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 effectively describes key constraints: the tool is for linking emails to accounts, it has specific preconditions (no existing email on account, email not already linked elsewhere), and it's rarely needed due to domain registration. However, it doesn't cover potential side effects, error conditions, or response formats, which leaves some behavioral aspects unclear.

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 well-structured and front-loaded with the core purpose, followed by important notes in bullet points. Every sentence adds value: the first explains the action and purpose, and the bullets provide critical constraints and context. There is no redundant or wasted text.

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 (account linking with constraints), no annotations, and no output schema, the description does a good job covering purpose, usage guidelines, and key constraints. However, it lacks details on what happens after linking (e.g., confirmation process, error responses) and doesn't mention authentication or rate limits, leaving some contextual 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 input schema has 0% description coverage, so the description must compensate. It implicitly clarifies that the 'email' parameter is the address to be linked to the account, adding meaningful context beyond the bare schema. However, it doesn't specify format requirements (e.g., valid email patterns) or provide examples, which could enhance usability further.

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 ('Links an email address') and the target resource ('to an AI agent's account'), with explicit purposes ('for web interface access and account recovery'). It distinguishes this tool from sibling tools like 'set_contact_information' or 'domains' by focusing on account-level email linking rather than general contact updates or domain management.

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 explicit guidance on when to use this tool ('Only accounts without an existing email can be linked') and when not to use it ('Each email can only be linked to one account', 'This method is rarely needed since emails are also set during domain registration'). It effectively distinguishes this from alternatives like domain registration processes, though it doesn't name specific sibling tools as 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?

With no annotations provided, the description carries full burden but only states the basic action. It doesn't disclose behavioral traits like authentication requirements, rate limits, error conditions, whether the operation is idempotent, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap.

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 appropriately sized and front-loaded with the core purpose in the first sentence. Each subsequent line adds necessary parameter details without redundancy. However, the parameter explanations could be slightly more structured (e.g., bullet points).

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 (mutation with 5 parameters), lack of annotations, and no output schema, the description is incomplete. It covers parameters well but misses critical behavioral context (e.g., permissions, side effects, response format), making it inadequate for safe agent invocation.

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 substantial meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose with examples (e.g., domain_id as UUID, type with record types, name as subdomain, value with IP examples, ttl with default). This fully compensates for the schema's lack of 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 creates a new DNS record for a domain, specifying both the action (create) and resource (DNS record). It distinguishes from siblings like delete_dns and update_dns by focusing on creation, but doesn't explicitly differentiate from other creation tools (none listed).

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 is provided. The description doesn't mention prerequisites (e.g., needing an existing domain), exclusions, or comparisons to sibling tools like update_dns or dns_records, leaving the agent to infer usage context.

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. While 'Delete' implies a destructive mutation, the description doesn't specify whether this action is reversible, requires specific permissions, has rate limits, or what happens upon success/failure. This is a significant gap for a mutation tool with zero annotation coverage.

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 appropriately sized and front-loaded, with the core purpose stated in the first sentence and parameter details following directly. Every sentence earns its place by providing essential information without redundancy or 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 complexity of a destructive operation with no annotations and no output schema, the description is incomplete. It lacks critical details such as the effect of deletion (e.g., permanent removal), error handling, or return values, which are necessary for safe and effective tool invocation.

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 meaningful context beyond the input schema, which has 0% description coverage. It explains that 'domain_id' is a 'Domain UUID' with an example format and 'record_id' is the 'DNS record ID to delete', clarifying their roles. However, it doesn't detail where to find these IDs or validation rules, leaving some ambiguity.

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 ('Delete') and resource ('a DNS record for a domain'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'update_dns' or 'create_dns', which would require mentioning this is specifically for removal rather than modification or creation.

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 'update_dns' and 'create_dns' available, there's no indication of prerequisites (e.g., needing an existing record), exclusions, or comparative context, leaving the agent to infer usage scenarios.

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 this is a 'Get' operation, implying read-only behavior, but doesn't mention critical aspects like authentication requirements, rate limits, error conditions, or whether it returns all records or requires pagination. 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 efficiently structured: the first sentence states the purpose, followed by a clear parameter explanation and a bulleted list of return fields. Every sentence earns its place without redundancy, making it easy to parse and front-loaded with essential 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 moderate complexity (1 parameter, no output schema, no annotations), the description is partially complete. It excels in explaining parameters and return values but lacks behavioral context (e.g., auth, errors) and usage guidelines relative to siblings. This makes it adequate but with clear gaps for reliable agent 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 description adds substantial value beyond the input schema, which has 0% description coverage. It explains the 'domain_id' parameter with a concrete example (UUID format) and details the structure of returned DNS records (id, type, name, value, ttl), compensating fully for the schema's lack of 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's purpose with a specific verb ('Get') and resource ('DNS records for a domain'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'domains' or 'search', which might also retrieve domain-related information, leaving some ambiguity about when to choose this specific tool.

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 'domains' (likely listing domains) and 'search' (potentially broader searches), there's no indication of context, prerequisites, or exclusions, leaving the agent to guess based on 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool as a read-only list operation (implied by 'List domains'), and it details the structure of returned domain objects, including fields like 'id', 'domain_name', and 'status'. This adds valuable context beyond basic functionality, though it doesn't cover aspects like error handling or authentication requirements explicitly.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by a bulleted list of return fields for clarity. Every sentence earns its place by providing essential information without redundancy or 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 low complexity (0 parameters, no output schema, no annotations), the description is quite complete. It explains what the tool does, who it applies to (authenticated user), and the structure of returned data. However, it could be slightly more complete by mentioning any limitations (e.g., pagination) or error cases, though this is minor for a simple list 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 input schema has 0 parameters with 100% coverage, so no parameter information is needed from the description. The description correctly focuses on output semantics by detailing the returned domain object fields, which compensates for the lack of an output schema. This adds significant value beyond the 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 verb ('List') and resource ('domains owned by the authenticated user'), making the purpose specific and unambiguous. It distinguishes this tool from siblings like 'search' or 'get_purchase_offers' by focusing on listing owned domains rather than searching or purchasing.

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 by specifying 'domains owned by the authenticated user,' which suggests this tool is for retrieving the user's own domains. However, it does not explicitly state when to use this tool versus alternatives like 'search' or provide any exclusions or prerequisites, leaving some guidance gaps.

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 states this is a retrieval operation, implying read-only behavior, but doesn't disclose any behavioral traits like authentication requirements, rate limits, error conditions, or what 'currently configured' means in terms of freshness/caching.

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 efficiently conveys the core purpose with zero waste. Front-loaded with the main action and resource, appropriately sized for a simple retrieval 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 parameterless retrieval tool with no annotations and no output schema, the description adequately states what it does but lacks context about return format, error handling, or relationship to sibling tools. It's minimally viable but has clear gaps in behavioral disclosure.

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 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately focuses on the tool's purpose without redundant parameter information, meeting the baseline for parameterless tools.

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 ('Retrieve') and resource ('currently configured contact information'), with specific purpose for 'domain purchases and ICANN registration'. It doesn't explicitly differentiate from sibling tools like 'set_contact_information', but the retrieval vs. setting distinction is implied.

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 contact information is needed for domain/ICANN purposes, but doesn't explicitly state when to use this vs. alternatives like 'set_contact_information' or other sibling tools. No guidance on prerequisites or exclusions is 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 provided, the description carries the full burden of behavioral disclosure. It effectively describes the return type (L402 offer), its structure, and how it can be processed ('by any tool supporting L402 offers'). It also includes important domain-specific constraints (.ai TLD requirements). However, it doesn't mention potential errors, rate limits, or authentication needs, leaving some behavioral aspects uncovered.

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 appropriately sized but not optimally structured. It front-loads the purpose but includes an extensive JSON example that could be summarized more concisely. The .ai TLD note is important but interrupts the flow. Some sentences could be tightened for better readability.

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 (domain purchasing with payment offers), no annotations, and no output schema, the description does a good job of explaining the return value structure and constraints. It covers the essential context needed to use the tool effectively, though additional information about error handling or authentication would make it more 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 description coverage is 0%, so the description must compensate. It clearly explains both parameters: 'sid' as 'Search ID from a previous search request' and 'domain' as 'Domain name to purchase from the search results related to `sid`'. This adds crucial semantic meaning beyond the bare schema, though it could provide more detail about format constraints or examples.

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 purpose: 'Request available payment options for a domain.' It specifies the verb ('request') and resource ('payment options for a domain'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'search' or 'domains' beyond mentioning domain purchase context.

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 context by mentioning that the domain should be 'from the search results related to `sid`' and includes a note about .ai domains requiring 2-year packages. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'search' or 'domains', nor does it specify prerequisites or exclusions beyond the sid and domain parameters.

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 effectively describes key behaviors: it returns search results with availability status, prices in USD cents, and a search ID needed for purchases. It also specifies query constraints (no subdomains, no spaces), which are crucial for correct usage.

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 well-structured and front-loaded: the first sentence states the purpose, the second details the return values, and the rest provides specific usage rules with clear examples. Every sentence adds value without redundancy, 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 tool's moderate complexity (1 parameter, no output schema, no annotations), the description is largely complete. It covers purpose, usage, behavioral traits, and parameter semantics thoroughly. However, it does not mention potential errors, rate limits, or authentication needs, leaving minor gaps in full contextual coverage.

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 0% description coverage, so the description fully compensates by adding rich semantic details about the 'q' parameter. It explains what constitutes valid queries (e.g., full domain names with or without TLD) and provides explicit examples of valid and invalid inputs, going far beyond the bare 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 with a specific verb ('Search') and resource ('available domains'), distinguishing it from siblings like 'domains' (likely a list tool) or 'get_purchase_offers' (related but different). It specifies what is being searched for and what is returned.

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 on when to use this tool (to search for domain availability) and includes explicit rules for valid/invalid queries. However, it does not explicitly state when to use alternatives like 'domains' or 'get_purchase_offers', missing full sibling differentiation.

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. It clearly indicates this is a write/mutation operation ('Set') with permanent effects (for domain registration). However, it doesn't disclose important behavioral traits like whether this requires specific permissions, if changes are reversible, what happens to existing contact information, or any rate limits/quotas.

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 efficiently structured with a clear purpose statement upfront, followed by prerequisite information, then a well-organized parameter explanation. Every sentence adds value with no redundant information. The bullet-style parameter listing is particularly effective for clarity.

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 mutation tool with 8 parameters and no annotations or output schema, the description does an excellent job explaining purpose, prerequisites, and parameter semantics. The main gap is lack of information about the return value or confirmation of success/failure, which would be helpful since there's no output schema.

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 0% description coverage (all parameters have generic titles like 'Cfn'), but the description provides comprehensive semantic mapping for all 8 parameters. It clearly explains what each parameter represents (e.g., 'first_name: First name', 'state: Two-letter state code...'), including format requirements and examples, fully compensating for the schema's deficiencies.

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 ('Set the contact information') and its purpose ('used for domain purchases and ICANN registration'). It distinguishes this from sibling tools like 'get_contact_information' by specifying it's a set/write operation rather than a read operation.

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 explicitly states when to use this tool ('must be set before attempting any domain purchases'), providing clear prerequisites. It also implies when not to use it (if contact information is already set or if only reading is needed, use 'get_contact_information' instead).

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 notes that 'Updating a record will change its record id,' which is a critical behavioral trait not obvious from the schema. However, it lacks other important details: whether this requires specific permissions, if changes are reversible, potential side effects on DNS resolution, or error handling for invalid inputs.

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 well-structured and appropriately sized. It starts with a clear purpose statement, includes a behavioral note upfront, and then lists parameters with explanations. Every sentence adds value, though the parameter explanations could be slightly more concise by avoiding redundancy in examples like 'e.g.,' repetitions.

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 annotations and no output schema, the description is moderately complete. It covers the tool's purpose and parameters well but lacks critical context: no output format details, no error conditions, no rate limits or authentication requirements, and minimal behavioral transparency beyond the record ID change note. For a mutation tool with 6 parameters, this leaves gaps in operational understanding.

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 successfully adds meaning for all 6 parameters by explaining each one's purpose with examples (e.g., 'domain_id: Domain UUID', 'type: DNS record type', 'ttl: Time To Live in seconds'). This goes beyond the schema's basic titles and provides essential context for proper 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 with a specific verb ('Update') and resource ('existing DNS record for a domain'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'create_dns' or 'delete_dns', which would require mentioning it modifies existing records rather than creating new ones or removing them.

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., needing an existing DNS record), contrast with 'create_dns' for new records or 'delete_dns' for removal, or specify any contextual constraints like domain ownership requirements.

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