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

With no annotations provided, the description carries full burden. It tells the tool is read-only ('List'), which is good. However, it does not disclose other behavioral traits such as pagination, ordering, authentication needs, or whether it returns errors for RBAC issues. It is adequate but lacks completeness.

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 one sentence of eight words. Every word is meaningful: 'List' for action, 'all available' for scope, 'Kubernetes namespaces' for resource. No 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?

For a parameterless tool with no output schema, the description is succinct and covers the purpose and scope. It explains what the user will get (list of namespaces). It could be improved by mentioning if the list is filtered by the current kubeconfig context or if it includes all clusters, but given the simplicity, it is sufficiently 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 tool has zero parameters and schema description coverage is 100%, so the schema already defines the tool fully. The description adds value by confirming that no parameters are needed and that the output will contain all namespaces. Nothing more is needed from the description on parameters.

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 ('List'), the resource ('all available Kubernetes namespaces'), and differentiates from siblings like list_k8s_services which list services. It specifies scope ('all available') and resource type ('namespaces'), making the purpose unambiguous.

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

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

The description implies use when you need to see which namespaces exist in a cluster. However, it provides no guidance on when not to use it (e.g., if only specific namespaces are needed) and does not mention alternatives among siblings. It does not explain prerequisites or context like cluster access requirements.

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?

Given no annotations are provided, the description clearly indicates that this is a read-only operation (retrieving lists), which is the core behavioral trait. It does not explicitly state that it is non-destructive, but the language strongly implies it, and there are no contradictions. A minor point is the lack of mention about performance or rate limits, but the simplicity of the tool makes this less critical.

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 concise at two sentences, each providing distinct and valuable information: the first explains what it does, the second explains when to use it. It is front-loaded with the primary purpose. It could be slightly more polished by omitting 'all available' as implied, but it remains efficient.

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 (1 optional param, no output schema, no annotations), the description is sufficient for an agent to understand its purpose and how to use it in relation to siblings. It lacks explicit details about the return format, but the simplicity of the tool and the context that it returns 'grouped' lists mitigates this. For a read-only list tool, this is complete enough.

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%, meaning the schema itself documents the optional namespace filter. The description goes beyond the schema by stating it groups results by 'short name and environment', which adds useful semantic context about how the returned list is structured, aiding the agent in understanding what to expect.

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 uses a specific verb 'Retrieves' and clearly identifies the resource as 'Kubernetes services grouped by short name and environment'. This clearly distinguishes the tool from siblings like list_k8s_namespaces, which lists namespaces, not services.

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 to use this tool before calling start_k8s_port_forward, providing a clear when-to-use and linkage to an alternative (the sibling tool). It also implies its role as a prerequisite, offering high-quality 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?

No annotations are provided, so the description carries the full burden. It discloses that the tool starts a process (mutation), that multiple forwards share a session, and that logs open in separate windows if includeLogs is true. However, it does not describe blocking behavior, failure modes, resource limits, or what the tool returns (no output schema exists). These gaps limit transparency for a potentially long-running operation.

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 three sentences with no wasted words. The main action is in the first sentence, followed by usage guidance and behavioral notes. Every sentence earns its place.

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

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

The description covers the prerequisite steps and session behavior, but it omits key details for a tool with no output schema: return value, success/failure signaling, and how to stop the port forwarding (though a sibling tool exists). For a tool that initiates a persistent process, additional context about lifecycle and results would be needed for full 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?

All parameters are described in the input schema (100% coverage), so the description is not required to add much. The description reinforces that service names and namespaces should be resolved beforehand and that each service config can differ, but it does not add new meaning beyond the schema. Baseline 3 is appropriate.

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

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

The description starts with a clear verb 'Starts' and resource 'port forwarding for one or more Kubernetes services'. It distinguishes from sibling tools like list_k8s_services (listing) and stop_k8s_port_forward (stopping), making the tool's core purpose unambiguous.

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

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

The description explicitly advises calling list_k8s_services and optionally list_k8s_namespaces first to resolve exact names, establishing a clear prerequisite workflow. It also notes that all port-forwards run in a single session, implying session management context. However, it does not specify when *not* to use this tool or mention alternatives like stop_k8s_port_forward for a different phase.

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 'stop all active,' which signals a bulk destructive action (terminating all forwards), but it does not clarify required permissions, side effects on existing connections, or behavior when no forwards are active.

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 sentence with no fluff or repetition. Every word earns its place, achieving maximum efficiency for a zero-parameter tool.

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

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

Given no output schema and no parameters, the description covers the core action adequately. It could mention whether calling the tool multiple times is safe or what happens if no forwards exist, but these are minor gaps for such a simple 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 zero parameters and 100% coverage. The description adds no parameter-specific detail because none is needed. Baseline 4 is appropriate for tools with no parameters.

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 uses a specific verb ('Stop') and resource ('all active Kubernetes port-forward processes'), clearly distinguishing it from sibling tools like start_k8s_port_forward (which initiates forwards) and list_k8s_services (which lists services).

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 use after starting port-forwards or for cleanup, but does not explicitly state when to use versus alternatives. However, the sibling names and the tool's zero-parameter simplicity make the usage context obvious.

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