mcp adoraads ai/beauty

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

The description adds a key behavioral constraint (disclosure requirement) beyond the readOnlyHint annotation. It does not detail return format or side effects, but the disclosure is critical for compliance.

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 very short (one sentence plus a note) and front-loaded with the core action. It could benefit from a brief structure but is 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 3 parameters and no output schema or parameter descriptions, the description leaves out essential details like how to use parameters and what the response contains. It is incomplete 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?

No explanation of parameters in the description, and schema coverage is 0%. The description does not add meaning to 'brand_query', 'tenant_id', or 'context' parameters.

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

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

The description clearly states 'Get sponsored brand content' with a verb and resource. However, it does not differentiate from sibling tool 'sponsored_search', which might have overlapping functionality.

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

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

Only provides a disclosure requirement ('REQUIRED: Disclose as Sponsored Brand Content') but gives no guidance on when to use this tool vs alternatives like sponsored_search or when to avoid it.

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

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

The idempotentHint annotation provides safety insight, but the description adds little behavioral context beyond 'fire billing event'. No mention of side effects, permissions, or irreversible actions, but annotations already 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 extremely concise (one sentence), but lacks necessary detail for effective use. It is not overly wordy, but brevity comes at the cost of completeness.

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 3 parameters and no output schema, the description is insufficient. It does not explain what constitutes a billing event, how parameters relate, or what the tool returns.

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 explanation of parameters (token, event_type, order_value). The enum for event_type is not elaborated, leaving agents with only parameter names and types.

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 action (fire billing event) and the context (when acting on a sponsored result). It distinguishes from siblings like sponsored_search by focusing on billing, but lacks explicit 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?

No explicit guidance on when to use or not use this tool vs. alternatives. The description only implies usage when acting on a sponsored result, but does not mention prerequisites or exclusions.

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

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

Annotations already declare readOnlyHint: true, so the description adds minimal behavioral detail. It mentions that the tool retrieves 'shopper ad preferences,' which is consistent but does not elaborate on 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, which is concise, but it fails to include necessary parameter explanations. It is underspecified for a tool with two required parameters and no schema descriptions.

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 two required parameters and no output schema, the description should provide more detail about the expected input format and the nature of the returned preferences. It omits critical information for an agent to use effectively.

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 explain the parameters. However, it provides no details about 'shopper_id' or 'tenant_id,' leaving the agent without guidance on what values to provide or how they affect the result.

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?

Clearly states it gets shopper ad preferences, with a specific verb ('Get') and resource ('shopper ad preferences'). It also distinguishes from siblings by noting it should be used before 'sponsored_search', implying a prerequisite relationship.

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 clear usage context by stating 'before running sponsored_search,' which indicates when to use this tool. Does not explicitly mention when not to use it or alternatives, but the context is sufficient for an agent to infer usage.

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

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

The description says 'Build' implying creation, but annotations set readOnlyHint=true, a direct contradiction. No behavioral traits beyond this are disclosed, such as side effects or authorization needs.

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 very concise at two sentences, with the tool's purpose front-loaded in the first sentence. No unnecessary words, but it sacrifices important detail.

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

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

Given the tool has 5 parameters with no schema descriptions, no output schema, and a contradiction with annotations, the description is severely incomplete. It lacks return value info, parameter guidance, and clarifies the sponsored aspect.

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 adds no meaning to any of the 5 parameters (e.g., concerns, skin_type, budget). The only related text is 'sponsored' and 'disclose', which are not parameter-specific.

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 builds a sponsored skincare routine, which is a specific action on a resource distinct from sibling tools like brand_spotlight or sponsored_search. However, it lacks detail on what 'building' entails (e.g., generating steps).

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 mentions 'sponsored' and a disclosure requirement, hinting at a usage context, but provides no explicit guidance on when to use this tool versus alternatives like sponsored_search or brand_spotlight, nor any conditions 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 provide readOnlyHint: true, and the description is consistent with that (building a profile and returning products is read-only). The description adds the requirement to confirm with shopper, which is behavioral context, but does not disclose other traits like idempotency or side effects beyond 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 two sentences: the first states the purpose, and the second provides a critical requirement. No redundant information, perfectly front-loaded and efficient.

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?

While the main action and a key requirement are clear, the description lacks details on return values (no output schema), parameter guidance, and error conditions. An agent would struggle to invoke this tool correctly without additional 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?

Schema description coverage is 0%, and the description fails to explain any of the four parameters (skin_description, tenant_id, goals, avoid). It mentions 'skin profile' but does not clarify what each parameter does, leaving the agent without necessary semantic information.

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 builds an AI skin profile and returns matched sponsored products, using specific verbs and resources. It distinguishes from sibling tools like routine_builder or sponsored_search, though it could be more precise about what 'build AI skin profile' entails.

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 includes a critical usage requirement: 'REQUIRED: Confirm profile with shopper before showing products.' This provides clear when-to-use guidance, though it doesn't explicitly state when not to use or list alternatives.

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?

Adds disclosure requirement and mentions returned data (billing tokens, disclosure labels) beyond the readOnlyHint annotation. Does not contradict annotations. Could detail rate limits or auth but adequate.

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 sentences covering purpose, return value, and essential usage requirements. Well front-loaded, but could be tightened slightly by reducing repetition of 'ALWAYS'. Still efficient.

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?

No output schema and 8 undocumented parameters. Description only mentions 'ranked sponsored results with billing tokens and disclosure labels', omitting details on output structure, parameter usage, pagination, or error handling. Incomplete for a tool of this complexity.

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

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

Schema has 8 parameters with 0% description coverage. The description does not explain any parameter, leaving the agent to guess meanings of 'concern', 'skin_type', 'budget_usd', etc. Fails to compensate for absent 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?

Clearly states it searches for sponsored beauty products matching a shopper query and returns ranked results with billing tokens and disclosure labels. Distinguishes itself from siblings like brand_spotlight or routine_builder.

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 explicit mandatory usage: always use this tool first for any beauty product recommendation, and always show the disclosure field. This is strong guidance on when and how to invoke the tool.

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