commercial

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

The annotations already declare readOnlyHint and idempotentHint, so the description only needs to add non-obvious context. It usefully discloses that the tool operates on public data only and that use cases are illustrative, which helps set expectations without contradicting 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?

Two concise sentences with the core purpose front-loaded and the important privacy caveat second. No filler, repetition, or boilerplate.

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 the central operational constraint (public-data-only scope) and the output schema handles return-value expectations. However, it leaves locale semantics and query phrasing largely underspecified, and it does not help an agent choose between this and closely related commercial siblings. Adequate but not fully complete.

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 carries the parameter-semantics burden. The phrase 'a prospective need' gives some meaning to the query parameter, but locale is never mentioned and its purpose must be inferred entirely from the enum values and default. The description adds only marginal parameter-level 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 uses a specific verb ('Match') and defines the resource scope: prospective need to public capabilities, illustrative use cases, and plans. It also differentiates itself by explicitly stating no access to customer projects or private data, though 'plans' is somewhat ambiguous and no sibling is named.

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 main sentence implies when to use this tool: when a prospective need should be matched to DigitalPublic's public offering. The privacy caveat establishes a clear exclusion boundary for customer-specific or private-data questions, but it does not explicitly route to alternatives like list_use_cases, get_offer, or compare_offers.

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

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

The annotations already mark the tool as readOnly and idempotent, and the description's 'recommend a plan' aligns with those signals without contradicting them. The description adds little beyond that, such as whether any state changes occur or how conflicting criteria are resolved, but with read-only annotations the bar is lower and the safe behavior is adequately conveyed.

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 fronts the primary action and enumerates the relevant inputs with no filler or repetition. Every word contributes to the agent's understanding of what to pass.

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 presence of an output schema reduces the need to describe return values, and the description covers the main input semantics. However, it omits the locale parameter and does not explain how the plan is chosen or when this recommender is preferred over sibling commercial tools, leaving a few gaps for an agent deciding to invoke it.

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 meaningfully maps the main criteria to the parameter concepts: project count -> projects, team size -> teamSize, live-data need -> wantsLiveData, distributor status -> distributor, and write requirement -> needsWrite. It does not mention locale, but it clarifies the purpose of five of the six parameters, adding substantial meaning over the bare schema.

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

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

The description clearly states the tool recommends a plan, which is a specific verb plus resource, and lists the exact decision criteria (project count, team size, live-data need, distributor status, write requirement). It does not explicitly distinguish itself from sibling comparison/estimation tools like dp_commercial_compare_offers or dp_estimate_roi, but the criteria-based recommendation function is recognizable enough.

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?

There is no guidance on when to use this tool versus the many sibling commercial tools. The description does not mention alternatives, exclusions, or preconditions, leaving the agent to infer from the tool name and criteria list 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?

Annotations already convey non-readonly, non-idempotent, open-world behavior, so the description only needs to add context beyond that. It adds that live trials produce no operational credential, that this is a legacy path, and that OAuth is the current replacement. It doesn't state whether claiming consumes/revokes the credential or what exactly happens on repeated claims, but the annotations cover idempotency.

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 compact and front-loaded, with two sentences that carry essential scope and routing information. The phrasing 'still-valid historical paid checkout intents' is slightly awkward, but there is 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?

The output schema presumably covers return values, and the description clearly handles the main alternative path. However, because parameter semantics are completely absent, an agent cannot confidently determine how to fill intentId and claimSecret or how to recognize a 'still-valid historical paid checkout intent.' This is a meaningful completeness gap.

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%, and the description never explains what intentId or claimSecret mean, where they come from, or how to obtain them. Both parameters are required and only have length constraints, so an agent has no semantic grounding for invoking the tool 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 states a specific action ('claim') on a specific resource ('credentials') and clearly scopes it to 'still-valid historical paid checkout intents.' It also distinguishes itself from the live-trial/OAuth path, making it easy for an agent to tell this tool apart from the many sibling tools.

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 says when this tool applies ('still-valid historical paid checkout intents') and when it does not ('Live trials never deliver an operational credential in chat'). It also names the preferred alternative: 'install DigitalPublic and use project OAuth instead.' This gives clear routing 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 communicate readOnlyHint=true and idempotentHint=true, and the description does not contradict them. The description adds useful scoping around what is compared, but it does not disclose behavioral details like what data sources are used, whether the comparison is generated in real time, or what the output contains beyond what the output schema likely covers.

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, front-loaded sentence with no filler or redundant restatement of the title. Every phrase earns its place by either specifying the comparison targets or the evaluation dimensions.

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 simple optional-locale parameter, read-only annotations, and presence of an output schema, the description provides enough scope for an agent to invoke the tool correctly. The only notable gap is the lack of explicit linkage between locale and the output language, but this is a minor issue for a zero-required-parameter 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 input schema has one parameter, locale, with an enum and a default value, but schema description coverage is 0%. The description does not mention locale at all, leaving the agent to infer that the comparison may be localized based on this parameter. This does not compensate for the missing schema descriptions.

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

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

The description names the specific action ('provide an objective comparison') and the exact objects being compared ('direct provider MCP servers and DigitalPublic'), and it lists four concrete dimensions: setup, governance, cross-channel work, and tradeoffs. This clearly distinguishes it from sibling tools like list_integrations or ask_navigator.

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 intended use is inferable from the description and title, but the description does not explicitly say when to choose this tool over alternatives such as dp_commercial_list_integrations or dp_commercial_get_security_profile. No exclusion criteria or when-not-to-use 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety and side-effect expectations. The description adds the 'canonical catalog' qualifier, which hints at a standardized data source, but does not disclose other behavioral traits such as error behavior, plan availability, or whether any filtering is applied. This is a modest addition over 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 a single, front-loaded sentence with no filler. Every word contributes to the core meaning, and it avoids repeating the tool name or title excessively.

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

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

The tool is simple, the output schema exists, and annotations cover the safety profile, so the description does not need to explain return values. However, the description omits the meaning of 'canonical catalog' and does not clarify when to use this tool among many similar siblings. These gaps keep it from being fully self-sufficient, though the simple nature of the tool makes it adequate overall.

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 bears the burden of explaining planIds. It only paraphrases the schema's minItems=2 as 'two or more plans' and gives no detail about what planIds represent, how they should look, or where they can be obtained. The parameter semantics are therefore weakly conveyed.

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

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

The description states a specific verb ('compare'), a clear resource ('plans'), and a scope qualifier ('using the canonical catalog'). This distinguishes the tool from siblings such as dp_commercial_compare_integration_options (which compares a different resource) and from get_offer/list_offers (which perform different operations).

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 dp_commercial_list_offers, dp_commercial_get_offer, or dp_commercial_compare_integration_options. There are no explicit conditions, exclusions, or references to related tools, leaving the agent to infer usage from the name 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?

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds some context by indicating the response is aimed at both humans and AI agents, but it does not describe any behavioral details beyond that.

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, front-loaded sentence with no superfluous content. It earns its place by stating the tool's core purpose clearly and economically.

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 simplicity of the tool, the presence of an output schema, and annotations covering idempotence and read-only behavior, the description is mostly adequate. However, it lacks usage guidance and any clarification of the locale parameter, leaving minor but real gaps.

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

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

The schema has 0% description coverage, and the description does not mention the 'locale' parameter at all. Since the description was expected to compensate for the missing schema descriptions, it fails to add any parameter-level meaning, even though the single parameter is simple and optional.

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 clear verb ('Explain') and identifies the resource ('DigitalPublic'), making the basic purpose understandable. It does not explicitly differentiate from the many sibling tools, but the general overview scope is implied by the name and description.

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 gives no guidance on when to use this tool versus alternatives like dp_commercial_get_company_profile or dp_commercial_list_use_cases. There are no when-to-use conditions, exclusions, or references to 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds behavioral context beyond annotations: it states the calculation is restricted to entered inputs, lists the specific calcued outputs, and explicitly disclaims forecasting. This is useful and consistent with the annotations, though it does not go into formula details or error 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?

Two short sentences, no fluff, and the scope is front-looaded with 'Calculate only'. The second sentence earns its place by explicitly ruling out a plausible misuse. This is an example of conciseness that improves usability.

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 four-parameter calculator with an output schema available and read-only/idempotent annotations, the description is largely complete: it identifies inputs, outputs, and what the tool will not do. It does not explain the exact formula or plan-pricing logic, but those are likely visible in the output schema or not needed to invoke the tool correctly. The main gap is slightly richer parameter guidance, already accounted for in parameter semantics.

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 partially does so by mapping 'time savings' to hoursSavedPerMonth and 'plan cost' to planId, and it names the outputs. However, it does not elaborate on the semantics of hourlyCost or currency, and the relationship between planId and plan cost is only implicit. The self-explanatory parameter names and enums help, but the description itself leaves some parameter meaning under-specified.

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

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

The description states a specific verb ('Calculate') and a precise resource scope ('DigitalPublic time-value ROI'), then narrows it further to time savings, plan cost, net value, and break-even hours. The explicit negative clause 'It never forecasts sales or advertising performance' clearly distinguishes this tool from any predictive/commercial tool among the siblings.

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 makes the intended use clear: this tool only values entered time-savings, plan cost, net value, and break-even hours. It also supplies an explicit exclusion ('never forecasts sales or advertising performance'), so an agent knows not to use it for forecasting. It does not name a specific alternative sibling, but the context and negative scope still provide solid 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 and idempotentHint, covering the safety profile. The description adds content scope ('explicit qualifications' and the capability categories), but does not address locale-dependent behavior or return formatting. This is comparable to the high-calibration example, where content scope earns a 3 given strong 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, well-formed sentence with no wasted words. The primary action and resource are front-loaded, and the content scope is enumerated compactly. It is appropriately sized for a simple read-only tool.

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

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

This is a simple tool with one optional parameter, no required parameters, an output schema for return values, and annotations covering safety. The description together with the schema and annotations provides all essential information for an agent to invoke it correctly. Nothing critical is missing.

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 for explaining the locale parameter, but it does not mention it at all. Although the parameter name and enum values make the locale self-explanatory, the description still fails to provide any additional meaning beyond the structured 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 states a specific verb 'List' and a clear resource, the DigitalPublic capability matrix, and enumerates the categories included (read, preparation, supervised-write, approval, plan, module). It is distinct enough from sibling tools like get_security_profile or get_data_processing_profile, though it does not explicitly name alternatives.

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?

Usage context is implied by the tool name and description: if an agent needs the capability matrix, this is the tool. However, there is no explicit when-to-use guidance, exclusion of alternatives, or differentiation from the many sibling get_ 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?

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds useful behavioral context by specifying exactly which availability dimensions are reported—real trial, self-service checkout, and Enterprise proposal onboarding—which goes beyond the generic tool name.

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 front-loaded sentence with no filler. It names the action and the three scopes in compact, unambiguous language.

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, read-only status tool with an output schema and annotations, the description is largely complete. It defines the exact query scope. It could be slightly stronger by pointing to sibling tools for deeper status detail, but nothing essential is missing.

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 and schema description coverage is 100%, so there is no parameter burden for the description to carry. The baseline of 4 applies since no parameter clarification is needed.

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 ('Report whether') and identifies the exact resource: current availability of the real trial, self-service checkout, and Enterprise proposal onboarding. This clearly distinguishes it from vague status tools and gives the agent a precise sense of what the tool does.

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 the tool is for checking current availability/readiness across three named onboarding paths, but it does not explicitly say when to prefer it over siblings like dp_commercial_get_checkout_status or dp_commercial_get_live_trial_status. Usage context is clear enough, but alternatives and exclusion criteria are not stated.

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 and idempotentHint, so the safety profile is covered. The description adds useful behavioral nuance by stating that only 'non-sensitive' status is returned, which tells the agent the response is intentionally sanitized. This is meaningful context beyond the annotations, though it does not discuss authentication or response filtering details.

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, no filler, front-loaded with the core behavior and followed by a targeted alternative. Every sentence earns its place and the structure makes it easy for an agent to parse quickly.

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 parameter-count tool with readOnly/idempotent annotations and an output schema, the description covers scope and the primary sibling alternative well. However, the complete absence of parameter guidance for intentId leaves a small but meaningful gap in the overall calling 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 never mentions 'intentId' or explains where it comes from, what it represents beyond the request context, or how to obtain it. With schema description coverage at 0%, the description was expected to compensate, but it does not, leaving the parameter semantics mostly dependent on the parameter name.

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 names a specific verb ('Return') and resource ('non-sensitive status of a historical checkout or proposal request'), which clearly distinguishes it from related status tools. It also explicitly distinguishes itself from the live-trial status sibling, so an agent can select it without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear directive for when not to use the tool ('For the real trial use dp_commercial_get_live_trial_status') and names the exact alternative. The first sentence implies the affirmative use case: retrieving checkout or proposal status, which is sufficient 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 establish readOnly and idempotent behavior. The description adds that the data is 'verified' and includes evidence URLs, which is some contextual value, but it discloses no additional behavioral traits such as locale behavior, data sourcing, or access requirements.

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?

One clear sentence, front-loaded with the return content and scoped to DigitalPublic. No filler 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 simple read-only tool with one optional enum parameter and an output schema, the description is largely sufficient. It omits explicit usage guidance and locale semantics, but those are minor given the low complexity and the richness of the schema and 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 needed to explain the locale parameter, but it never mentions locale or how the value affects the returned profile or evidence URLs. The schema enum and default are present, but the description itself adds no parameter meaning.

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 names a specific action ('Return') and a precise resource: DigitalPublic's verified legal identity, corporate contacts, and evidence URLs. These concrete data categories distinguish it from sibling tools like get_security_profile or get_data_processing_profile.

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 the tool whenever the agent needs company identity, contacts, or evidence URLs, but it gives no explicit guidance about alternatives or when not to use it. Usage must be inferred from the resource scope rather than directly stated.

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

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

The annotations already declare readOnlyHint and idempotentHint, so the description does not need to restate safety. It usefully adds that the response covers authentication modes, scopes, human prerequisites, review state, and known limitations, but it does not disclose error behavior or any connector-specific constraints.

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 with no filler or repetition. It front-loads the action and the main content categories, making it easy for an agent to quickly infer the tool's scope.

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

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

The tool is simple: one required parameter, read-only annotations, and an output schema are present, so the description does not need to explain return values. It covers the purpose and scope well, though explicit connectorKey guidance and usage exclusions would make it fully complete.

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 for the lone connectorKey parameter. It partially does by saying 'for one DigitalPublic connector', which implies connectorKey selects that connector, but it does not explain connectorKey format, provenance, or accepted values in detail.

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 names a specific verb ('Explain') and a precise resource: authentication modes, scopes, human prerequisites, review state, and known limitations for one DigitalPublic connector. These content areas distinguish it from sibling tools like get_install_options or get_onboarding_guide without needing to open their schemas.

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 the tool should be used when a caller needs connection requirements for a particular connector, but it does not explicitly state when to prefer it over siblings or when not to use it. No alternatives or exclusions are mentioned, so the usage guidance is only 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?

The annotations already convey read-only and idempotent behavior, and the description adds useful context about what the profile covers, including privacy, DPA, c ontrols, and evidence URLs. It does not contradict the annotations and gives the agent a clearer picture of the response's focus.

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?

A single compact sentence lists all relevant topic areas with no filler, repetition, or unnecessary detail. Every phrase contributes to the agent's understanding of what the tool returns.

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 one-parameter, read-only tool with an output schema and annotations, the description is mostly complete: it captures the core subject areas and even mentions evidence URLs. It could be slightly stronger by explicitly differentiating from sibling profile tools, but the content list makes the scope clear.

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 optional locale parameter with an enum and default, which is self-explanatory, but the description adds no explanation of locale or how it affects the response. With schema description coverage at 0%, the description was expected to compensate but does not.

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, 'Explain', and lists concrete content topics: controller and processor roles, public AI training policy, private customer data exclusions, controls, DPA, privacy, and subprocessor evidence URLs. This clearly identifies the tool's purpose and makes it distinguishiable from sibling tools like security or company profile tools, even without naming an alternative.

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 explicit when-to-use guidance, alternatives, or exclusion criteria. An agent must infer from the topic list when this profile tool is appropriate, and there is no comparison with sibling tools such as dp_commercial_get_security_profile.

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, idempotentHint=true, and destructiveHint=false. The description adds real behavioral value by warning that 'Directory URLs remain null until publication is explicitly enabled,' which is a non-obvious state an agent must know. It also clarifies the 'authenticated' requirement and the concept of 'publication-aware' 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 with no wasted words. The primary operation is front-loaded, and the critical caveat about directory URLs is placed second, making the structure both efficient and easy to parse.

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

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

Given the output schema exists and annotations cover the safety profile, the description does not need to explain return shapes or non-destructiveness. The main behavioral caveat is included, and the auth context is mentioned. The only notable omission is the meaning of the locale parameter, which slightly reduces completeness for a tool with one parameter.

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%, and the description does not explain the locale parameter at all. The schema provides an enum and default, so an agent can infer some meaning, but the description should have compensated for the missing schema documentation by stating whether locale controls the language of the returned install options or something else. This is a clear gap.

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

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

The description states a specific verb ('Return'), a clear resource ('publication-aware installation options for the authenticated DigitalPublic operational product'), and the target contexts (OpenAI, Claude Code, generic MCP clients). This distinguishes it from siblings like compare_integration_options or list_integrations without needing to open the schema.

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 the tool is for retrieving install options and emphasizes the 'authenticated' and 'publication-aware' aspects, giving some context. However, it does not explicitly state when to use this tool versus sibling tools such as dp_commercial_compare_integration_options or dp_commercial_list_integrations, nor does it name 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 readOnly, idempotent, and non-destructive, so the description adds meaningful privacy guarantees: it never returns email, provider tokens, OAuth URLs, or provider payloads. This goes beyond the structured annotations and helps an agent reason about safe usage.

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: the first states the action and inputs, the second lists return content and explicit exclusions. There is no filler or repetition of schema details.

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

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

With an output schema present, the return-value details are already covered. The description adds the key safety exclusions and the token requirement. It is mostly complete for a simple read-only status tool, though parameter semantics could be richer.

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 clarifies that statusToken is a 'limited status token' and contrasts it with provider tokens, but it does not explain where trialId comes from or how the two parameters relate. The parameter meaning is only partially inferred.

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 identifies the resource (live trial status) and action (get/resume via status token), and the second sentence details what is returned. It is distinguishable from siblings like start_live_trial, though 'Resume a trial' is slightly less direct than 'Get status'.

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 when a limited status token is available and the caller needs trial status. However, it does not explicitly contrast this with sibling tools such as start_live_trial, get_checkout_status, or get_onboarding_guide, leaving the selection logic to inference.

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 and idempotentHint, so the safety profile is clear. The description adds only the scoping notion of 'current' and 'by id', but does not disclose error behavior, permissions, or data freshness. With annotations covering the main concerns, 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, compact sentence with no filler. Every word ('Return', 'one', 'current', 'plan', 'by id') contributes meaning, and the key operation is 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 tool with readOnly and idempotent annotations plus an output schema, the description is mostly complete. The only gap is navigation: an agent without a planId may not know to use list_offers, but that is a minor omission given the tool's simplicity.

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

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

Schema description coverage is 0%, so the description must compensate. 'by id' maps directly to the required planId parameter and gives it meaning, but it does not explain what a valid planId looks like or how to obtain one. The parameter name is self-explanatory, so this is minimally adequate.

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 ('Return') and a specific resource ('one current plan') with an identifier qualifier ('by id'). This clearly distinguishes it from siblings like dp_commercial_list_offers (plural) and dp_commercial_compare_offers, which operate on multiple plans.

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: you need a specific plan id to fetch a single plan, which differentiates it from listing or comparing offers. However, it does not explicitly state when to prefer this tool over siblings or mention alternatives like list_offers when an id is not available.

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

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

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description's 'Return' is consistent with those. The description adds useful context about the guide's contents, such as mandatory human checkpoints and the handoff, but it does not address auth needs, side effects, or edge behavior. For a read-only guide with annotations covering the safety profile, this is adequate but not exceptional.

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 front-loaded sentence that names the verb, resource, and key distinguishing features without fluff. Every part earns its place, and it remains compact for what it conveys.

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 tool with zero required parameters, a safe read-only annotation profile, and an output schema, the description covers what matters: the nature of the returned sequence and the critical handoff/checkpoint content. Return-value details are already handled by the output schema. The missing when-to-use guidance is a usage-guidance concern, not a contextual completeness gap for this simple 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 only parameter, locale, is constrained by enum ['es','en'] and default 'es' in the schema, but the description provides no explanation of it. With schema description coverage at 0%, the description should compensate by noting that locale selects the guide's language, and it does not. Invocation is still feasible because there is one optional, fully constrained parameter, so this is below baseline but not broken.

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

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

The description states a specific verb and resource: it returns the goal-oriented onboarding sequence an agent should follow, and it names two concrete contents, mandatory human checkpoints and the handoff from DigitalPublic Commercial to DigitalPublic. This clearly distinguishes it from sibling get_* tools such as dp_commercial_get_capability_matrix or dp_commercial_get_checkout_readiness. The title is reinforced, not merely restated.

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 when-to-use or when-not-to-use guidance is provided. The description does not say when an agent should choose this tool over siblings, nor does it name any alternatives or exclusions. The intended usage is only implicit from the tool name and title.

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 and idempotentHint, so the safety profile is covered. The description adds valuable context beyond annotations: the result is synthetic, illustrative, contains no customer data, and must not be misrepresented as real measured performance.

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 core purpose is front-loaded, and the second sentence adds an essential guardrail. Every sentence 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?

With zero parameters, an output schema, and annotations covering read-only/idempotent behavior, the description provides the key missing semantic context: the output is synthetic and must not be mistaken for real customer performance. Nothing material is missing.

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 and the empty schema is fully covered. No parameter explanation is needed, and the baseline of 4 for no-parameter tools applies.

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

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

The description states a specific verb ('Return') and resource ('illustrative synthetic report sample'), and explicitly clarifies it contains no customer data. It also distinguishes the tool from a service trial by stating it is not one, which helps differentiate it from sibling trial/status tools.

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 this tool should be used to retrieve a synthetic sample report and explicitly warns against representing it as measured customer performance. However, it does not state when to prefer this over sibling tools such as dp_commercial_get_live_trial_status or dp_commercial_get_offer.

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 and idempotentHint, so the safety profile is clear. The description adds the explanatory nature of the tool and the topics it covers, but does not disclose details like response shape or whether it returns live configuration versus general documentation. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence that front-loads the resource and lists the key content areas with no filler. Every word 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 that output schema exists and there are no parameters, the description covers the main subject matter adequately. It could improve by indicating how this profile relates to other profiles, but the listed topics give enough context for an agent to understand what the tool provides.

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?

This tool has zero parameters, so parameter documentation is essentially moot. The baseline for no-parameter tools applies, and the description does not need to compensate for missing parameter 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 names a specific resource (security profile) and lists concrete topics: project isolation, scopes, approvals, token revocation, and audit controls. It is distinguishable from siblings like get_company_profile or get_data_processing_profile, though it doesn't explicitly contrast itself with them.

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?

There is no guidance on when to use this tool versus alternatives such as get_data_processing_profile or get_company_profile. The context is implied to be informational/security-related, but no explicit exclusions or routing cues are 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?

Beyond the annotations, the description adds meaningful behavioral context: status comes from an independent external monitor, missing evidence yields 'unknown', and 'unknown' must not be treated as healthy. This materially shapes how an agent should interpret the response.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences, front-loaded with the core action. Every sentence adds essential interpretive guidance without redundancy 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?

With no parameters and an output schema present, the description supplies the critical behavioral caveats that could affect correct interpretation, such as the meaning of 'unknown'. Nothing essential is missing.

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 there is nothing for the description to clarify. This matches the baseline of 4 for parameterless tools.

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

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

The description states a specific verb and resource: 'Return current component health and timestamp.' It also differentiates itself from the related get_uptime_history sibling by explicitly noting it does not invent uptime history or an SLA.

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 clearly conveys this is for current live status rather than historical uptime data, which provides good usage context. It stops short of explicitly naming a sibling alternative or stating when not to use it, but the distinction is strongly implied.

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 and idempotentHint, and the description adds valuable behavioral context: it always returns coverage alongside uptime, returns 'insufficient_data' when coverage is too low, and clarifies that DigitalPublic publishes no contractual SLA. These are meaningful details beyond the annotations and schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each earning their place: the core result, the critical caveat about coverage, and the edge-case behavior. The main function is front-loaded and no words are wasted.

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 read-only tool with two self-explanatory parameters and an output schema, the description is nearly complete. It covers the main behavior, the mandatory pairing with coverage, the insufficient-data edge case, and the SLA stance. The main gap is explicit parameter guidance, but the enum values and output schema compensate.

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%, and the description does little to explain the parameters. It mentions 'component' and 'historical uptime,' which loosely maps to componentId and window, but it does not explain the window options, defaults, or what componentId refers to beyond the name.

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

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

The description states a specific action ('Return historical uptime') on a specific resource ('a component') and adds the distinctive requirement that data coverage is always included. It is clearly not a status or offer tool, though it does not explicitly name a sibling for contrast.

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 the tool: whenever historical uptime for a component is needed, and it warns that coverage must be considered alongside uptime. It does not explicitly mention alternatives like get_service_status or state when not to use it, though the 'no contractual SLA' note suggests it should not be used for SLA verification.

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 convey readOnlyHint and idempotentHint. The description adds field-level behavioral context by telling the agent which output field (trialChannels) to pass downstream and which to avoid (connector id), going beyond what annotations provide.

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, each earning its place. The first sentence front-loads the core purpose, and the second delivers a specific, non-obvious usage instruction. No filler 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?

With no parameters, an output schema present, and annotations covering safety, the description supplies the remaining key context: the scope (commercial V1) and the downstream field mapping to dp_commercial_start_live_trial. An agent has everything needed to call and use this tool correctly.

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

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

The tool has zero parameters, so the input schema fully covers parameter semantics by vacuous completeness (100% coverage). The description needs no parameter explanation; baseline 4 applies.

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 and resource: 'List integrations included in commercial V1.' This clearly distinguishes from sibling list tools (list_offers, list_use_cases) by the noun 'integrations' and scopes to a particular plan version.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides actionable context: the tool lists commercial V1 integrations, and explicitly instructs that trialChannels (not connector id) should be used as channels for dp_commercial_start_live_trial. It lacks explicit when-not-to-use or alternative routing, but the cross-tool guidance is concrete and useful.

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

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

The annotations already declare readOnlyHint=true and idempotentHint=true, covering the main behavioral profile. The description is consistent with those annotations and adds scope details about what is listed, but it does not disclose extra behavior such as locale handling, pagination, or response shape beyond the output schema.

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, front-loaded sentence that immediately states the action and resource, then lists the key content areas. There is no filler, repetition, or 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?

For a simple read-only list tool with an optional parameter and an output schema, the description covers the essential scope and safety context. It is slightly incomplete because it does not clarify how locale affects output or when to prefer this over closely related sibling tools, but these are minor gaps.

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

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

The only parameter, locale, has no description in the schema (0% coverage) and is not mentioned in the tool description. An agent must infer from the enum and default that it controls language, but the description does not compensate for the missing schema descriptions.

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

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

The description uses a specific verb ('List') and resource ('current plans') and enumerates the fields returned (prices, limits, seats, modules, checkout mode). It is clear about the tool's function, but it does not differentiate it from sibling tools like get_offer or compare_offers, which could overlap in purpose.

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?

There is no guidance on when to use this tool versus alternatives. With siblings such as compare_offers and get_offer, an agent gets no explicit direction about which tool fits which scenario, leaving usage entirely to inference.

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

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

The annotations already signal read-only and idempotent behavior, so the description does not need to restate that. It adds value by warning that the use cases are illustrative and must not be presented as actual customer outcomes or performance claims, which is meaningful behavioral context beyond the schema and 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?

One sentence with no filler. The core action and the critical qualifier are front-loaded and every word 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?

For a simple listing tool with an output schema, optional locale parameter, and safety annotations, the description covers the main behavioral caveat. The only real gap is explicit usage guidance, which is minor given how self-explanatory the tool is.

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 single optional locale parameter has no description in the schema, and the tool description does not mention it at all. The enum and default provide some semantic information, but with 0% schema description coverage, the description should have compensated and did not.

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 identifies the action (list), the resource (illustrative use cases), and the key caveat: they are illustrative, not customer results or performance claims. This distinguishes it from performance-claim or ROI-related sibling tools even without naming one directly.

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?

There is no explicit guidance on when to choose this tool over siblings or when not to use it. The intended context is implied by the name and phrasing, but no alternatives or exclusion conditions are given.

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 carry readOnly=false and destructiveHint=true, so the description is not the only source of behavioral context. It usefully adds that no contract is created and no charge is incurred, but it does not reveal what actually happens when the proposal is requested (e.g., whether an email is sent, a record is created, or something is overwritten), which is relevant given openWorldHint and destructiveHint.

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 one tight sentence plus a caveat, with no wasted words. The most distinctive facts are front-loaded, and the negative boundary is stated immediately.

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 an action tool with destructive and open-world hints, four parameters, and many sibling commercial tools, this description is too thin. The output schema may cover return values, but the description still leaves unclear when to choose this over checkout/trial options, why an idempotency key is needed, and what side effects occur.

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 needs to compensate for the parameters. The phrase 'email-verified' gives some clue about the email parameter, but idempotencyKey, locale, and companyName are not explained at all, and the role of idempotencyKey is important for correct invocation.

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 names a specific action ('Request') and a specific resource ('email-verified Enterprise proposal'), and adds a decisive boundary ('does not create a contract or charge'). This makes the tool's purpose clear even among many sibling commercial tools.

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?

There is no explicit guidance on when to use this tool instead of siblings such as dp_commercial_start_checkout, dp_commercial_start_live_trial, or dp_commercial_get_offer. The no-contract/no-charge caveat is a behavioral clarification, not a routing rule, and prerequisites or selection criteria are left implied at best.

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

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

The description adds operational context beyond the annotations: a human must verify the email and complete any payment. Since annotations already declare destructiveHint=true and readOnly=false, the description doesn't need to repeat those; it usefully warns about the manual step.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences front-load the purpose and include the critical caveat. Every sentence earns its place with no repetition 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?

It is adequate for tool selection: domain, alternative, and human step are clear. It is less complete for invocation because it leaves parameter semantics unterunched in spite of 7 parameters and 0% schema coverage, though parameter names and enums give some hints.

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%, and the description doesn't explain the required parameters planId, market, currency, or idemPotencyKey. It mentions email and payment loosely, but provides almost no guidance on how to populate the schema fields.

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

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

The description states a clear purpose: compatibility checkout for paid plans and Enterprise proposals. It also names the sibling alternative (dp_commercial_start_live_trial) for evaluation, which distinguishes it from other start_* tools.

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 says to use dp_commercial_start_live_trial for evaluation, giving an alternative for a different scenario. It also sets expectations that a human must verify email and handle payment, clarifying when this tool is appropriate.

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

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

The description adds substantial behavioral context beyond the annotations: supervised write access, human approval for sensitive actions, passwordless email verification, session establishment, provisioning resumption, and the statusToken handling warning. This is genuinely useful operational detail for an agent invoking the 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?

Four dense sentences with no filler. The core trial limits are front-loaded, followed by critical security and session behavior. Every sentence adds information an agent needs.

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 operational behavior and security well, and an output schema exists for return values. However, with eight parameters and very low schema coverage, the lack of guidance on several input fields and the absence of usage alternatives leave meaningful gaps for 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?

Schema description coverage is only 13%, so the description must compensate for undocumented parameters. It adds meaning for email (identity verification, portal session) and implies idempotencyKey behavior, but runtime, channels, projectUrl, projectName, company, and locale remain unexplained in both the schema and description.

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 a specific verb and resource: start a 14-day DigitalPublic trial, with concrete limits (three projects, 2,000 units, five tools). It does not explicitly contrast itself with sibling tools such as dp_commercial_start_checkout or dp_commercial_get_live_trial_status, so it falls short of full 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 intended use is implied: call this when you need to start a real trial. However, there are no explicit when-to-use, when-not-to-use, or alternative tool references, so the agent must infer selection from the verb and resource rather than being guided toward the correct sibling.

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