Venturu

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false), the description adds the critical authentication requirement and clarifies that inquiryType selects buyer vs seller representation. It does not describe the response format or potential side effects, but the annotations cover the mutation 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 five sentences and mostly front-loaded with the core action in the first sentence. The final sentence about providing the slug and message is somewhat redundant with the schema and earlier phrasing, but the overall length is appropriate for the tool's complexity.

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 has a small parameter set and no output schema, and the description covers the key operational aspects: auth, parameter semantics, and an alternative for finding slugs. It does not state what the response will be, but for a send-style tool this is a minor gap given the annotations.

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% schema description coverage, the description compensates by explaining all three parameters: slug (broker slug, findable via search_brokers), message (the message to send), and inquiryType (buying default vs selling, with explicit semantics). This provides the agent with the meaning needed to construct a correct call.

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 sends a contact message to a broker identified by their profile slug. It names the specific verb ('Send') and resource ('contact message to a broker'), which distinguishes it from sibling tools like contact_seller and search_brokers.

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 instructs to use search_brokers to find broker slugs and explains how to set inquiryType for buying or selling representation. It also states the prerequisite of an authenticated account, giving the agent clear context for when to invoke the tool. However, it does not explicitly contrast with the sibling contact_seller, though the name and context make this implicit.

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 the tool is not read-only and not destructive. The description adds the requirement for an authenticated account and implies an external side effect (sending a message). It does not disclose details like rate limits, success/failure behavior, or irreversibility, but for a simple message-sending tool this is reasonable. The description does not contradict 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 front-loaded with the purpose in the first sentence and is generally compact. The sentence 'Provide the listing ID and the message to send' is somewhat redundant given the schema, but the overall length is appropriate and each other sentence contributes useful context.

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 two-parameter action with no output schema, the description covers the core aspects: what it does, the authentication requirement, and how to obtain the listing ID. It does not explain differences from contact_broker or what happens after sending, but these are minor gaps given the tool's low complexity.

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 has no property descriptions and schema coverage is 0%, so the description must compensate. It names both parameters ('listing ID and the message') and provides the crucial semantic link that listing IDs come from search_businesses. This is more than just restating the schema, adding practical meaning to the parameters.

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 function: 'Send a contact message to a seller on Venturu by their listing ID.' It identifies both the action (sending a message) and the resource (a seller via listing ID). The use of 'seller' differentiates it from the sibling tool contact_broker, which targets brokers.

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 guidance on prerequisites ('Requires an authenticated Venturu account') and tells the user to 'Use search_businesses to find listing IDs,' which is a helpful pointer. However, it does not explicitly distinguish when to use this tool versus the sibling contact_broker, so it falls short of giving full alternatives or exclusions.

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 limited behavioral context beyond that, such as the source of the slug, but does not detail response format, potential errors, or other nuances. Given the low bar set by the annotations, this is adequate but not rich.

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 primary purpose and followed by usage guidance. Every word earns its place; there is no redundant information or filler.

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 single-parameter tool with no output schema, the description covers the essential points: what it does ('full details'), for which entity ('single broker'), how to identify it ('profile slug'), and where to get the slug ('search_brokers results'). It lacks some edge-case behaviors but is adequately complete for its complexity.

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 only defines 'slug' as a string with minLength 1, offering minimal meaning. The description compensates by specifying it's a 'profile slug' and instructing to use the slug from search_brokers results, adding practical context for how to populate the parameter correctly.

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: 'Get full details for a single broker (agent) by their profile slug.' This is a specific verb+resource combination that distinguishes it from siblings like search_brokers (search) and get_business (different resource). The clarification that 'broker' is an 'agent' further disambiguates the target.

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 usage context: 'Call this when the user asks for more information about a specific broker' and instructs to use the slug from search_brokers results. This is clear guidance on when to use the tool, though it does not explicitly mention when not to use it or name alternatives like contact_broker.

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, so the agent knows this is a safe read operation. The description adds minimal behavioral context beyond the schema, such as returning 'full details', but it does not disclose error handling, authentication requirements, or rate limits. With annotations doing the heavy lifting, a score of 3 is appropriate.

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 filler. The first sentence states the primary purpose, and the second provides usage context and slug provenance. It is well-structured 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?

For a single-parameter read-only tool with annotations and no output schema, the description covers the essential context: what it does, when to use it, and how to get the required slug. It omits error behavior (e.g., not-found handling), but that is not critical for a simple getter. Overall, it is sufficiently complete for an agent to use 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?

The schema has one parameter (slug) with no description (0% coverage). The description compensates by explaining that the slug comes from search_businesses results, giving the agent clear guidance on how to obtain a valid value. This goes beyond the schema and is sufficient for a single parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Get') with a clear resource ('business (listing)') and scope ('by its slug'). It distinguishes itself from sibling search tools by explicitly referencing search_businesses results, making the tool's unique role clear.

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 when-to-use guidance: 'Call this when the user asks for more information about a specific business.' It also indicates the prerequisite of using a slug from search_businesses, implying that search should be used first if no slug is available. However, it does not explicitly exclude other alternatives or mention 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.

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

Annotations already mark readOnlyHint=true and destructiveHint=false. The description adds that this is a discovery tool returning IDs for use in search_businesses, but does not detail response format or size; still, for a zero-param read-only list, this is sufficient 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?

Two sentences, front-loaded with the primary function, followed by usage guidance. No redundant 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 no-parameter, read-only tool with no output schema, the description covers what it does, when to use it, and how to use the result, making it complete in context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so the description need not explain parameter semantics. It adds meaning about the output (categories and business types with IDs), which is 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?

The description clearly states 'Returns all industry categories and their business types with IDs', specifying a unique resource and its output, distinguishing it from siblings like list_languages and search_businesses.

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?

It explicitly instructs to use business type IDs in search_businesses (businessTypeIds) and says to call this first for discovering IDs, providing clear when-to-use guidance and the downstream consumer tool.

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, so the safety profile is covered. The description adds that it returns 'all languages' (scope) and includes IDs, but does not detail the response structure, ordering, or any potential limitations. While adequate for such a simple tool, it adds limited 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 two sentences long, front-loads the primary function, and provides usage context in the second sentence. Every word contributes value, with no redundancy or fluff.

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 reference-list tool with strong annotations, the description is complete. It states what is returned (all languages with IDs) and how to use the result (search_brokers languageIds), which fully addresses the agent's needs given the lack of parameters 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?

There are zero parameters, and the schema coverage is trivially 100%. Baseline for no-parameter tools is 4. The description adds no parameter details because none are needed, which 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 function with a specific verb ('Returns') and resource ('all languages with their IDs'). It also distinguishes itself from sibling tools that focus on search or contact operations, making its purpose unmistakable.

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 explains when to use this tool ('Call this when you need to discover which language IDs to use') and how the output integrates with another tool ('Use these IDs in search_brokers (languageIds)'). This provides strong usage guidance and alternative context.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral details: results are 'verified brokers' and 'email and phone redacted.' This goes beyond the annotations by informing the agent about output content and data policy.

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 primary action ('Search for business brokers'), and each sentence earns its place by conveying purpose and key output characteristics. No redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 12 parameters and no output schema, the description provides a high-level overview but omits pagination/sorting behavior and details on the return structure beyond redaction. However, the core functionality is clear, and annotations cover safety aspects, making this reasonably complete for a search 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?

Schema description coverage is 0%, so the description must compensate. It mentions 'location', 'name', and 'languages', which loosely maps to city/state/county/zipCode/neighborhood/countryCode, name, and languageIds. However, it does not explain page, limit, sort, or opportunityScore, leaving these ambiguous. The description covers the main search facets but not all parameter semantics.

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: searching for business brokers (agents) on Venturu with specific filters (location, name, languages). It also notes the return includes verified brokers with redacted contact info, distinguishing it from similar tools like 'search_businesses' and 'get_broker'.

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—use this tool when you need to search for brokers—but does not explicitly mention when to use alternatives or provide exclusions. Sibling tools are present but not referenced. This is clear context without explicit alternative 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 readOnlyHint=true and destructiveHint=false. The description adds behavioral context beyond annotations by noting 'Returns censored listing data with titles and addresses handled according to listing visibility settings,' which discloses output censorship and visibility behavior not present in 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 three sentences long, front-loaded with the core purpose, and every sentence adds value. There is no redundant or filler 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?

The description covers location, ranges, and return censorship, but given the tool has 38 parameters, nested objects, and no output schema, it omits guidance on pagination (cursor/limit), ordering (orderByProperty/orderByDirection), and the overall result shape. For a complex search tool, this is a moderate gap, so a score of 3 is appropriate.

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% schema description coverage, the description compensates by explaining the most complex parameters: location (natural-language vs bbox) and the min/max range pattern with concrete examples (minPrice/maxPrice, minRevenue/maxRevenue, etc.). It does not explain all 38 parameters, but many are self-explanatory from their names, and the description adds meaningful guidance for the trickier ones.

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: 'Search for businesses (listings) for sale on Venturu.' It uses a specific verb ('search') and resource ('businesses/listings'), and distinguishes from siblings like search_brokers and get_business by naming the platform and resource type.

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 usage context for parameters, such as 'Supports natural-language location ... or an exact bbox' and 'Use flat min/max fields for ranges.' However, it does not explicitly mention when to use this tool versus alternatives (e.g., get_business for a single listing, search_brokers for brokers), so there's no explicit when-not-to-use 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 declare readOnlyHint=true and destructiveHint=false, but the description adds 'Requires authentication' and the purpose of verification, which are behavioral traits not covered by the annotations. No contradictions exist.

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: the first states the core function, the second gives a concrete use case. Every word adds value with no redundancy or irrelevant 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 simplicity (no parameters, no output schema, strong annotations), the description sufficiently covers its purpose, usage, and authentication requirement. Return format details are not essential for the stated verification use case.

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, so the schema fully covers parameter semantics. The description correctly does not attempt to explain non-existent parameters, and the baseline for 0 params is 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 'Returns the identity of the currently authenticated user' with a specific verb and resource. It distinguishes itself from sibling tools like get_broker and search_businesses, which focus on external entities rather than the authenticated user.

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?

It provides explicit usage context: 'Use this to verify that the connection is correctly authenticated (e.g. in the voice agent).' However, it does not explicitly name alternatives or when-not-to-use, though the sibling tools make the distinction clear.

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