NameIntel

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

No annotations are provided, so the description must carry full behavioral disclosure. It only states the tool checks availability and pricing, omitting details like rate limits, authentication needs, side effects, or how unavailability is handled. The behavioral traits are underdescribed.

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 with no wasted words. It front-loads the primary action and scope, making it efficient and easy to parse.

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

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

Given the sibling context, the description distinguishes adequately. However, it lacks detail on the output format (e.g., how availability and pricing are returned), and there is no output schema to compensate. The description is minimally adequate but not fully complete.

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

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

Schema description coverage is 100%, with both parameters having clear descriptions. The tool description adds the context 'for a brand name' but does not significantly enhance the meaning beyond the schema. Baseline 3 is appropriate given the high 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 action (check), resource (domain availability and pricing), and scope (multiple TLDs for a brand name). It effectively distinguishes from sibling tools like check_geo, check_social, and check_trademark by using the keyword 'domain'.

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 checking domain availability and pricing but provides no explicit guidance on when to use this tool versus alternatives, nor when not to use it. The sibling names are distinct, so inference is possible, but no direct guidance is given.

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

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

No annotations are provided, so the description carries full burden. It lists assessment criteria but does not disclose behavioral traits such as whether the operation is read-only, data sources, rate limits, or side effects. This is insufficient for a tool without 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, front-loaded with the main action, and lists the four assessment aspects concisely. No unnecessary words or redundancy.

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

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

Despite having one parameter and no output schema, the description does not explain what the output looks like (e.g., a score, report, or feedback). The four aspects are listed but their output format is omitted, leaving the agent without critical return value 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 100% for the single parameter 'name'. The description adds 'brand name' context but does not provide additional semantics like format restrictions, examples, or expected values beyond what the schema already states.

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 'Evaluate' and resource 'brand name' for a specific context (AI findability/GEO score). It lists four distinct aspects assessed, which distinguishes it from sibling tools like check_domain or check_social.

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 evaluating brand names for AI findability but does not explicitly state when to use this tool over siblings like check_domain or check_trademark. No exclusions or alternative suggestions are provided.

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

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

With no annotations, the description bears full responsibility for behavioral disclosure. It does not explain what 'check' entails (e.g., network calls, rate limits, or result format). There is no mention of safety or side effects, which is critical for a tool contacting external services.

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 (10 words) and front-loaded. Every word is meaningful, with no redundancy. For a simple tool, this is optimal.

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 low complexity, the description lacks essential context. There is no output schema, so the agent needs to know the return format (e.g., per-platform availability status). The tool's behavior with invalid handles or network errors is unaddressed, 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?

The description adds context beyond the input schema: it specifies the scope 'across 12 platforms' and implies default behavior for the optional 'platforms' parameter. This helps the agent understand the scale and optionality, adding value to the schema descriptions.

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

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

The description clearly states the tool's function: checking social media handle availability across 12 platforms. The verb 'check' and resource 'social media handle availability' are specific. Sibling tools like 'check_domain' and 'check_trademark' cover different resources, so this is well-differentiated.

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. No conditions or exclusions are mentioned. The description simply states what it does without 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 carries the burden. Describes output but does not disclose any behavioral traits such as rate limits, data freshness, or whether results are real-time. Lacks depth beyond basic functionality.

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?

Single sentence that is front-loaded with the action ('Search USPTO trademark database'). No redundant words; each phrase adds value.

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 search tool with two parameters and no output schema, the description adequately covers what the tool does and returns. No obvious gaps in information needed for selection.

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 100%, both parameters have descriptions. The description adds no extra meaning beyond the schema (e.g., 'Nice class information' is already implied). Baseline score 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?

Clearly states the tool searches the USPTO trademark database for conflicts, specifically for a brand name, and enumerates return items (exact matches, similar marks, risk level, Nice class). This distinguishes it from siblings like check_domain which searches domain databases.

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?

Implied usage for trademark conflict checking, but no explicit guidance on when to use versus alternatives (e.g., check_domain) or prerequisites. Does not state when not to use.

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 carries full burden. It discloses the output structure (composite score 0-100 with sub-scores and verdict) and lists the five dimensions, but does not detail behavioral aspects such as external calls, latency, or computational cost. The transparency is adequate but not exhaustive.

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 highly concise: two sentences that front-load the action and output. Every word adds value without redundancy, making it easy to parse quickly.

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

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

Given the tool's complexity (multi-dimensional scoring, 2 parameters, no output schema), the description adequately covers purpose and return format. However, it lacks specifics on the verdict meaning or data structure of sub-scores, which would improve completeness. The presence of sibling tools mitigates this 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 100%, so the schema already documents both parameters. The description adds no extra meaning beyond listing the five dimensions (which are not parameter-specific). The baseline score of 3 is appropriate as the description does not enhance parameter understanding.

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

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

The description clearly states the tool's function: scoring a brand name across five specific dimensions (domain, trademark, social, SEO, AI findability). It explicitly distinguishes from sibling tools (individual checks) by offering a composite score, making the 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 implicitly suggests using this tool for a holistic evaluation and siblings for individual checks, but it lacks explicit when-to-use or when-not-to-use guidance. No alternative tools or exclusions are mentioned, limiting proactive decision-making.

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