mcp adoraads ai/beauty

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

No annotations exist, and the description fails to disclose any behavioral traits such as read-only nature, data retrieval scope, or side effects. The single sentence provides no operational insight.

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 brief (two short statements) and avoids redundancy. However, the conciseness comes at the cost of completeness, making it minimally acceptable.

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, no output schema, and zero schema coverage, the description is grossly insufficient. Important usage context like parameter formats, return contents, and authentication needs are entirely 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?

With 0% schema description coverage and no parameter explanations in the description, the meaning of 'context', 'tenant_id', and 'brand_query' is entirely opaque. The description adds no value over the schema structure.

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' which identifies the action and resource. While it doesn't explicitly differentiate from siblings, the name and verb provide adequate clarity.

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 a mandatory disclosure instruction is given. No guidance on when to use this tool versus alternatives like 'sponsored_search' or the other siblings. The agent is left without contextual usage boundaries.

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?

No annotations provided, so the description carries full burden. It only mentions firing a billing event; no information on side effects, idempotency, required permissions, or error handling.

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?

Extremely concise but at the cost of omitting critical details. A useful description should balance brevity with 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?

Given three parameters, no annotations, and no output schema, the description provides almost no contextual information. It fails to help an agent select or invoke the 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?

Schema description coverage is 0%, and the description does not explain the meaning of any parameter. Token, event_type, and order_value are left entirely implicit.

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 fires a billing event when acting on a sponsored result. It uses a specific verb and resource but does not differentiate from sibling tools like sponsored_search.

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 on when to use this tool versus alternatives or when not to use it. The description implies a specific context but lacks explicit usage rules.

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?

No annotations are provided, so the description must cover behavioral traits. It only implies a read operation ('Get') but does not disclose side effects, auth needs, or rate limits. The minimal description adds little beyond the 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 sentence, which is concise and front-loaded. However, it is overly brief, sacrificing important details for brevity.

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 no output schema, no annotations, and two undocumented required parameters, the description is inadequate. It does not explain the response format, preconditions, or behavioral expectations, leaving significant 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?

Schema description coverage is 0%, and the description does not mention or explain the parameters (tenant_id, shopper_id). It adds no meaning beyond the schema, leaving the agent without guidance on parameter usage.

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 'Get' and the resource 'shopper ad preferences', and it distinguishes from siblings by mentioning 'before running sponsored_search'. However, it does not elaborate on what exactly the preferences are.

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 context by stating 'before running sponsored_search', implying a prerequisite check. But it does not give when-not-to-use or alternative tools, which would improve 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?

With no annotations provided, the description carries the burden. It discloses the sponsorship context and the mandatory disclosure of sponsored steps, which is a behavioral constraint. However, it lacks details on side effects (e.g., whether it creates a permanent record, updates user data) or any auth/rate limit 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?

The description is very concise, with two sentences: the first states the purpose, the second adds a critical requirement. It front-loads the key action. No wasted words, though it could benefit from slightly more 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 5 parameters, no output schema, and no annotations, the description is insufficient. It does not explain what the routine building entails, how sponsorship is integrated, or what the return value looks like. The sponsorship disclosure requirement is valuable but does not fill the gap 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 description coverage is 0%, meaning the description adds no information about the five parameters. It does not explain concerns, skin_type, tenant_id, budget_usd, or routine_type beyond what the schema already states. The description fails to compensate for the lack of parameter documentation.

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, specifying the verb and resource. It distinguishes from sibling tools like brand_spotlight or skin_match by focusing on routine creation with sponsorship, though it could be more explicit about what a routine entails beyond the schema enums.

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 procedural requirement ('REQUIRED: Disclose sponsored steps individually') but does not give guidance on when to use this tool versus alternatives like brand_spotlight or sponsored_search. No explicit exclusions or context for selection among siblings.

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?

No annotations provided, so description must carry transparency burden. It mentions building a profile and returning products, but discloses no side effects, data handling, or privacy implications beyond the confirmation requirement.

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, with a clear action and a critical requirement. Efficient but could be improved by integrating parameter details without significant expansion.

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?

Missing output schema and behavioral context. The description does not specify the return format, pagination, or what happens if no products match, leaving the agent underinformed for a tool with 4 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 coverage is 0% with no property descriptions. The description does not explain parameters like 'avoid' or 'goals', leaving the agent uncertain about their expected values and 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?

Description clearly states the tool builds an AI skin profile and returns matched sponsored products, with a specific verb and resource that distinguishes it from sibling tools 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?

The description includes a strong requirement ('Confirm profile with shopper before showing products'), but lacks guidance on when to use versus alternatives, and no exclusion criteria.

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?

With no annotations provided, the description bears full responsibility for behavioral disclosure. It notes that the tool 'Returns ranked results with billing tokens,' but lacks details on whether the tool is read-only, destructive, or has auth/rate limit requirements. No explanation of side effects or return format beyond billing tokens.

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—two sentences that are front-loaded with purpose. The first sentence states the core function, and the second adds a critical usage instruction. While it sacrifices detail, it respects the conciseness principle by not including extraneous information.

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

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

Given the tool's complexity (8 parameters, no output schema, no annotations), the description is grossly incomplete. It fails to explain the meaning of key parameters (e.g., tenant_id, budget_usd), the structure of the ranked results, or the conditions under which billing tokens are generated. The description does not equip an agent to invoke the 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?

Schema description coverage is 0%, meaning no parameter descriptions exist in the schema. The tool has 8 parameters, including required fields like query and tenant_id, and optional ones like budget_usd and max_results. The description does not explain any parameter, leaving the agent to infer their meaning from names alone. This severely hinders correct usage.

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

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

The description clearly states the tool's purpose: 'Search for sponsored beauty products.' It specifies the domain (beauty products), the nature (sponsored), and mentions return content (ranked results with billing tokens). The required labeling instruction further clarifies the output expectation. This effectively distinguishes it from sibling tools like brand_spotlight or skin_match.

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 one usage requirement: 'Always label results as Sponsored.' However, it offers no guidance on when to use this tool versus alternatives (e.g., organic search, brand-specific tools). There are no explicit when/when-not statements or context-based recommendations.

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