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

With no annotations provided, the description carries full burden but only states the basic purpose. It doesn't disclose behavioral traits like whether this is a read-only operation (implied but not stated), rate limits, authentication requirements, network dependencies, or what happens with invalid names. The description is minimal and lacks operational context.

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 directly states the tool's purpose with zero wasted words. It is appropriately sized for a simple query tool and front-loads the core functionality without unnecessary elaboration.

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 single-parameter query tool with no annotations and no output schema, the description is adequate but minimal. It covers the basic purpose but lacks context about return values (e.g., boolean availability status, error responses) or integration with sibling tools like 'get-registration-price'. Given the low complexity, it meets minimum viability.

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 the parameter 'name' clearly documented in the schema. The description adds no additional parameter semantics beyond what the schema provides (e.g., no examples, format clarifications, or edge cases). Baseline 3 is appropriate when the schema does the heavy lifting.

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 specific action ('Check if... is available') and resource ('an ENS name'), with the verb 'check' precisely indicating a query operation. It distinguishes from siblings like 'get-registration-price' (price calculation) and 'resolve-name' (address lookup) by focusing on availability status.

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

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

The description implies usage when determining if an ENS name can be registered, but provides no explicit guidance on when to use this tool versus alternatives like 'get-registration-price' (which might be a logical next step) or 'resolve-name' (for existing names). 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves information (implying a read-only operation) but doesn't specify aspects like rate limits, authentication needs, error conditions, or what 'all available information' entails (e.g., format, depth). This leaves significant gaps for safe and effective use.

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, direct sentence with zero wasted words, front-loading the core purpose ('Get all available information for an ENS name'). It efficiently communicates the essential action and target without redundancy or fluff, making it easy for an agent to parse quickly.

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

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

Given the tool's simplicity (one parameter, read-only implied), no annotations, and no output schema, the description is minimally adequate but incomplete. It clarifies the purpose and parameter broadly but omits behavioral details and output expectations, which could hinder an agent's ability to use it correctly in complex scenarios.

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 description coverage is 100%, with the single parameter 'name' clearly documented as 'The ENS name to query'. The description adds no additional parameter details beyond this, such as format examples or constraints, but the schema adequately covers the basics, meeting the baseline for 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 ('Get all available information') and target resource ('for an ENS name'), making the purpose immediately understandable. It doesn't explicitly distinguish from siblings like 'get-text-record' or 'resolve-name', which might retrieve specific subsets of information rather than 'all available' data, but the scope is well-defined.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'get-text-record' or 'resolve-name' from the sibling list. It implies usage for comprehensive ENS name data but lacks explicit comparisons, prerequisites, or exclusions, leaving the agent to infer context from tool names alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves history but doesn't specify what 'history' entails (e.g., ownership changes, transaction logs, registration events), whether it requires authentication, rate limits, or the format of the returned data. This leaves significant gaps for an agent to understand the tool's 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 a single, clear sentence with no wasted words. It is front-loaded with the core purpose, making it easy to parse quickly. Every part of the sentence contributes directly to understanding the tool's function.

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 complexity of historical data retrieval and the lack of annotations and output schema, the description is insufficient. It doesn't explain what type of history is returned, potential errors, or how to interpret results. For a tool that likely involves nuanced data, more context is needed to guide an agent 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?

The schema description coverage is 100%, with the parameter 'name' clearly documented as 'The ENS name to check history for'. The description adds no additional meaning beyond this, as it doesn't elaborate on the format of the ENS name or provide examples. Given the high schema coverage, 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 states the action ('Get the history') and the resource ('of an ENS name'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings like 'get-all-records' or 'resolve-name', which might also involve historical or record-related queries about ENS names.

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

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get-all-records' and 'resolve-name', there's no indication of whether this tool is for transaction history, ownership changes, or other types of historical data, leaving the agent to guess based on the name alone.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but lacks critical behavioral details: it doesn't specify if this is a read-only operation (implied but not stated), whether it requires authentication, rate limits, network calls, or what the output format looks like (e.g., currency, units). For a tool with zero annotation coverage, this is a significant gap in transparency.

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 directly states the tool's purpose without any fluff. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place, achieving optimal conciseness for this simple 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 moderate complexity (price calculation for registrations), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects (e.g., read-only nature, potential errors), output details (e.g., price format), or usage context (e.g., when to call it relative to availability checks). For a tool with no structured safety or output information, more descriptive context is needed.

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 ('name' and 'duration') well-documented in the schema. The description adds no additional parameter semantics beyond what the schema provides (e.g., it doesn't explain format constraints like name length or validation rules). Baseline 3 is appropriate when the schema does the heavy lifting, but no extra value is added.

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 ('Get the price') and resource ('to register an ENS name'), making the purpose immediately understandable. It distinguishes from siblings like 'check-availability' (which checks name availability) or 'resolve-name' (which resolves addresses). However, it doesn't explicitly differentiate from all siblings (e.g., 'get-all-records' might also involve pricing data), keeping it at 4 rather than 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., name must be available), exclusions (e.g., invalid names), or relationships with siblings like 'check-availability' (which might be a prerequisite). Usage is implied but not explicitly stated, resulting in minimal 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 full burden for behavioral disclosure. It states what the tool does but doesn't describe how it behaves: no information on rate limits, authentication needs, error conditions, or what format the subdomains are returned in. For a query tool with zero annotation coverage, this leaves significant gaps in understanding the tool's operational characteristics.

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 states exactly what the tool does with zero wasted words. It's appropriately sized for a simple query tool and front-loads the core functionality immediately.

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

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

Given the lack of annotations and output schema, the description is incomplete for effective tool use. It doesn't explain what format the subdomains are returned in, whether there are pagination considerations, or what happens with invalid ENS names. For a query tool with no structured output documentation, the description should provide more context about the return values and error conditions.

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 description coverage is 100%, with the single parameter 'name' clearly documented as 'The ENS name to query for subdomains'. The description adds no additional parameter semantics beyond what's already in the schema. This meets the baseline of 3 when the schema does the heavy lifting, but earns no extra credit for enhancement.

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 resource 'subdomains for an ENS name', making the purpose immediately understandable. It distinguishes this from siblings like 'get-all-records' or 'resolve-name' by focusing specifically on subdomains. However, it doesn't specify whether this returns direct subdomains only or includes nested ones, which prevents a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'get-all-records' (which might include subdomain data) or 'resolve-name' (which resolves names to addresses). There's no mention of prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool 'gets' a text record, implying a read-only operation, but doesn't specify whether it requires authentication, has rate limits, returns errors for non-existent records, or provides any context about the ENS system. This leaves significant gaps for an agent to understand the tool's 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, 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 lack of annotations and output schema, the description is incomplete. It doesn't explain what a 'text record' entails in the ENS context, what format the return value might have, or any error conditions. For a tool interacting with a specialized system like ENS, more context is needed for effective use.

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 100% description coverage, clearly documenting both required parameters ('name' and 'key') with examples for 'key'. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline for high 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 action ('Get') and resource ('text record for an ENS name'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'get-all-records' or 'resolve-name', which might also retrieve ENS-related 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 provides no guidance on when to use this tool versus alternatives like 'get-all-records' (which might retrieve multiple records) or 'resolve-name' (which might resolve to an address). There's no mention of specific use cases, 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the basic operation but omits critical details such as error handling (e.g., for invalid names), rate limits, authentication requirements, or response format. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 a single, efficient sentence that directly states the tool's purpose with zero wasted words. It is front-loaded and appropriately sized for a simple tool, making it easy to parse and understand 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 lack of annotations and output schema, the description is incomplete. It covers the basic purpose but fails to address behavioral aspects like error cases or response structure, which are essential for a tool performing a resolution operation. This leaves the agent with insufficient context for reliable use.

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 description coverage is 100%, with the parameter 'name' fully documented in the schema (including an example). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 for adequate but not enhanced parameter 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 specific action ('resolve') and target resource ('ENS name to an Ethereum address'), distinguishing it from siblings like 'reverse-lookup' (which does the opposite) or 'get-name-history' (which provides historical data). It precisely communicates the tool's function without ambiguity.

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 converting ENS names to addresses but provides no explicit guidance on when to use this tool versus alternatives like 'reverse-lookup' (for address-to-name resolution) or 'check-availability' (for name status). It lacks context on prerequisites or exclusions, leaving usage decisions to inference.

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

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It doesn't disclose whether this is a read-only operation, if it requires authentication, rate limits, error conditions (e.g., unregistered addresses), or what happens on failure. The description is functional but lacks critical operational 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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core functionality and appropriately sized for a simple lookup operation. Every word earns its place.

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

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

For a simple lookup tool with one parameter and no output schema, the description is minimally adequate. However, without annotations or output information, it doesn't address what the tool returns (e.g., ENS name string, null for unregistered addresses) or error behavior. The description covers the basic 'what' but misses important contextual 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?

Schema description coverage is 100%, with the single parameter 'address' clearly documented in the schema. The description adds no additional semantic context beyond implying the parameter's purpose. This meets the baseline for high schema coverage, but doesn't enhance understanding of parameter usage or constraints.

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 specific action ('Get') and target resource ('ENS name for an Ethereum address'), distinguishing it from sibling tools like 'resolve-name' (which likely does the opposite) or 'get-name-history' (which provides historical data). It precisely communicates the tool's function without ambiguity.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., address format), exclusions (e.g., invalid addresses), or comparisons to siblings like 'resolve-name' (which might convert ENS names to addresses). Usage context is implied but not explicitly stated.

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