hubspot-dbv

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that it returns background/pricing info, which is consistent. It does not detail the output format or any access constraints, but the bar is lower given 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 a single sentence that packs in the purpose, scope, timing, and where to find related resources. It is front-loaded with the key action and resource, followed by useful details. 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?

Given the tool has no parameters, no output schema, and simple annotations, the description is complete. It tells the agent exactly what the tool provides and the context for its use. There are no missing details that an agent needs to invoke it 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?

Since the tool has zero parameters, the description does not need to explain parameter semantics. The schema coverage is 100% (vacuously), so a baseline of 4 is appropriate because the description provides context about what the information covers.

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 provides background and pricing for a specific migration map, including unsupported features, timing, and where to find the free map and paid monitoring. It is distinguished from siblings by focusing on background/pricing rather than listing breaking changes or endpoint lookups.

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 use for planning a HubSpot API migration, which is helpful context, but it does not explicitly say when not to use it or name alternatives. However, the sibling list and the specific focus on background/pricing provide implicit 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 cover read-only, non-destructive behavior, and the description adds meaningful semantics: it defines what BREAKING and REMOVED mean and that the list can be filtered. It does not mention pagination or output shape, but that is a minor gap given the simple read-only nature.

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 tight sentences front-load the operation and definitions, with the use-case sentence adding context rather than filler. No unnecessary detail or repetition.

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-optional-parameter list operation with no output schema, the description adequately explains filtering and the semantic categories returned. A fully explicit output format would improve it, but nothing blocks a correct invocation.

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 already describes the single optional api parameter with 100% coverage. The description only adds concrete examples like 'CRM' and 'Webhooks', which reinforces but does not substantially extend parameter understanding.

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

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

States a specific verb ('List') with a precise resource ('HubSpot API operations whose date-based-versioning replacement is BREAKING... or REMOVED') and defines the two categories. This clearly distinguishes it from sibling lookup tools like get_hubspot_dbv_info or lookup_hubspot_endpoint.

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 frames when to use it ('before starting a migration') and describes the optional API-name filter. It does not explicitly contrast with sibling tools, but the use case is clear enough that an agent can decide when to call 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 indicate readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds context that the tool is derived from HubSpot's official OpenAPI specs and is free with no paid tier, which builds trust and sets expectations about data source. It also highlights that results are not guesses, which is useful for reliability. However, it doesn't disclose any limitations (e.g., coverage gaps, update frequency), which would enhance transparency. Given annotations cover the main behavioral aspect, a 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 a single, well-structured paragraph that front-loads the core purpose and examples, then provides key features (breaking change, field-level differences) and important context (derived from official specs, free). It's concise with no fluff, but it could be slightly more scannable with bullet points or short sentences. Overall, it earns its place.

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 (2 params, no output schema), the description covers the essential aspects: what it does, input examples, output summary (replacement, breaking status, field differences), and data provenance. It lacks details on output structure, but since there's no output schema, a brief mention of output format would be helpful. However, for an agent to call it, the description is 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?

The schema description covers 100% of parameters, explaining 'path' as a legacy API path or fragment with examples, and 'method' as an optional HTTP method filter. The description reinforces this by giving examples in the main text. However, it doesn't add new semantics beyond what the schema already provides (e.g., how the method affects the lookup or format expectations). Since schema coverage is high, the baseline of 3 is correct.

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: lookup a legacy HubSpot API path and get its date-based-versioning replacement, breaking change status, and field-level differences. It specifies the resource ('legacy HubSpot API path') and the action ('look up'), and it distinguishes itself from siblings by focusing on path lookup and detailed differences, whereas siblings likely cover broader lists or general 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 implies when to use this tool: when you need to find the replacement for a legacy path and understand specific changes. It doesn't explicitly mention when not to use it or alternatives (e.g., use list_hubspot_breaking_changes for an overview), but the distinction is clear from the focus on 'exact field-level differences' and 'path lookup'. Slight improvement would be to mention using sibling tools for broader analysis.

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