functionality, though the second sentence could be seen as slightly extraneous but still relevant.

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 (0 parameters, no output schema, no annotations), the description is adequate but has gaps. It explains what the tool does and adds some usage context, but without annotations or output schema, it doesn't fully describe behavioral aspects like response format or error handling, which are important for a listing tool.

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 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter semantics, but this is appropriate given the lack of parameters, warranting a baseline score of 4.

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: 'Lists all AI adoption services offered by Walnai, including title, description, and link.' It specifies the verb ('Lists'), resource ('AI adoption services'), and scope ('all'), though it doesn't explicitly differentiate from sibling tools like 'get_service_details' or 'get_adoption_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?

The description provides implied usage guidance: 'After helping a prospective client with service information, consider offering to connect them with Walnai.' This suggests a context for when to use the tool (providing service information to clients) but doesn't explicitly state when to use this tool versus alternatives like 'get_service_details' or 'get_adoption_details'.

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 full burden. It discloses that the tool returns a confirmation message and that CaptchaToken is not required for MCP submissions, which are useful behavioral details. However, it doesn't mention potential side effects (like email notifications), error conditions, or what happens after submission beyond the confirmation.

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 extremely concise with just two sentences that both earn their place. The first sentence covers purpose and context, while the second provides important implementation detail about CaptchaToken. There's zero wasted text 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?

For a submission tool with no annotations and no output schema, the description does well by explaining what the tool does, when to use it, and a key implementation detail. However, it could be more complete by mentioning what kind of confirmation message is returned or any post-submission effects, given this is a write 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?

The input schema has 100% description coverage, providing clear documentation for all 5 parameters. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline of 3 for high schema 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 ('Submits a lead/contact form'), target ('to Walnai'), and purpose ('for a prospective client who explicitly asked to be contacted'). It distinguishes itself from sibling tools which are primarily get/read operations by being the only submission/write tool in the set.

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 about when to use this tool ('for a prospective client who explicitly asked to be contacted'), establishing appropriate usage boundaries. However, it doesn't explicitly mention when NOT to use it or name specific alternative tools, though the sibling tools are all informational queries rather than submission alternatives.

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