commercial

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safe, non-mutating nature. The description adds no further behavioral context, such as how the plan is generated or whether it depends on live data. While it does not contradict annotations, it does not enrich the behavioral picture beyond the bare purpose.

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 directly states the action and lists the input factors. Every word is purposeful, and there is no wasted or redundant information.

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

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

The tool has 6 optional parameters, no output schema, and minimal descriptionization. The description fails to explain what the recommended plan looks like, how outputs are returned, or what the defaults imply. This incompleteness is notable given the absence of an output schema and the moderate complexity of the input set.

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, but the description paraphrases most parameter names (e.g., 'project count', 'team size', 'live-data need'). However, it does not add true semantic meaning, such as units, constraints, or how these factors influence the recommendation. It also omits the 'locale' parameter entirely, leaving the agent with limited understanding of input semantics.

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

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

The description uses a specific verb 'Recommend' and names the resource 'a plan', clearly indicating the tool's function of recommending a plan based on several input factors. This distinguishes it from sibling tools that compare offers or estimate ROI, as it focuses on suitability recommendation.

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 does not provide any guidance on when to use this tool versus alternatives. It merely states what the tool does without specifying scenarios, prerequisites, or comparing to other tools like get_offer or compare_offers. This leaves the agent without explicit direction on selection.

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 the description does not need to restate safety. It adds valuable context about the scope and dimensions of the comparison (setup, governance, cross-channel work, tradeoffs) and emphasizes 'objective,' which clarifies expected behavior. No contradictions 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?

The description is a single, efficient sentence that front-loads the primary purpose ('Provide an objective comparison') and then lists the key comparison dimensions. No unnecessary words or repetition; it is perfectly concise.

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 comparison tool with no output schema, the description explains what is compared and the main axes of comparison, which covers the core use case. The main gap is the lack of detail on the output format or how the locale parameter affects results, but given the tool's simplicity and strong annotations, the description is sufficiently 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?

The schema fully defines the single parameter 'locale' with an enum and default, making it self-explanatory. However, the description provides no additional meaning or purpose for the parameter beyond what the schema already offers, and schema_description_coverage is 0%. Given the simplicity and clarity of the schema, a baseline score of 3 is appropriate.

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

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

The description clearly identifies the tool's purpose: to provide an objective comparison between direct provider MCP servers and DigitalPublic, with specific comparison dimensions (setup, governance, cross-channel work, tradeoffs). This distinguishes it from sibling tools like compare_offers or assess_fit.

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 establishes a clear context for use (when a comparison between direct integrations and DigitalPublic is needed), but does not explicitly state when to use this tool over alternatives or provide exclusion criteria. It implies a decision-support scenario but leaves the agent to infer the exact differentiation from 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 readOnly and idempotent safety. The description adds that the comparison uses the canonical catalog, providing context about the data source. However, it does not disclose return format or other behavioral 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?

The description is a single, clear sentence that front-loads the action and object, with no unnecessary words.

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

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

For a read-only comparison tool with a simple parameter, the description is adequate but lacks information about the output format or what the comparison results contain. The lack of an output schema increases the need for such details.

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

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

The schema has one parameter (planIds) with 0% description coverage. The description clarifies that the parameter refers to plans and requires at least two, but does not explain the format or where plan IDs come from.

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

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

The description clearly states the tool's function: comparing two or more plans using the canonical catalog. It distinguishes itself from sibling tools like compare_integration_options by specifically targeting 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 the tool is for comparing multiple plans, but does not explicitly state when to use it over alternatives or provide exclusions. The 'two or more' phrasing hints at use cases with multiple plans.

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 safety is covered. The description adds a small behavioral detail by stating the explanation is 'for humans and AI agents', which hints at output audience, but it doesn't disclose return format or other behaviors. This is consistent with annotations, adding minimal value.

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, front-loaded with the main action, and contains no filler. It is concise and easy to parse, earning full marks for efficiency.

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 output schema and minimal description, the tool's return value is unspecified. It doesn't describe what the explanation will contain (e.g., capabilities, use cases, architecture), making it incomplete for an agent that needs to know what to expect. The low complexity partially mitigates this, but the lack of return details is a significant 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%, so the description must compensate. It does not mention the 'locale' parameter at all. While the parameter is simple (enum es/en, default es), the description fails to explain its purpose or effect, leaving the agent to rely solely 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 uses a specific verb ('explain') and resource ('DigitalPublic'), clearly stating the tool's function. It distinguishes from sibling tools which are action-oriented (e.g., get offers, compare options) by focusing on a general platform overview, though it doesn't explicitly call out the 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?

There is no guidance on when to use this tool versus alternatives. The description does not mention any context or exclusions, leaving the agent to infer that this is for introductory platform information, but without explicit direction.

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 no need to restate those. The description adds valuable behavioral context by clarifying that the tool is purely a calculator and will not forecast sales or ad performance, which is consistent with the read-only annotation and provides extra insight beyond it.

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 the main action 'Calculate only...' front-loaded. Every word earns its place, and the exclusion is stated in a single efficient second sentence.

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 calculator with 4 parameters and read-only/idempotent annotations, the description adequately covers purpose, scope, exclusions, and implied outputs (net value, break-even hours). It does not specify the formula or output structure, but given the tool's simplicity and the annotations covering safety, it is sufficiently 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%, and the description does not explicitly map parameters like hoursSavedPerMonth, hourlyCost, planId, and currency. It mentions 'time savings' and 'plan cost' which hint at some parameters, but it does not explain how plan cost is derived or the meaning of currency, and the names alone are only partially self-explanatory.

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 the specific verb 'calculate' and clearly lists the inputs/outputs: time savings, plan cost, net value, and break-even hours. It also explicitly states what it does not do ('never forecasts sales or advertising performance'), which distinguishes it from sibling tools that may predict business outcomes.

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

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

The description provides clear context by stating 'only' time-value ROI and explicitly excluding sales/advertising forecasts, so the agent knows when this tool is appropriate. However, it does not name specific alternative tools or say 'use instead of X', so it falls short of full alternative guidance.

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

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is known. The description adds content scope (types of capabilities) but no additional behavioral traits such as return format, pagination, or error conditions. This matches the baseline for a read-only tool 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?

The description is a single, focused sentence that front-loads the action and resource. Every word adds value, with no 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?

For a simple tool with one optional parameter and no output schema, the description adequately explains what is returned. It could be slightly more explicit about the 'explicit qualifications' phrase, but overall it is complete enough for an agent to invoke 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?

Schema description coverage is 0%, but there is only one optional parameter (locale) with a clear enum and default in the schema. The description does not mention or add meaning to this parameter, yet the schema alone makes it self-explanatory, so the description is not required to compensate heavily.

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 identifies the resource ('capability matrix'), enumerating the types of capabilities included. This clearly distinguishes it from sibling tools, none of which mention capability matrices.

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 the many sibling get/list tools. It does not mention contexts, alternatives, or exclusions, leaving the agent to infer applicability.

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 the agent knows it is a safe, repeatable read operation. The description adds the specific services being checked, which is useful context, but it does not disclose any additional behavioral traits such as data freshness, permission requirements, or response structure beyond what is already implied.

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, concise sentence that is front-loaded with the action ('Report whether') and immediately states the three readiness areas. There is zero 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?

For a simple, parameterless, read-only status check, the description fully captures the tool's purpose and output (availability of three specific onboarding paths). The output schema is absent, but the description's implied result (booleans for each service) is sufficient for this simple tool.

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

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

The tool has zero parameters, and the schema coverage is trivially 100%. The description does not need to explain parameters. It clearly states what the tool reports, which is sufficient for a no-parameter tool.

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

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

The description uses the specific verb 'Report' and clearly states the resource ('checkout readiness') with the exact scope: Sandbox, self-service checkout, and Enterprise proposal onboarding. This distinguishes it from sibling tools like dp_commercial_get_checkout_status, which likely reports on a specific checkout session rather than overall readiness.

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

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

No explicit guidance on when to use this tool versus alternatives. It does not name any sibling tools or provide context such as 'use before starting checkout'. The description only states what it does, leaving usage implicit from the tool name and the listed readiness areas.

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 the safety profile. The description adds valuable behavioral context by specifying that only 'non-sensitive status' is returned, which is a meaningful trait beyond the annotations. It also clarifies the covered request types.

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

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

The description is a single, well-structured sentence that is front-loaded with the core action and scope. Every word adds value, with no 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 output schema and a terse description, the agent does not know the structure of the returned status or how to interpret it. The description is adequate for a simple read-only tool, but it lacks details about response format and does not address potential errors. Given the simple parameter set and annotations, this is minimally 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?

The input schema has one required parameter 'intentId' with no description (schema coverage 0%). The tool description fails to explain the meaning or format of 'intentId', leaving the agent to infer from the name alone. Since the description carries the full burden for parameter understanding, this is a significant 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 clearly states the tool's function: 'Return the non-sensitive status of a Sandbox, checkout, or proposal request.' It uses a specific verb (return) and resource (status of specific request types), which distinguishes it from sibling tools like get_service_status or get_checkout_readiness.

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 is used to check the status of a checkout/sandbox/proposal, but it does not explicitly explain when to choose it over related siblings (e.g., get_checkout_readiness, get_service_status) or provide exclusions. Usage context is implied rather than clearly 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 safety is covered. The description adds contextual detail about the returned content (verified legal identity, corporate contacts, evidence URLs), going slightly beyond what annotations provide. It does not reveal localization nuances, but the read-only nature is already established.

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, concise sentence that immediately states the tool's purpose and key outputs. No filler or redundancy, making it easy to parse and front-loaded.

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

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

Despite lacking an output schema, the description lists the main return elements, giving a clear expectation of the response. However, it omits the role of the 'locale' parameter, which limits completeness for a tool with optional localization. Overall, the low complexity makes the description mostly 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 documents the 'locale' parameter with enum values and a default, but the description provides no explanation of how 'locale' affects the output. With schema_description_coverage at 0%, the description was expected to compensate, yet it omits any reference to the parameter, leaving its semantics ambiguous.

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 the specific verb 'Return' and names the exact resources: 'verified legal identity, corporate contacts, and evidence URLs for DigitalPublic.' This clearly distinguishes the tool from siblings like dp_commercial_get_offer or dp_commercial_get_security_profile, which target different data.

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 its use case through the tool name and content, but it does not explicitly state when to use it over alternatives or provide exclusions. It lacks comparative guidance such as 'use this instead of get_offer for legal entity details,' so the 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description doesn't need to restate safety. It adds value by disclosing the specific content areas (authentication modes, scopes, human prerequisites, review state, known limitations). This goes beyond annotations by clarifying what information is exposed, though it doesn't mention any potential side-effects or additional behaviors.

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 is front-loaded with the main purpose, concise, and contains no filler. Every word contributes meaning, covering both the scope and content of the 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?

For a one-parameter, read-only informational tool with strong annotations, the description fully covers what is needed. It explains the key aspects of what the tool returns without requiring an output schema, and it is clear enough for an agent to select and invoke 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?

Schema coverage is 0%, so the description must compensate. It indicates the connectorKey refers to a specific DigitalPublic connector ('for one DigitalPublic connector'), but it does not explicitly define the parameter's format, where to find it, or any constraints beyond the schema's minLength. Since there is only one obvious parameter, this partial compensation is adequate but not fully explicit.

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 clearly identifies the resource: 'connection requirements for one DigitalPublic connector'. It enumerates the exact aspects covered (authentication modes, scopes, human prerequisites, review state, known limitations), which distinguishes 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 usage when one needs connection requirements for a specific connector, but it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions. There is no mention of a sibling tool like get_security_profile that might overlap, so guidance is only 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 mark the tool as read-only and idempotent, so the description's 'Explain' is consistent. It adds useful context beyond annotations by specifying the exact topics covered, including references to subprocessor evidence URLs, giving the agent a clearer picture of the tool's informational output without risking contradiction.

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 front-loads the main verb and resource, followed by a compact list of specific topics. It contains no filler or redundant wording, earning every character.

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

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

For a read-only informational tool with no output schema, the description gives a thorough list of content areas and hints at return values (evidence URLs). It could be slightly more explicit about the output format, but the level of detail is sufficient for the agent to understand what it will receive.

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 coverage is 0%, but the single `locale` parameter is well-defined by its enum (es/en) and default value, making its purpose self-evident. The description does not mention the parameter, but this is a minor omission given the schema's clarity, so a baseline score is appropriate.

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

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

The description uses a specific verb 'Explain' and resource 'data processing profile', then details distinct content areas (controller/processor roles, AI training policy, DPA, subprocessors) that clearly differentiate it from sibling tools like get_security_profile or get_company_profile. The resource and topic list make the tool's purpose unambiguous.

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 guidance is provided on when to use this tool versus alternatives such as get_security_profile or get_company_profile. The description only lists what it explains, leaving the agent to infer applicability without explicit exclusions or comparisons.

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's addition of 'current' provides a small behavioral nuance (that plans may not all be current). However, it does not elaborate on return format, error behavior, or other operational details, so it remains at a baseline level.

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 redundancy or filler, making it very concise 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?

For a simple get-by-id tool with one parameter and no output schema, the description sufficiently conveys the core action. It doesn't need to explain return values since no output schema exists, and the tool's simplicity reduces the need for extensive 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 schema has 0% description coverage for planId, and the description only says 'by id', which minimally clarifies that the parameter is an identifier. It does not explain what a planId looks like, its format, or its meaning beyond being an ID, leaving significant semantic 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 'Return one current plan by id' clearly states the verb (return), resource (plan), and scope (one current plan by id), which distinguishes it from sibling tools like list_offers (all plans) and compare_offers (comparison).

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 you have a specific plan id, but it does not explicitly state when to use this tool versus alternatives such as list_offers or compare_offers. No exclusions or prerequisites are mentioned.

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 that the report is synthetic and contains no customer data, which is valuable behavioral context. It also aligns with the annotations, with no contradiction.

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 of eight words, front-loaded with the action ('Return') and devoid of filler. It is maximally concise.

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

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

Given the tool's simplicity (zero parameters, read-only, idempotent), the description sufficiently conveys the purpose and key characteristic (synthetic, no customer data). However, it does not specify the structure or format of the sample report, which could be important for an agent expecting a particular output type, though no output schema is provided.

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 accepts no parameters, so the schema is empty and the description correctly omits parameter details. The baseline of 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?

The description clearly states the tool returns a synthetic report sample, using the verb 'return' and specifying the resource ('synthetic report sample') and its scope ('without customer data'). This distinguishes it from sibling tools like get_offer or get_company_profile, which deal with actual data.

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 obtaining a sample report, but it does not explicitly state when to use it over alternatives or mention exclusions. There are no sibling tools with similar functionality, so the context is somewhat inherent, but the guidance is not explicit.

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 the safety profile. The description adds substantive behavioral context by enumerating the topics the explanation covers (isolation, scopes, approvals, token revocation, audit controls), which sets expectations about the content returned. No contradictions 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?

The description is a single clear sentence that front-loads the key content topics. Every word earns its place, and there is no redundancy or filler. It is appropriately sized for a simple no-parameter information 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?

Given the tool's low complexity, no parameters, and helpful annotations, the description is complete. It clearly specifies the scope of the explanation and needs no additional details about return values or behavior. The listed topics give the agent a precise understanding of what information this 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?

The tool has zero parameters, so parameter semantics are trivially satisfied. The baseline of 4 for a no-parameter tool applies, and there is nothing more the description could add beyond what is already evident from the empty input 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's purpose: it explains specific security-related topics (project isolation, scopes, approvals, token revocation, audit controls). The verb 'Explain' combined with the resource 'security profile' makes the function specific and distinct from sibling tools like get_company_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 provides clear context about when to use the tool—when you need to understand the security profile aspects listed. It does not explicitly state when not to use it or name alternatives, but the topic list and tool name make the use case apparent. The absence of alternatives is acceptable given the tool's unique focus.

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, but the description adds useful behavioral context: it will not fabricate uptime history or SLA, and it returns a timestamp. This goes beyond the structured 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-structured sentence that front-loads the primary action and result. Every word earns its place, with no fluff 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 zero-parameter, read-only status tool, the description provides sufficient context: it states the output (component health and timestamp) and the key limitation (no invented history/SLA). Given the tool's simplicity, this is complete, though a bit more detail on what 'component health' includes could improve clarity.

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 no parameters, so the description does not need to explain any. The absence of parameters is clear from the schema, and the description appropriately focuses on the return value rather than input.

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 names the resource ('current component health and timestamp'), clearly distinguishing this from sibling tools like get_company_profile or get_checkout_status. It also explicitly scopes what is returned (current health and timestamp).

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 (to get current status) and explicitly states what it does not do ('without inventing uptime history or SLA'), which helps set expectations. However, it does not name alternative tools for historical status or SLA data.

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 safety profile is covered. The description adds the 'commercial V1' scope but provides no extra behavioral details such as data source, pagination, or response format. This is acceptable but not rich.

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

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

The description is a single, front-loaded sentence: 'List integrations included in commercial V1.' Every word contributes to purpose and scope, with no filler 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?

Given the tool's simplicity (no parameters, read-only annotations, no output schema), the description is largely sufficient. It could mention what 'integrations' refers to or the response shape, but for a simple list operation it is adequately 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?

The tool has zero parameters, and the schema is empty with 100% coverage. The description does not need to explain parameters, and the baseline for no-parameter tools is 4.

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

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

The description uses a specific verb 'List' with a clear resource 'integrations' and scopes it to 'commercial V1'. This clearly distinguishes it from sibling tools like list_offers and list_use_cases.

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. It only states what it lists, without mentioning exclusions, prerequisites, or related tools that might be more appropriate for other queries.

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 read-only nature is covered. The description adds value by detailing what the list will contain (prices in both currencies, limits, seats, modules, checkout mode), which provides useful behavioral context beyond the annotations. No contradictions.

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 is efficient and contains no filler. Every phrase adds meaningful information about the tool's output.

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 list tool with one optional parameter and no output schema, the description conveys the essential return content (plans with prices, limits, seats, modules, checkout mode). It is moderately complete, though it omits any explanation of the locale parameter and possible output format, which would slightly improve completeness.

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

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

Schema description coverage is 0%, and the description does not mention the 'locale' parameter at all. While the schema includes an enum and default, the agent is left without guidance on how locale affects results, and the description fails to compensate for the low schema coverage.

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

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

The description clearly states the verb 'List' and the resource 'current plans', enumerating specific attributes (EUR/USD prices, limits, seats, modules, checkout mode). This distinguishes it from sibling tools like get_offer (single offer) or compare_offers (comparison).

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 is for viewing all current plans, but it does not explicitly mention when to use it versus get_offer or compare_offers. No exclusions or alternative recommendations are provided, so the context is clear but the guidance is implicit.

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

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

Annotations already declare readOnlyHint and idempotentHint. The description adds valuable context that outputs must be clearly labeled as illustrative and not presented as customer results or performance claims, which prevents misinterpretation. This goes beyond the annotation information.

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, front-loaded with the verb 'List', and contains no extraneous information. It is concise and easy to scan.

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 list tool with strong annotations, the description covers the essential purpose and the key behavioral constraint. It does not describe the output format or locale parameter, but these are largely self-evident given the schema and the nature of the 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 fully defined by the schema with an enum and default, but the description does not mention it. With 0% schema description coverage, the description could have explained the parameter, but its absence is acceptable given the simplicity and self-explanatory nature of the enum.

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

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

The description clearly states the verb and resource: 'List clearly labeled illustrative use cases'. This distinguishes it from sibling tools like list_offers and list_integrations by specifically targeting use cases. The title reinforces the 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?

Usage is implied by the name and description: it's for listing illustrative use cases. However, no explicit guidance is given on when to use this tool versus alternatives like describe_platform or get_capability_matrix, and no alternative tools are mentioned.

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: false and destructiveHint: true, indicating this is a state-changing, potentially destructive operation. The description adds that no contract or charge is created, which is valuable, but it does not explain the email verification mechanism, other side effects, or the response behavior. With annotations present, the description adds some context but leaves significant unknowns.

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 short sentences with no filler. The first sentence front-loads the action and target, while the second adds a crucial clarification. Every clause contributes meaning, making it exemplary in conciseness and structure.

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 4 parameters, no output schema, and a rich set of sibling tools, the description is too sparse. It does not specify prerequisites (e.g., email verification), the outcome of the proposal request, or the role of idempotencyKey. The agent is left without essential context to confidently invoke the tool in the correct scenario.

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 parameter understanding. The only hint is 'email-verified', which partially explains the email parameter, but there is no explanation for idempotencyKey, locale, or companyName. The agent cannot understand the purpose or constraints of three out of four parameters from the 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 the tool requests an 'email-verified Enterprise proposal' and distinguishes it from similar actions by clarifying it does not create a contract or charge. This separates it from sibling tools like dp_commercial_start_checkout, making its specific purpose unambiguous.

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 for non-binding enterprise proposals via the explicit 'does not create a contract or charge' clause, giving clear context for when to use this tool instead of a purchase/completion action. However, it does not explicitly name alternatives or state conditions when not to use it, so it lacks the full 'when/when-not' guidance found in top examples.

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?

It discloses that a human must verify the email and authorize payment, which is critical behavioral context beyond the annotations. However, it doesn't elaborate on idempotency or side effects, though annotations cover those.

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

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

Two sentences, front-loaded with the action, and every word earns its place. No 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?

Given the tool's complexity (7 params, no output schema, multiple request types), the description covers the core purpose and the human approval step, but lacks details on request lifecycle, return value, or how idempotencyKey is used. It's minimally 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 description doesn't explain any of the seven input parameters. With 0% schema description coverage, the description fails to add meaning to fields like planId, market, or idempotencyKey, leaving the agent to rely solely on schema enums.

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 opens with the verb 'Create' and specifies the resource: email-verified Sandbox, self-service checkout, or Enterprise proposal request. This clearly states the tool's function and distinguishes it from read-only or assessment 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 implies the tool is for starting a checkout/proposal process, but doesn't explicitly state when to use it over siblings like dp_commercial_start_sandbox or dp_commercial_request_proposal, nor does it provide exclusions or alternatives. The context is clear but under-specified.

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 (readOnlyHint=false, idempotentHint=true), the description adds that the sandbox is synthetic and read-only once created, and that human email verification is a required gate before access is provisioned. It does not contradict annotations, though it could add more about idempotency or failure behavior.

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

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

The description is two sentences, front-loaded with the core action and followed by a single essential behavioral note. There is no filler or repetition of schema information.

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

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

The description provides a clear purpose and the key prerequisite of email verification, but with no output schema and zero parameter explanations, it leaves important invocation details about idempotencyKey, locale, and companyName unexplained. It is minimally adequate but has clear gaps for a tool with four parameters.

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 provides no parameter-specific guidance. It mentions 'email-verified' but does not explain how the email parameter relates, nor does it clarify idempotencyKey, locale, or companyName. With four parameters and no schema descriptions, the description fails to compensate, leaving the agent uncertain about required inputs.

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 'Start' with a clear resource 'Sandbox enrollment', and adds qualifiers 'email-verified, synthetic, read-only' that distinguish it from sibling tools like start_checkout. It is immediately obvious this tool initiates a sandbox rather than a commercial checkout.

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 initiating sandbox access and explicitly states the prerequisite that a human must verify the email before access is created. It does not name alternatives or when-not-to-use scenarios, but the context is clear enough for an agent to select it appropriately among the sibling commercial tools.

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