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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, covering safety and scope. The description adds value by specifying the analysis outputs (scores, strengths, weaknesses, compatible technologies), but doesn't disclose additional behavioral traits like rate limits, authentication needs, or what '6-dimension scores' entail.

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 front-loads the core purpose and lists key outputs without unnecessary words. Every element (analysis, scores, strengths, weaknesses, compatible technologies) earns its place by clarifying 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 tool has annotations covering safety and scope, and schema coverage is 100%, the description adequately explains what the tool does. However, without an output schema, the description could better detail the return format (e.g., structure of '6-dimension scores'), and it lacks usage context compared to siblings.

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 well-documented in the schema. The description doesn't add any meaning beyond what the schema provides about 'technology' and 'context', so it meets the baseline for high schema coverage without compensating with extra details.

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 performs 'Detailed analysis of a technology' with specific outputs (6-dimension scores, strengths, weaknesses, compatible technologies), providing a specific verb+resource. However, it doesn't explicitly differentiate from sibling tools like 'compare_techs' or 'list_technologies', 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 'compare_techs' or 'recommend_stack', nor does it mention prerequisites or exclusions. The context parameter hints at different use cases but isn't explained in the description itself.

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

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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the agent knows this is a safe, closed-world read operation. The description adds useful context about the output format ('per-dimension winners and compatibility matrix'), but doesn't disclose behavioral traits like rate limits, authentication needs, or what 'closed-world' means in practice beyond what annotations provide.

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 front-loads the core functionality and includes key constraints (2-4 technologies) and output details. Every word earns its place with zero waste 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?

For a read-only comparison tool with good annotations and full schema coverage, the description is adequate but has gaps. It explains the output format but doesn't clarify how 'winners' are determined or what dimensions are compared. Without an output schema, more detail about return values would be helpful, though annotations cover the safety profile sufficiently.

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 fully documents both parameters (technologies array with constraints, context enum). The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain what 'per-dimension winners' means in relation to parameters or provide examples of technology names. Baseline 3 is appropriate when 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 tool performs a 'side-by-side comparison of 2-4 technologies' with specific outputs ('per-dimension winners and compatibility matrix'), which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'analyze_tech' or 'recommend_stack', which might have overlapping functionality.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'analyze_tech' or 'recommend_stack'. It mentions the 2-4 technology constraint and context parameter, but doesn't explain when this comparison is appropriate versus other analysis or recommendation tools in the sibling list.

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

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

The description adds significant behavioral context beyond annotations: it discloses the asynchronous nature of blueprint generation, the default synchronous waiting behavior, the option for manual polling, and authentication requirements. Annotations only indicate it's not read-only, not open-world, and not destructive, so the description provides crucial 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 efficiently structured: the first sentence states the core purpose, followed by key behavioral details, then practical examples. Every sentence serves a distinct purpose without redundancy, 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 tool's complexity (asynchronous creation with configurable waiting), lack of output schema, and rich annotations, the description is complete. It covers purpose, behavior, authentication, usage patterns, and examples, providing all necessary context for an agent to invoke it 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?

With 100% schema description coverage, the baseline is 3. The description adds value through concrete usage examples that illustrate how parameters like projectType, scale, and priorities combine in real scenarios (e.g., 'SaaS MVP' or 'enterprise API'), providing semantic context beyond the schema's technical definitions.

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 ('Creates a new tech stack blueprint') and resource ('for a project'), distinguishing it from siblings like get_blueprint (read) or analyze_tech (analysis). 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 clear context about when to use this tool (creating blueprints) and mentions prerequisites (API key with 'blueprint:write' scope). However, it doesn't explicitly contrast with alternatives like recommend_stack or compare_techs, which prevents a perfect score.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, covering safety and scope. The description adds value by specifying the API key requirement and that blueprints are generated via the web UI, but doesn't disclose additional behavioral traits like rate limits, error handling, or response format. No contradiction with annotations exists.

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 front-loaded with the core purpose in the first sentence, followed by two additional sentences that add context. It's appropriately sized with no redundant information, though it could be slightly more structured for optimal 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?

Given the tool's simplicity (1 parameter, no output schema) and rich annotations, the description is adequate but lacks details on the return value or error conditions. It covers the basics but doesn't fully compensate for the absence of an output schema, leaving gaps in understanding the tool's full behavior.

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, with the single parameter 'blueprintId' documented as a 'Blueprint UUID'. The description doesn't add any parameter-specific details beyond what the schema provides, such as format examples or validation rules, 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 ('fetches') and resource ('an existing blueprint by ID'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_technologies' or 'create_blueprint', which would require a more specific scope statement to earn a 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 implies usage by mentioning 'blueprints are generated via the StacksFinder web UI' and 'requires API key', providing some context. However, it lacks explicit guidance on when to use this tool versus alternatives like 'list_technologies' or 'create_blueprint', and doesn't specify prerequisites beyond the API key.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, covering safety and scope. The description adds valuable context by specifying the prerequisite ('Requires a configured API key'), which is not captured in annotations, enhancing transparency about authentication needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core purpose followed by a prerequisite. Every word earns its place, with no redundancy or unnecessary elaboration, making it highly efficient and well-structured.

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 (0 parameters, no output schema) and rich annotations, the description is mostly complete. It covers purpose and prerequisites, but lacks details on return values (e.g., format of listed keys) and behavioral aspects like pagination or rate limits, which could be useful despite the annotations.

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 parameters and 100% schema description coverage, the baseline is 4 as there are no parameters to document. The description does not need to add parameter details, and it appropriately focuses on the tool's purpose and prerequisites instead.

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 ('Lists') and resource ('your StacksFinder API keys'), distinguishing it from siblings like 'revoke_api_key' (destructive) and 'setup_api_key' (creation). It precisely defines the tool's scope 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 clear context by stating 'Requires a configured API key,' indicating a prerequisite for use. However, it does not explicitly mention when to use this tool versus alternatives like 'setup_api_key' or 'revoke_api_key,' nor does it specify exclusions, leaving some guidance implicit.

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

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

Annotations already provide readOnlyHint=true, openWorldHint=false, and destructiveHint=false, covering safety and scope. The description adds valuable context beyond this: it clarifies that the output is 'technology IDs' (not full technology details) and that these IDs are 'valid' and 'for use with other tools,' which helps the agent understand the tool's role in a workflow. No contradiction with 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 concise sentences that are front-loaded with the core purpose. Every word earns its place: the first sentence states what it does, and the second explains why it's important, with no redundant or vague phrasing.

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 (one optional parameter), rich annotations, and 100% schema coverage, the description is mostly complete. It clarifies the output format ('technology IDs') and their purpose, though it doesn't detail the return structure (e.g., list format), which is a minor gap since there's no output schema. For a simple list tool, this is sufficient.

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, with the single parameter 'category' fully documented in the schema (including enum values and description). The description does not add any parameter-specific information beyond what the schema provides, so it meets the baseline of 3 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 tool's purpose with a specific verb ('Lists') and resource ('all available technology IDs'), and explicitly distinguishes it from siblings by noting it's 'for use with other tools' and 'essential for discovering valid technology identifiers.' This differentiates it from analysis, comparison, or recommendation tools in the sibling list.

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: 'for use with other tools' and 'essential for discovering valid technology identifiers.' It implies an alternative approach (not using this tool) would lack valid IDs, and it distinguishes usage from siblings like analyze_tech or recommend_stack by focusing on ID discovery rather than analysis or recommendation.

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

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

Annotations declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, indicating a safe, non-destructive read operation with limited scope. The description adds value by specifying 'real-time scoring with context adjustments,' which suggests dynamic behavior beyond a simple lookup, and notes the API key requirement, addressing authentication needs. However, it doesn't detail rate limits, output format, or other behavioral traits, so it partially compensates for the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise and front-loaded: it states the core purpose in the first clause and adds a critical prerequisite in the second. Every sentence earns its place with no wasted words, making it efficient and easy to parse for an agent.

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 (4 parameters, real-time scoring) and lack of output schema, the description is somewhat incomplete. It covers the basic purpose and authentication need but doesn't explain the return values, scoring methodology, or how context adjustments work. With annotations providing safety context, it's minimally adequate but leaves gaps for a recommendation 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?

Schema description coverage is 100%, with all parameters well-documented in the schema (e.g., projectType, scale, priorities, constraints). The description doesn't add any parameter-specific semantics beyond what's in the schema, such as explaining how 'constraints' affect recommendations. Given the high coverage, a baseline score of 3 is appropriate, as the schema handles 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 tool's purpose: 'Recommends the best tech stack for a project using real-time scoring with context adjustments.' It specifies the verb ('recommends'), resource ('tech stack'), and method ('real-time scoring with context adjustments'), but doesn't explicitly differentiate from siblings like 'analyze_tech' or 'compare_techs', which likely serve different purposes. This makes it clear but not fully sibling-aware.

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 minimal usage guidance: it only states 'Requires API key' as a prerequisite. There's no explicit guidance on when to use this tool versus alternatives like 'recommend_stack_demo' or other siblings, nor any context on exclusions or specific scenarios. This leaves the agent with little direction on tool selection.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, covering safety and scope. The description adds useful context about the 'once per day' rate limit and 'no account required' authentication aspect, which aren't in the annotations. However, it doesn't describe output format or error behavior. With annotations providing core safety info, a 3 is appropriate as the description adds some behavioral 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 efficiently structured in two sentences: the first covers purpose and limitations, the second contrasts with Pro features. Every sentence adds value without redundancy, making it appropriately sized 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 (2 parameters with enums), annotations covering safety, and no output schema, the description is mostly complete. It explains the tool's purpose, usage limits, and upgrade path. However, it lacks details on the return format (e.g., structure of recommendations), 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?

Schema description coverage is 100%, with both parameters having clear enum-based descriptions. The description doesn't add any parameter-specific information beyond what the schema provides (e.g., how projectType and scale affect recommendations). Since the schema fully documents parameters, the baseline score of 3 is applied.

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 provides 'tech stack recommendations' and returns 'optimal technology for each category based on deterministic scoring,' which specifies the verb (recommend) and resource (technology stacks). However, it doesn't explicitly differentiate from sibling tools like 'recommend_stack' or 'analyze_tech,' which appears to be a similar recommendation tool without the demo limitation.

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 'once per day, no account required' and contrasts this with 'unlimited access, priorities, constraints, and AI-generated narratives' available via a Pro upgrade. This provides clear when-to-use guidance (free, limited use) and when-not-to-use (when more features are needed), with an alternative (upgrading to Pro) 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?

Annotations already indicate destructiveHint=true, so the agent knows this is a destructive operation. The description adds valuable context by explicitly stating 'This action cannot be undone,' reinforcing the irreversible nature beyond the annotation. It does not contradict annotations, as 'revokes' aligns with destructiveHint=true and readOnlyHint=false.

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—two short sentences that are front-loaded with the core action and followed by a critical warning. Every word earns its place, with no redundancy or unnecessary 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 (a destructive, irreversible action with one parameter) and the presence of annotations (destructiveHint=true), the description is mostly complete. It covers the irreversible nature, but without an output schema, it does not explain return values or potential errors, leaving a minor 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?

The input schema has 100% description coverage, with the 'keyId' parameter fully documented as 'The UUID of the API key to revoke.' The description does not add any further meaning or details about the parameter 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 ('revokes') and the resource ('an API key'), making the purpose specific and unambiguous. It distinguishes this tool from sibling tools like 'list_api_keys' or 'setup_api_key' by focusing on revocation rather than listing 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 clear context by stating 'This action cannot be undone,' which implies when to use it—specifically, for irreversible revocation. However, it does not explicitly mention when not to use it or name alternatives, such as using 'list_api_keys' first to verify the key ID.

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

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

Annotations already indicate this is a non-destructive write operation (readOnlyHint: false, destructiveHint: false). The description adds valuable behavioral context beyond annotations: it discloses that the key is returned only once and should be saved securely, which are critical implementation details not captured in structured fields.

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 front-loaded with the core purpose and efficiently conveys essential information in just two sentences. Every sentence earns its place: the first explains the action and prerequisites, while the second provides critical behavioral guidance about key security.

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 that creates credentials with no output schema, the description is reasonably complete. It covers the purpose, prerequisites, and key behavioral aspects (one-time return, security). However, it could mention what happens on failure (e.g., invalid credentials) or the format of the returned key, which would enhance completeness.

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 fully documents all three parameters (email, password, keyName). The description doesn't add any parameter-specific semantics beyond what the schema provides, such as explaining the format of keyName or authentication requirements. Baseline 3 is appropriate when the schema handles 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 specific action ('Authenticates... and creates an API key') and resource ('your StacksFinder account'), distinguishing it from sibling tools like list_api_keys or revoke_api_key. It goes beyond just restating the name/title by explaining the authentication and key creation process.

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 for when to use this tool ('Requires Pro or Team tier'), which helps differentiate it from alternatives. However, it doesn't explicitly state when NOT to use it (e.g., if you already have an API key) or name specific alternatives like list_api_keys for checking existing keys.

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