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

The annotations already provide destructiveHint: true, so the description's additional context about no shell interpretation adds some value. However, it does not detail potential destructive effects or error handling, but it does not contradict 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 two sentences, directly stating the purpose and key usage rule. It is front-loaded and contains no unnecessary words.

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?

While the description covers the essential command format and security aspect, it omits details like return format, prerequisites (e.g., pod must be running), error handling, and potential side effects. Given no output schema, more completeness would be beneficial. However, it is still adequate for a simple exec 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 coverage is 100%, so baseline is 3. The description adds the important constraint that the command array must have the executable as the first element, and clarifies no shell interpretation. This adds meaningful guidance beyond the 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 executes a command in a Kubernetes pod and returns output, specifying the command must be an array of strings. This distinguishes it from sibling tools like kubectl_generic or kubectl_logs.

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 explains the required command format (array of strings) and notes that shell interpretation is avoided for security. However, it does not explicitly state when to use this tool over alternatives like kubectl_generic or when not to use it.

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, so the description's addition of 'Get documentation' is consistent but adds no new behavioral insights. The tool's non-destructive nature is clear, but there is no mention of authorization requirements or data source (e.g., cluster API or bundled docs).

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, making it concise and front-loaded. However, it lacks structure and could benefit from a second sentence clarifying the tool's relationship to kubectl explain. The brevity sacrifices nuance.

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 resources, the absence of context about document format (e.g., plaintext), scope (e.g., cluster API docs), and how it differs from describe/list is a shortcoming. The description is too minimal for the tool's role among 20+ 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 coverage is 100%, with each parameter having a description. The tool description repeats 'Kubernetes resource or field', which mirrors the resource parameter's role. It adds no extra meaning beyond what the schema already provides, meeting 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 retrieves documentation for a Kubernetes resource or field, which is a specific verb+resource combination. It distinguishes itself from sibling tools like kubectl_get (list/retrieve resources) and kubectl_describe (detailed info on live resources) by focusing on API documentation.

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 is provided on when to use explain_resource versus alternatives such as kubectl_describe or list_api_resources. The description lacks explicit context for tool selection, leaving the agent to infer usage from the tool name alone.

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

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

The destructiveHint annotation already signals potential destructiveness. The description adds mention of two installation modes but does not elaborate on behavioral traits such as error handling, rollback behavior, or prerequisites like Helm being installed. Given the annotation coverage, a score of 3 is appropriate as the description adds some but limited context.

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

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

The description is a single sentence with no redundancy. It is concise and front-loaded with the core purpose, though it could benefit from a brief expansion on usage.

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 9 parameters, destructive potential, and no output schema, the description is incomplete. It does not cover return values, error scenarios, prerequisites, or when to choose between installation modes. The schema and annotations provide partial context, but the description should bridge remaining 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 parameters. The tool description does not add meaningful extra semantics beyond referencing the two installation modes (standard/template), which is already covered in the 'useTemplate' parameter description.

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 installs a Helm chart and highlights support for standard and template-based installations, which differentiates it from sibling tools like upgrade_helm_chart and kubectl commands.

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 lacks explicit guidance on when to use this tool versus alternatives or which installation mode to choose. The parameter schema hints at use cases for the 'useTemplate' flag, but the description itself does not provide decision points.

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 provide destructiveHint=true. Description adds no additional behavioral context beyond the schema's parameter descriptions. No contradiction, but no extra value.

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 9-word sentence, front-loaded with verb and resource, zero wasted words.

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?

No output schema, so description should explain return values or errors, but does not. However, the tool is a standard kubectl operation; description is adequate but incomplete for a mutation tool with 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%, so the schema already documents all parameters. Description only hints at 'string or file' but adds no meaningful semantic detail beyond the 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?

Description clearly states 'Apply a Kubernetes YAML manifest from a string or file', specifying the action (apply) and resource (YAML manifest). It distinguishes from siblings like kubectl_create, which creates resources differently.

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 explicit guidance on when to use apply versus siblings like kubectl_create or kubectl_patch. Usage is implied but not differentiated.

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 annotation readOnlyHint: true contradicts the description's claim of a 'set' operation, which modifies the current context. This is a serious inconsistency. The description fails to disclose this behavioral trait or any side effects, and it contradicts the available annotation.

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, front-loaded sentence that efficiently conveys the tool's purpose and operations. No words are wasted, and it is appropriately sized for a straightforward tool.

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

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

Given the tool has 5 parameters, no output schema, and conflicting annotations, the description is too brief. It omits critical details such as what the 'set' operation actually modifies, return values, or prerequisites. The agent lacks sufficient information to use the tool safely and effectively.

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

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

Schema description coverage is 100%, with all parameters having clear descriptions. The tool description itself adds no extra meaning beyond what the schema provides. Baseline 3 is appropriate as the schema already handles parameter semantics.

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 contexts and enumerates the three specific operations: list, get, or set the current context. This distinguishes it from sibling tools like kubectl_get or kubectl_apply, 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 provides no guidance on when to use this tool versus alternatives. It does not mention when to choose list over get, or when using the set operation is appropriate. No exclusions or conditions are given.

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 responsibility for behavioral disclosure. It states 'Create', implying a mutation, but does not elaborate on idempotency, error behavior, permission requirements, or side effects. The parameter 'dryRun' hints at validation support, but the description itself adds no further behavioral context.

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

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

The description is a single short sentence, which is concise. However, it could be more structured by front-loading the two creation methods and possibly indicating that the tool supports many resource types. It is not verbose but lacks a clear structure that aids quick scanning.

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 (23 parameters, no output schema, no annotations), the description is insufficient. It does not explain how parameters interact, which resource types are supported, or what the return value looks like. The user must rely entirely on the schema, which is unusual for such a versatile 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 coverage is 100%, so every parameter has a description in the schema. The tool description adds minimal value beyond the schema; it only mentions two methods without linking them to specific parameters. The baseline is 3 because the schema already documents all parameters, and the description does not compensate for any gaps.

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 'Create Kubernetes resources using various methods (from file or using subcommands)'. It identifies the tool's function (creating resources) and distinguishes it from siblings like kubectl_apply (which applies updates) and kubectl_patch (which modifies existing resources). The verb 'Create' and resource type 'Kubernetes resources' are specific and 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 does not provide any guidance on when to use this tool versus alternatives such as kubectl_apply, kubectl_patch, or exec_in_pod. It mentions two methods (file or subcommands) but does not explain which scenarios favor one method over the other. There are no prerequisites, exclusions, or context on when not to use the tool.

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, so the agent knows this is a safe read operation. The description adds that it describes resources, which is consistent. It does not mention output format or other behavioral traits, but with the annotation covering the safety profile, a 3 is appropriate.

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 of 11 words. It conveys the action and essential parameters without any filler, making it extremely concise and front-loaded.

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 tool has 5 parameters (2 required) and no output schema. The description covers the core purpose and the most important parameters, but it does not explain the output format or how to use optional parameters. For a read-only describe tool, this is minimally adequate but could be improved by noting that output is detailed resource information.

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 coverage is 100%, so all parameters are described in the schema. The description summarizes three parameters (resource type, name, namespace) but does not add extra meaning beyond the schema for optional parameters like context or allNamespaces. Baseline 3 is correct when schema covers all 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 the specific verb 'describe' and identifies the resource as 'Kubernetes resources'. It clearly lists the key parameters (resource type, name, optionally namespace), making the tool's purpose unambiguous and distinguishing it from sibling tools like kubectl_get or kubectl_logs.

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 stating 'describe...by resource type, name, and optionally namespace', but it does not explicitly state when to choose this tool over alternatives (e.g., kubectl_get for listing, kubectl_logs for logs) or when not to use it. The context is clear but lacks explicit 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?

Annotations already indicate readOnlyHint=true. The description confirms read behavior (get/list) but adds no further behavioral details (e.g., pagination, rate limits, or side effects). It does not contradict 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 a single, efficient sentence that front-loads the core action and key parameters. Every word adds value; no 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?

The description is adequate for a simple read tool but lacks mention of default values (e.g., namespace default), allNamespaces, and output formats. Since schema covers these, completeness is acceptable but not thorough.

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 coverage is 100%; each parameter has a description. The tool description only mentions three parameters (resourceType, name, namespace) without adding new meaning. Baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: get or list Kubernetes resources by type, name, and namespace. It uses specific verbs and resource, and the action is distinct from sibling tools like kubectl_describe or kubectl_delete.

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 kubectl_describe (for detailed info) or kubectl_logs. With many sibling tools, explicit usage context is lacking.

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 set readOnlyHint=true, and the description's 'get logs' is consistent. However, the description does not elaborate on behavioral traits beyond the annotation, such as potential side effects of the 'follow' parameter or that logs are from stdout/stderr. The description adds minimal value over the annotation.

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

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

The description is a single, clear sentence with no redundancy. It is appropriately concise for the tool's simplicity. However, it could include key parameter hints without becoming verbose.

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 12 parameters and no output schema, the description is too sparse. It omits important contextual details such as the need for container when multi-container pods exist, the meaning of labelSelector, and the risk of timeouts with follow. The description fails to fully equip an agent to handle complex log retrieval scenarios.

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

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

The input schema covers all 12 parameters with descriptions (100% coverage). The description does not add high-level semantics or explain parameter interactions (e.g., mutual exclusivity of since/sinceTime). Baseline is 3 due to full schema coverage, and the description provides no additional benefit.

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 gets logs from Kubernetes resources and lists examples (pods, deployments, jobs). The name kubectl_logs is self-explanatory, but the description adds specificity by mentioning resource types. It distinguishes from sibling tools like kubectl_get which retrieve resource definitions, not logs.

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

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

The description implies usage for retrieving logs but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it (e.g., for live streaming which may cause timeouts). No exclusions or context for sibling tools are given.

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 destructiveHint=true. Description adds patch types but no additional behavioral context (e.g., side effects, rollback). Adequate but minimal.

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, no fluff, efficiently conveys core functionality.

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?

With 8 parameters and nested objects, the description is too brief. Lacks explanation of patch type differences or return values, though schema covers parameters.

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 baseline is 3. Description adds no extra parameter meaning beyond what schema provides.

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 updates fields of a resource using specific patch types, distinguishing it from sibling tools like kubectl_apply or kubectl_create.

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; lacks context on selecting patch type or prerequisites.

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 indicate readOnlyHint=false, and the description adds behavioral detail: it recreates API clients and forces fresh DNS resolution and TCP connections. 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?

Two sentences, front-loaded with purpose and usage. No redundancy; every word adds value.

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 with no parameters and no output schema, the description covers purpose, usage context, and behavioral effects completely and concisely.

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 no parameters (0 params, 100% coverage), so the description need not explain parameters. Baseline 4 for zero-parameter 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 'Reconnect' and the resource 'Kubernetes API server by recreating all API clients'. It distinguishes from siblings by specifying a concrete use case: after cluster upgrades that rotate ENIs/IPs.

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 the tool ('after cluster upgrades...') and why ('to force fresh DNS resolution and new TCP connections'). It does not mention alternatives, but the guidance is clear and actionable.

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 does not add behavioral context beyond the annotation destructiveHint=true. It does not explain potential impacts (e.g., rollback causing downtime) or required permissions. Since annotations already indicate destructiveness, a score of 3 is appropriate.

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 very short (one sentence, 7 words), but it is underinformative for a tool with 9 parameters and multiple subcommands. While concise, it sacrifices necessary detail, so a score of 3 is warranted.

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 (multiple subcommands, no output schema), the description is too minimal. It lacks information about return values, when to use each subcommand, and execution behavior, making it incomplete for effective agent use.

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

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

Schema description coverage is 100%, so all parameters are described in the input schema. The tool description adds no additional meaning beyond what the schema provides, resulting in a baseline score of 3.

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 the rollout of a resource, with examples of resource types (deployment, daemonset, statefulset). This distinguishes it from sibling tools like kubectl_apply or kubectl_scale, which do not handle rollout operations.

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 is provided on when to use this tool versus alternatives. The description does not mention specific use cases (e.g., viewing history, pausing, rolling back) nor does it compare with other kubectl tools that may have overlapping functionality.

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 annotation 'destructiveHint: true' already indicates state modification. The description adds no further behavioral context, such as that scaling triggers pod creation/termination, or whether the operation is immediate and idempotent. Given the annotation presence, a score of 3 is appropriate as the description does not contradict but adds little value.

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 at one sentence. While it is front-loaded, it may be insufficient for a tool with 5 parameters and potential variations. A slightly longer description with key details would improve usability without losing conciseness.

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 tool performs a simple mutation, but the description lacks mention that it can scale resources other than deployments (e.g., replicasets, statefulsets). No output schema exists, but for a scaling operation, the return value is often the updated resource or status; the description could hint at that. Overall, it meets minimum viability but has 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 baseline is 3. The tool description does not add any meaning beyond the parameter descriptions in the schema. It provides no examples, constraints, or relationships between 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 'Scale' and resource 'Kubernetes deployment'. However, it omits that the tool can also scale other resource types (replicaset, statefulset) as indicated by the 'resourceType' parameter. Among siblings like kubectl_apply and kubectl_patch, it could be more distinctive.

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 (e.g., kubectl_apply for broader changes). No prerequisites or conditions are mentioned, such as requiring the target resource to exist. The description does not help the agent decide between scaling and other operations.

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 readOnlyHint annotation already indicates a read-only operation. The description adds no additional behavioral context beyond stating the action 'List'. No details on scope, safety, or response characteristics are provided.

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, front-loaded sentence with no superfluous words. However, it is overly brief given the complexity of the tool and its parameters, but this is not penalized heavily under conciseness.

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?

Despite 5 parameters and many sibling tools, the description lacks critical context such as what the output looks like (no output schema) and when to use this tool. The description is insufficient for effective tool selection and 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?

Schema description coverage is 100%, so the baseline is 3. The description does not add any extra meaning beyond what the schema already explains for each parameter.

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 'List the API resources available in the cluster' clearly states the verb and resource, but it does not distinguish this tool from siblings like kubectl_get or explain_resource, which also list API resources. The term 'API resources' is ambiguous; it could mean resource types or instances.

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 such as kubectl_get or kubectl_describe. There is no mention of context, 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?

Annotations provide readOnlyHint: true, indicating safety. The description adds that it verifies responsiveness and connection, which aligns with annotations and provides additional behavioral 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?

A single sentence that is concise, front-loaded, and contains no unnecessary words. Every word earns its place.

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

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

Given the tool's simplicity (no parameters, no output schema), the description is complete enough for an agent to understand its purpose and use.

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

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

No parameters exist. Baseline is 4 for zero parameters, and the description doesn't need to add parameter info beyond what the schema already provides.

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 function: verifying the counterpart is responsive and the connection is alive. It distinguishes from sibling tools like kubectl_get or exec_in_pod which perform other operations.

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 explicit when-to-use or when-not-to-use guidance is given. However, from context it's implied for connectivity checks before other operations, but no alternatives 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?

Annotations provide no readDestructive hints. The description only states the basic operation without disclosing behavioral traits such as network activity duration, port conflict handling, or cleanup requirements. For a tool that opens a tunnel, more context is needed.

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 (one sentence), but it is too terse for a tool with 5 parameters. It would benefit from additional structure without being verbose.

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 (forwarding ports, multiple parameters, no output schema), the description is incomplete. It does not mention supported resource types, error cases, how to stop the forward, or relationship to sibling tool 'stop_port_forward'. The agent lacks sufficient context for reliable 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?

Schema description coverage is 0%. The description does not explain any parameters. Parameter names (resourceType, resourceName, etc.) are self-explanatory but lack syntax, constraints, or examples. The description should add meaning beyond the 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 action and resource: 'Forward a local port to a port on a Kubernetes resource'. It uses a specific verb and resource, distinguishing it from sibling tools like 'stop_port_forward' and other kubectl operations.

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 (e.g., exec_in_pod, kubectl_logs). No prerequisites, exclusions, or context for when port forwarding is appropriate.

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 beyond title; the description does not disclose behavioral traits such as side effects (e.g., terminating network connections), permissions needed, or whether the operation is reversible.

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 short (one sentence) but it is underspecified. It lacks sufficient content to be useful, crossing from conciseness into incompleteness.

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, no parameter explanations, and minimal description, the tool definition is inadequate for an agent to correctly select and invoke it.

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 only parameter 'id' has no description in the schema, and the tool description adds no meaning. With 0% schema description coverage, the description fails to clarify what 'id' represents.

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 'Stop a port-forward process' is a specific verb+resource, but it's vague and doesn't clarify what 'a port-forward process' refers to. It distinguishes from the sibling 'port_forward' but lacks detail.

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 like 'port_forward' or when it's appropriate. The description provides no context for usage.

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 mark the tool as destructive (destructiveHint=true). The description adds no additional behavioral context, such as authorization needs, side effects, or rollback behavior, which would be valuable for an upgrade 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 a single short sentence, which is concise but lacks sufficient detail. It could be expanded slightly without sacrificing conciseness, e.g., by mentioning that the release must already exist.

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?

No output schema is present, and the description does not explain return values, error handling, or the upgrade process. For a tool with 7 parameters and a nested object, this is incomplete.

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 coverage, the input schema already describes all parameters. The description does not add extra meaning beyond the schema, meeting the baseline for high coverage.

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

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

The description uses a specific verb ('upgrade') and resource ('existing Helm chart release'), clearly indicating what the tool does. However, it does not distinguish itself from the sibling tool 'install_helm_chart' for new installations, which would be a minor improvement.

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 the release must exist ('existing') but provides no explicit guidance on when to use this tool versus alternatives like 'install_helm_chart'. No prerequisites or when-not-to-use advice is given.

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