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 lists actions like 'clear_session' and 'set_dry_run', implying mutation capabilities, but doesn't detail permissions, side effects, or response formats. For a tool with multiple actions including destructive ones (e.g., clear_session), 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 efficiently structured with a brief purpose statement followed by a bulleted list of actions, making it easy to scan. Every sentence earns its place by clarifying the tool's scope. Minor improvement could be made by front-loading more critical information, but it's well-organized.

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 with 6 actions including mutations (e.g., clear_session, configure), no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, return values, and error handling, which are crucial for safe and effective use in a Kubernetes audit context.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds value by mapping parameters to actions (e.g., 'enabled' for set_dry_run, 'requireConfirmation' for configure), but doesn't provide additional syntax or format details beyond what the schema specifies. 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 tool's purpose as managing audit logging and safety controls with specific actions listed. It distinguishes itself from sibling tools like k8s_configmaps or k8s_pods by focusing on audit functionality rather than Kubernetes resource management. However, it doesn't explicitly contrast with all siblings, keeping it from 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 implies usage through the action list (e.g., 'get_status' for checking status, 'configure' for updating settings), but it lacks explicit guidance on when to use this tool versus alternatives like k8s_events for event monitoring or general context for audit needs. 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 full burden and does well by disclosing key behavioral traits: it specifies that update and delete actions require confirm=true or dryRun=true, indicating safety mechanisms for destructive operations. However, it doesn't cover other important aspects like authentication needs, rate limits, or error handling.

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

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

The description is efficiently structured with a brief introductory phrase followed by a bulleted list of actions with specific constraints. Every sentence earns its place, and the information is front-loaded with the most critical details about destructive action requirements.

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 complex tool with 6 parameters, no annotations, and no output schema, the description provides adequate but incomplete context. It covers the main actions and safety constraints but lacks information about return values, error conditions, authentication requirements, and how it differs from sibling tools managing other Kubernetes resources.

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

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

Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds minimal value beyond the schema by mentioning that name is 'required for most actions except list' and data is 'required for create/update', but these are already implied in the schema. Baseline 3 is appropriate when schema does 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 manages Kubernetes ConfigMaps with specific actions (list, get, create, update, delete), providing a verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like k8s_secrets or k8s_deployments, which likely manage different Kubernetes resources.

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 through the action parameter but doesn't provide explicit guidance on when to use this tool versus alternatives like k8s_secrets or k8s_deployments. It mentions prerequisites for update/delete actions (confirm=true or dryRun=true), which offers some contextual guidance but not comprehensive 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 of behavioral disclosure and does so effectively. It clearly identifies destructive actions (scale, restart) and their safety requirements (confirm=true or dryRun=true), mentions the 'rolling restart' behavior, and distinguishes between read-only (list, get, get_status, get_metrics) and mutating operations. It doesn't cover rate limits or authentication needs, but provides substantial 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 perfectly structured and concise: a clear purpose statement followed by a bulleted list of actions with brief, action-specific notes. Every sentence earns its place, with no redundant information. The front-loaded structure immediately communicates the tool's scope.

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 multi-action tool with 6 parameters, no annotations, and no output schema, the description provides excellent coverage of operations, parameter dependencies, and safety requirements. The main gap is the lack of output format information (what gets returned for each action), but given the complexity and absence of output schema, this is a minor omission in an otherwise comprehensive description.

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

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

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds some value by clarifying parameter dependencies (e.g., 'name required for most actions except list', 'replicas required for scale action'), but doesn't provide significant additional semantic meaning beyond what's in the schema descriptions. This meets the baseline expectation.

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 as 'Manage Kubernetes deployments' and enumerates six specific actions (list, get, scale, restart, get_status, get_metrics), providing a comprehensive verb+resource breakdown. It distinguishes itself from sibling tools like k8s_pods or k8s_services by focusing specifically on deployments.

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 usage context by specifying which actions require certain parameters (e.g., 'name required for most actions except list') and when confirm/dryRun are needed for destructive actions. However, it doesn't explicitly state when to choose this tool over alternatives like k8s_pods for pod-level operations or provide exclusion criteria.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description mentions actions but doesn't disclose critical behavioral traits: whether this is a read-only operation, if it requires specific permissions, rate limits, pagination behavior, or what the output format looks like. For a Kubernetes tool with no annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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 main purpose. The bullet-point structure for actions is efficient and easy to scan. However, the first sentence could be more specific (e.g., 'Retrieve and filter Kubernetes cluster events'), and some redundancy exists between the description and schema (e.g., action explanations). Overall, it's concise with minimal waste.

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 (6 parameters, no annotations, no output schema), the description is incomplete. It lacks information on behavioral aspects like safety, permissions, and output format, which are crucial for a Kubernetes events tool. Without annotations or an output schema, the description should compensate more by explaining return values or operational constraints, but it doesn't.

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

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

Schema description coverage is 100%, so the schema already documents all six parameters thoroughly. The description adds minimal value beyond the schema: it lists the three action values and hints at their purposes (e.g., 'get_resource: Get events for a specific resource'), but doesn't provide additional syntax, format details, or examples. This 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 tool's purpose: 'Get Kubernetes cluster events' with three specific actions. It uses a specific verb ('Get') and resource ('Kubernetes cluster events'), but doesn't explicitly distinguish this from sibling tools like k8s_audit or k8s_metrics, which might also retrieve cluster information. The description is clear about what the tool does but lacks sibling differentiation.

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 implied usage guidance by listing three actions with brief explanations (e.g., 'list: Get cluster events with optional filtering'). However, it doesn't explicitly state when to use this tool versus alternatives like k8s_audit (which might handle audit logs) or provide clear exclusions. The guidance is helpful but not comprehensive about 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions what metrics are retrieved (CPU/Memory), it lacks critical information such as whether this requires specific permissions, how metrics are formatted or aggregated, if there are rate limits, or what the response structure looks like. For a tool that likely interacts with a Kubernetes metrics API, 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 efficiently structured with a clear main purpose followed by bullet points for actions. It avoids unnecessary words, though the bullet points could be more integrated into a single sentence. Every sentence earns its place by specifying the resource types and actions.

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 Kubernetes metrics retrieval, no annotations, and no output schema, the description is incomplete. It doesn't explain return values, error conditions, authentication needs, or how metrics are scoped (e.g., current vs historical). For a tool with 4 parameters and likely nuanced behavior, this is inadequate.

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

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

Schema description coverage is 100%, so the schema already documents all four parameters with their types and descriptions. The description adds minimal value by listing the two action options, but doesn't provide additional context like how namespace/podName interact for pod metrics or what happens when optional parameters are omitted. Baseline 3 is appropriate given 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: 'Get Kubernetes resource metrics (CPU/Memory)' with specific actions for pods and nodes. It uses a clear verb ('Get') and resource ('Kubernetes resource metrics'), but doesn't explicitly differentiate from sibling tools like k8s_pods or k8s_nodes which might also retrieve information about those resources.

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 implied usage guidance by listing two specific actions (get_pod_metrics and get_node_metrics), suggesting when to use each based on the resource type. However, it doesn't explicitly state when to use this tool versus alternatives like k8s_pods for non-metric information, nor does it mention 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 does well by specifying that delete requires confirmation or dry-run, indicating a destructive operation. However, it lacks details on permissions needed, rate limits, error handling, or what 'details' include for get actions, leaving gaps for a mutation-capable tool.

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 uses a bulleted list for actions, making it highly scannable and efficient. Every sentence earns its place by clarifying action specifics without redundancy, resulting in zero waste in communication.

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, mutation capabilities) and lack of annotations or output schema, the description is adequate but incomplete. It covers basic actions and delete safeguards but misses details on return values, error responses, or broader behavioral traits like idempotency, which are important for a Kubernetes management 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%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by mentioning that name is 'required for get, create, delete' and clarifying delete conditions, but it doesn't provide additional semantic context like format examples or edge cases. This 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 tool's purpose with specific verbs ('Manage Kubernetes namespaces') and lists four distinct actions (list, get, create, delete). It distinguishes itself from sibling tools like k8s_pods or k8s_services by focusing exclusively on namespace operations, making the scope unambiguous.

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

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

The description provides clear context for when to use each action (e.g., 'get details of a specific namespace') and includes prerequisites for delete actions (confirm or dryRun). However, it doesn't explicitly state when to choose this tool over alternatives like k8s_configmaps for resource management, leaving some sibling differentiation implicit rather than explicit.

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 does well by specifying safety requirements for the delete action and mentioning log filtering capabilities. However, it misses critical details like authentication needs, rate limits, error handling, or what the tool returns (especially since there's no output schema). The description provides some behavioral context but leaves significant gaps for a multi-action tool.

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 brief introductory phrase followed by a bulleted list of actions, each with just enough detail. Every sentence earns its place by clarifying action purposes or constraints (e.g., the confirm/dryRun requirement for delete). It's front-loaded with the tool's scope and avoids 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?

Given the tool's complexity (14 parameters, 6 actions) and lack of both annotations and output schema, the description is moderately complete. It covers the action spectrum and key constraints but falls short on behavioral details like return formats, error cases, or prerequisites. For a multi-action Kubernetes tool with no structured safety or output information, it should provide more comprehensive guidance to fully compensate.

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

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

Schema description coverage is 100%, so the schema already documents all 14 parameters thoroughly. The description adds minimal parameter semantics beyond the schema—it mentions 'optional label selector' for list and 'filtering (severity, grep, time-based)' for get_logs, but doesn't provide additional syntax, format, or interaction details. This meets the baseline 3 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 tool's purpose as 'Manage Kubernetes pods' and enumerates six specific actions (list, get, delete, get_logs, get_status, summarize_logs), providing a comprehensive verb+resource scope. It effectively distinguishes this pod-focused tool from sibling tools like k8s_deployments or k8s_services, which target different Kubernetes resources.

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 specific actions (e.g., 'list: List pods in a namespace with optional label selector'), and includes important constraints like 'delete: Delete a pod (requires confirm=true or dryRun=true)'. However, it lacks explicit guidance on when to choose this tool over sibling tools (e.g., k8s_deployments for deployment-level operations) or broader usage scenarios beyond the action 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?

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: metadata-only retrieval for 'get', confirmation requirements for destructive actions (update/delete), and dry-run capabilities. It doesn't cover rate limits, authentication needs, or error behaviors, but provides substantial 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 efficiently structured with a clear headline followed by bullet points for each action. Every sentence earns its place by providing essential operational information without redundancy. The formatting makes it easy to scan and understand.

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 complex tool with 7 parameters, no annotations, and no output schema, the description provides substantial context about actions and their requirements. It covers the main use cases and safety mechanisms (confirm/dryRun) but doesn't explain return values or error conditions, which would be helpful given the absence of 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%, so the baseline is 3. The description adds some value by clarifying parameter usage in context (e.g., 'name required for most actions except list', 'data required for create/update'), but doesn't significantly expand beyond what the schema already documents.

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 as 'Manage Kubernetes Secrets' with specific actions listed (list, get, create, update, delete). It distinguishes from sibling tools by focusing specifically on Secrets rather than other Kubernetes resources like configmaps, deployments, or pods.

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 usage context by listing specific actions and their purposes, but doesn't explicitly state when to use this tool versus alternatives like k8s_configmaps or other sibling tools. It does differentiate actions within the tool (e.g., list vs get) but lacks cross-tool comparison 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 only lists action types without describing what 'manage' entails (read-only vs. mutations), authentication requirements, error conditions, rate limits, or response formats. For a Kubernetes management tool with zero annotation coverage, this leaves significant behavioral gaps.

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 concise with a clear bulleted list structure. The opening statement establishes scope, and each bullet corresponds to an action enum value. No wasted words, though it could be slightly more front-loaded with the most critical 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 no annotations and no output schema, the description is incomplete for a Kubernetes management tool. It doesn't explain what 'manage' means (read vs. write operations), doesn't describe return values or error handling, and provides minimal behavioral context. For a tool with 3 parameters and complex Kubernetes operations, this leaves too many gaps.

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

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

Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds no parameter semantics beyond what's in the schema - it doesn't explain namespace defaults, name requirements for specific actions, or action-specific behaviors. 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's purpose as 'Manage Kubernetes services' and enumerates three specific actions (list, get, get_endpoints). It distinguishes itself from sibling tools by focusing on services rather than other Kubernetes resources like pods or deployments. However, it doesn't explicitly differentiate from potential overlapping tools (though none are listed among siblings).

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 when to use list vs. get, when get_endpoints is appropriate, or how this tool relates to sibling Kubernetes tools. The description is purely functional without contextual usage advice.

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