ocp-mcp

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools target distinct resource types (list_* vs get_* per kind), and overlap is limited to a few areas like logs (get_pod_logs, get_all_container_logs, get_previous_pod_logs) and deployment operations (rollout_restart, rollback_deployment, get_deployment_revision_history). Descriptions clarify these related tools, so an agent can usually pick the right one, but the sheer number increases selection risk.
Naming Consistency4/5
The dominant pattern is verb_noun in snake_case (list_pods, get_deployment, scale_statefulset), which is predictable. However, there are deviations like rollout_restart (noun_verb), top_pods/top_nodes (no list/get prefix), and pod_resource_usage_vs_requests (descriptive phrase) that break the strict pattern.
Tool Count2/5
With 77 tools, the surface is very large and far exceeds the typical well-scoped range. While OpenShift is broad, many tools are similar list/get variants for different resource kinds, making the server feel overloaded. This volume could overwhelm agents and increase decision cost.
Completeness3/5
The server covers a wide range of OpenShift resources with list/get, scaling, logs, events, and monitoring. However, there are notable gaps: no create/update for most resources, delete only for a few kinds, and missing some common resources like roles/rolebindings. Core operational workflows are present, but full lifecycle coverage is incomplete.
Average 3.3/5 across 77 of 77 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must convey behavioral traits but only says 'Get detailed information', offering no details on read-only nature, return format, potential errors, or side effects. It is not misleading but severely under-informs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. However, it is too terse, omitting essential usage and parameter details, so it borders on under-specification rather than concise completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema, no annotations, and minimal parameter documentation, this description is inadequate. Even for a simple getter, it should clarify the parameters and possibly the nature of 'detailed information'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description mentions none of the three parameters (name, namespace, cluster_alias). It does nothing to clarify parameter semantics, leaving the agent to infer from names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves detailed information about an OpenShift BuildConfig, using a specific verb and resource. It distinguishes from sibling list_buildconfigs by implying a single resource lookup, but does not explicitly differentiate from get_build or other getters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like list_buildconfigs or get_build. The usage context is implied by the name and sibling tools, but there is no explicit when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 merely restates the tool's name ('Get events for a specific Pod') without adding any context about event limits, sorting, permissions, error behavior, or what 'specific' implies. It offers no more insight than the name itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence that is immediately clear and free of unnecessary words. It is front-loaded and efficient, though perhaps too terse given the need for more context. It does not waste space but lacks elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the existence of an output schema, the description is incomplete for effective tool use. It fails to mention how the pod is identified (name/namespace), what cluster_alias does, or when to use this tool relative to list_events. With no annotations and minimal schema descriptions, this is insufficient for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the three parameters (name, namespace, cluster_alias). The phrase 'specific Pod' implies name and namespace but provides no detail on defaults, formats, or the role of cluster_alias. The description adds no value over the bare parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves events for a specific Pod, using a specific verb ('Get') and resource ('events for a specific Pod'). This distinguishes it from sibling tools like list_events (which likely lists all events) and get_pod (which retrieves pod details).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 list_events. There is no mention of exclusions, prerequisites, or scenarios where this tool is preferred. It only states the basic function.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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, but it reveals nothing about read-only behavior, permissions, error handling, or what 'detailed information' includes. It only implies a read operation via the verb 'Get'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded, with no wasted words, but it is under-specified. It earns a middle score for being concise yet lacking essential content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is expected to provide more context. It does not explain what 'detailed information' entails, the required 'name' parameter, or any potential errors, making it incomplete for a simple get operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not mention any parameters or how they should be used. It fails to compensate for the lack of schema descriptions, leaving the agent without guidance on 'name', 'namespace', or 'cluster_alias'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and the resource ('OpenShift Build') with a specific scope ('detailed information'). This distinguishes it from sibling tools like 'list_builds' and 'get_buildconfig'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as 'list_builds' or 'get_buildconfig'. The description only states the basic function, leaving usage context entirely implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states that the tool retrieves a ConfigMap including its data, but it does not disclose read-only intent, permission requirements, error behavior (e.g., not found), or any other side effects. The description adds minimal context beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is front-loaded with the main action and resource. However, it is arguably under-specified, but the conciseness itself is appropriate given the simple nature of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has three parameters, no output schema, and no annotations. The description only says 'including its data', which partially addresses the return value but does not explain parameter semantics, error conditions, or how cluster_alias affects the request. A more complete description would mention that it fetches a specific ConfigMap by name, namespace, and optional cluster alias, and what the response contains.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for parameters. The description does not mention any of the three parameters (name, namespace, cluster_alias). While 'name' and 'namespace' are somewhat self-explanatory, 'cluster_alias' is ambiguous and left unexplained. The description provides no added meaning over the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' with the resource 'ConfigMap' and clarifies that the return includes its data. This distinguishes it from list_configmaps, which lists all ConfigMaps, though it does not explicitly differentiate from other getter tools in the sibling set.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 neither states when to use it (e.g., when you need a specific ConfigMap's data) nor mentions alternatives like list_configmaps for listing or get_secret_metadata for secrets. The usage is only implied by the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states that it retrieves detailed information, offering no specifics about return format, error behavior (e.g., missing pod), or permissions. The read-only nature is implied but not elaborated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no fluff. It is concise and easy to parse, though it sacrifices substance for brevity. The length is appropriate for a simple get operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read tool with 3 parameters, no output schema, and no annotations, the description is too sparse. It does not explain what 'detailed information' includes, how parameters interplay, or how this tool differs from similar getters. This leaves the agent with insufficient context to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate for parameter meaning. It does not explain the parameters at all. However, the parameter names (name, namespace, cluster_alias) are fairly self-explanatory, and the phrase 'specific Pod' clarifies the primary parameter, providing minimal additional context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('Pod'), making its purpose clear. While it doesn't explicitly distinguish from sibling tools like get_pod_logs or get_pod_events, 'detailed information' likely refers to the full pod object/status, which is a reasonable reading.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. Given the large number of pod-related sibling tools (get_pod_logs, get_pod_events, top_pod, etc.), explicit usage context or exclusions would be valuable, but none are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states this is a 'Get' operation, implying a read-only action, but does not disclose aspects such as required permissions, error behavior (e.g., deployment not found), or the structure of the returned 'detailed information'. The description adds minimal value beyond the tool name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler words, making it concise and easy to parse. However, it is under-specified for a tool with three parameters and no annotations, which prevents a perfect score since conciseness here borders on insufficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description should provide more context about what 'detailed information' means, such as whether it returns the full deployment spec and status, and how cluster_alias is used. The current description is too vague for an agent to fully understand the tool's output and dependencies.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the tool description does not compensate. While the description implies the 'name' parameter identifies the deployment, it does not clarify the meaning or purpose of 'namespace' or 'cluster_alias', nor their optionality. With three parameters and no supplemental explanation, the agent gets little semantic help.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as retrieving detailed information about a specific Deployment, using a specific verb ('Get') and resource ('Deployment'). This distinguishes it from sibling tools like list_deployments (which lists) and get_deployment_rollout_status (which specifically targets rollout status), 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.
Usage Guidelines2/5
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 get_deployment_rollout_status, get_deployment_revision_history, or rollback_deployment. There is no mention of prerequisites or exclusions, leaving the agent to infer usage purely from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden of disclosing behavioral traits. It provides basic information about the output (status and capacity info) but omits important behaviors such as how the optional cluster_alias parameter affects the operation, whether any authentication is required, or if results are paginated. This leaves significant ambiguity for the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose. It is well-structured and front-loaded, but could arguably include a brief mention of the cluster_alias parameter without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description covers the primary return content but remains incomplete because it fails to explain the behavior of the optional parameter. It also lacks any mention of prerequisites or side effects. The missing parameter semantics create a notable gap in overall context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. However, it does not mention the cluster_alias parameter at all. The parameter name alone provides only a hint, leaving its effect (selecting which cluster to list nodes from) undocumented in both the schema and description. The description adds no value to parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'List all nodes in the cluster with status and capacity info.' It uses a specific verb ('list') and resource ('nodes'), and distinguishes itself from siblings like get_node (which retrieves a single node) and top_nodes (which focuses on resource usage).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. The description does not mention any exclusions, preferred scenarios, or related tools such as get_node for targeted queries. The only implied context is from the action of listing, but this is not elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden for behavioral disclosure. It only says 'Get detailed information' and does not mention return format, error behavior, permission requirements, or that it is a read-only operation. While 'Get' implies non-mutating, the description lacks any extra 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no unnecessary words. It is appropriately concise for a simple getter, stating exactly what the tool does without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It does not describe what 'detailed information' includes (e.g., spec, status), nor does it provide context on cluster selection or return format. The tool is simple, but the description leaves significant ambiguity for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no parameter descriptions (0% coverage), and the description does not compensate. It does not explain the meaning or usage of name, namespace, or cluster_alias, leaving the agent to infer solely from field names and defaults, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets detailed information about an OpenShift DeploymentConfig. It specifies the verb 'Get' and the resource 'OpenShift DeploymentConfig', which distinguishes it from sibling tools like get_deployment (for Kubernetes Deployments) and list_deploymentconfigs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives such as list_deploymentconfigs or scale_deploymentconfig. The description only states what the tool does, without any context on prerequisites, selection criteria, 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description alone must disclose behavioral traits. It only states the basic listing action and reveals nothing about side effects, authentication needs, rate limits, pagination, or output specifics beyond what the schema might convey. This is a significant gap for a tool that could be used in production environments.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant words. It efficiently conveys the core purpose, making it maximally concise and well-structured for its scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is fairly simple and the presence of an output schema covers return values. However, the description fails to mention the role of cluster_alias or provide any operational context, making it minimally adequate but not complete for a tool with optional cluster selection and many sibling list tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must clarify the parameters. It adds meaning to the 'namespace' parameter by saying 'in a namespace,' but completely ignores 'cluster_alias,' which remains unexplained. The description only partially compensates for the schema's lack of semantic detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List all Jobs in a namespace.' clearly states the action (list), the resource (Jobs), and the scope (a namespace). It is specific enough to distinguish from get_job (singular) and list_cronjobs (different resource), though it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus sibling tools like list_cronjobs or get_job. The description omits any context about prerequisites, intended use cases, or exclusions, so it provides no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description bears full responsibility. It discloses the filtering behavior but omits details such as pagination, ordering, cluster context, or any side effects. The verb 'List' implies a read operation, but this is not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that leads with the action and clearly states the criterion. No filler or redundant information is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and has an output schema, but the description lacks necessary context about how namespace and cluster_alias affect the query. Without usage guidance or parameter semantics, the description is insufficient for a new agent to invoke the tool correctly in all scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description mentions none of the parameters. The meanings of 'namespace' and 'cluster_alias' are left to inference from names and defaults, which is insufficient for correct use across clusters or namespaces.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 (pods), and the specific filter (at least one container not ready). This distinguishes it from sibling tools like list_pods (all pods) and list_failing_pods (different failure criteria).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as list_pods or list_failing_pods. The description states what it does but gives no context for selection or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 only states the action without mentioning whether it is read-only, which cluster is used, how the cluster_alias parameter affects behavior, or any side effects or permissions required.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with zero wasted words. It conveys the core purpose efficiently, though this conciseness comes at the cost of other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists to cover return values, the description omits any mention of cluster_alias, which is a critical parameter in a multi-cluster environment (as evidenced by sibling cluster tools). It also lacks guidance on default behavior, making it incomplete for an agent to confidently invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain either parameter. It mentions 'a namespace' but does not clarify the default namespace behavior or the purpose of cluster_alias, leaving the agent without meaningful parameter context beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List all ServiceAccounts in a namespace' uses a specific verb ('List') and identifies the resource ('ServiceAccounts') and scope ('in a namespace'). This clearly distinguishes it from sibling tools, as no other sibling targets ServiceAccounts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, nor any exclusions or prerequisites. It merely states what it does, leaving the agent to infer usage context from the name and sibling set.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full transparency burden. It only says 'List all ServiceMonitors in a namespace' and adds a parenthetical definition; it does not disclose behavioral details such as pagination, cluster selection via cluster_alias, error handling, or whether the list includes full objects or names only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence with a clarifying parenthetical. It front-loads the action and resource, and every word adds value with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given two parameters, no annotations, and an output schema present, the description should at least explain parameter roles and selection context. It only identifies the resource type and namespace scope; it leaves cluster_alias unexplained and provides no guidance for effective use. The output schema covers return values, but this is still insufficient for complete context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description fails to explain either parameter. The phrase 'in a namespace' loosely hints at namespace, but cluster_alias is completely undocumented. The description does not compensate for the missing parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list', the resource 'ServiceMonitors', and the scope 'in a namespace', with a parenthetical clarifying they are 'Prometheus scrape targets'. This distinguishes it from similar tools like list_pod_monitors by naming the specific resource type and adding domain context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives like list_pod_monitors or list_prometheus_rules. The description only implies a use case by naming the resource, but does not mention exclusions, prerequisites, or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states that the tool lists services, without mentioning pagination, cluster selection behavior, permissions, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant words or filler. It efficiently conveys the core operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and zero schema description coverage, the description is too sparse. It omits behavior around cluster_alias and list limitations, though the existence of an output schema slightly reduces the need to describe return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not mention either parameter. The agent must infer the meaning of 'namespace' and 'cluster_alias' solely from their names and defaults, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List'), resource ('Services'), and scope ('in a namespace'), clearly distinguishing it from sibling list tools for other resource types like ConfigMaps or Pods.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, nor any exclusions or prerequisites. The description is purely functional and gives no context about cluster_alias or typical usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It only says 'Get' implying read-only, but does not mention requirements (e.g., metrics server), permissions, or edge cases. This leaves the agent guessing about operational constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero filler. It is appropriately sized for its simple purpose and the information it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 provides minimal context. It omits parameter semantics, usage guidance, and return format details. While the tool is simple, the description is not complete enough for reliable autonomous invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds no meaning to any parameter—it does not even connect 'specific pod' to the 'name' parameter. The agent must infer semantics solely from parameter names and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb and resource: 'Get real-time CPU and memory usage for a specific pod.' The word 'specific' distinguishes it from sibling 'top_pods', which likely covers all pods.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 top_pods. The description lacks any exclusions, preferred contexts, or references to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description does not disclose the destructive consequences, lack of reversibility, or potential cluster impact. It simply restates the action from the tool name without adding behavioral context or safety warnings.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the core operation. No extra words, but it may be too terse given the need for safety and parameter context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
As a bulk destructive tool with no annotations, output schema, or parameter descriptions, the description is insufficient. It tells the agent what it does but not the risks, prerequisites, or return behavior, making it incomplete for safe operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the namespace or cluster_alias parameters, their defaults, or how they affect execution. The description fails to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (force-delete), the resource (pods), the scope (ALL), and the condition (stuck in Terminating state) within a namespace. It distinguishes from sibling tools like force_delete_pod (singular) and list_terminating_pods.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when pods are stuck in Terminating state, but does not explicitly contrast with force_delete_pod for individual pods or provide warnings about bulk deletion. It gives a clear context but no exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It only says 'Get detailed information' without mentioning potential errors, required permissions, or the nature of the response. The presence of an output schema helps, but the description itself adds little 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no unnecessary fluff. It is appropriately sized for the tool's simplicity and front-loads the essential action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get-resource tool with an output schema, the description and schema together are minimally viable. However, the description does not mention the default namespace or cluster_alias behavior, leaving some contextual gaps that could affect correct invocation in multi-cluster scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not compensate by explaining any parameters. It does not clarify the role of 'name', 'namespace', or 'cluster_alias', leaving the agent to rely solely on parameter names and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'specific HorizontalPodAutoscaler', making its purpose unambiguous. It distinguishes itself from list_hpas by focusing on a single, specific HPA.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like list_hpas, nor any mention of prerequisites or use cases. The description implies usage for a specific HPA but does not elaborate on context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 only states the action without mentioning any behavioral traits such as pagination, ordering, permissions, return format, or cluster selection semantics. For a list operation, it doesn't state whether it returns all fields or just names, or if cluster_alias overrides the default.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no filler. It is well-structured and front-loads the action verb immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple, and an output schema exists to explain return values. However, the description does not clarify the role of cluster_alias or the behavior when multiple clusters are available, nor does it mention any filtering or pagination. Given the availability of an output schema, the description is close to sufficient for a basic list operation, but the cluster_alias parameter introduces ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the undocumented parameters. It does not mention either parameter, leaving the agent to guess the semantics of namespace (which has a default) and cluster_alias (which is nullable). No parameter meanings are added beyond the schema's type definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' and resource 'Deployments' with a namespace scope, clearly distinguishing it from sibling tools like get_deployment or scale_deployment. It directly states the action and target.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. It doesn't mention exclusions, prerequisites, or alternatives. The description is purely declarative with no contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral details, but it only states the basic operation. It does not mention permissions, pagination, limitations of namespace scope, or how cluster_alias affects results, so the agent is left unaware of potential side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, succinct sentence that is immediately clear and front-loaded with the action and scope. It contains no wasted words and is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is straightforward and an output schema exists to define return values, the description lacks important usage and behavioral context. It is minimally sufficient but incomplete, especially regarding cluster_alias and when to use the tool relative to siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the tool description fails to explain the parameters. It merely echoes 'namespace' without adding semantic meaning, and does not address cluster_alias at all, leaving the agent without necessary parameter context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('List') and resource ('Pods') with scope ('in a namespace'), making it easily distinguishable from filtered pod-listing siblings like list_failing_pods or list_pods_not_ready, as it explicitly says 'all Pods'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 filtered pod lists or get_pod. It does not mention use cases, exclusions, or prerequisites, leaving the agent without clear decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only says 'Get detailed information' without specifying what details are returned, any permissions needed, or side effects. It does not add meaningful transparency beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no wasted words. It is appropriately front-loaded with the key action and object.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and three parameters with zero description coverage, the description is incomplete. It does not explain the return value, how cluster_alias or namespace affect the call, or what 'detailed information' entails.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the three parameters (name, namespace, cluster_alias). The parameter names are self-explanatory to some extent, but the description adds no additional meaning or usage context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'specific CronJob', distinguishing it from list_cronjobs. It conveys the tool's scope precisely.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives like list_cronjobs or get_job. The intended use case is only implied by the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior, but it only says 'get detailed information.' It does not mention return format, side effects, error behavior, or permissions, which is insufficient without annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant information. Every word contributes to the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 3-parameter tool with no annotations and no output schema, the description is too thin. It leaves the agent without understanding of return details, required cluster context, or how this fits into the wider Kubernetes toolset.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description adds no parameter meaning beyond the schema's property names. While 'name', 'namespace', and 'cluster_alias' are self-descriptive, the description fails to clarify nuances like cluster_alias selection or defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('DaemonSet'), and explicitly says 'specific' to distinguish from list_daemonsets. This clearly states the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like list_daemonsets or get_statefulset. There are no prerequisites or exclusions, leaving invocation timing implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure. It only states that detailed information is returned, mentioning 'all tags,' but does not indicate error handling, permissions, side effects, or response format. This is a significant gap for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action and resource, and contains no unnecessary words. It is highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has three parameters, no annotations, and no output schema. The description is too terse to be complete: it does not address error cases, default behavior of namespace/cluster_alias, or the structure of the returned data beyond mentioning tags. This is a clear gap for a getter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the three parameters (name, namespace, cluster_alias). The schema provides only parameter names and defaults, so the agent is left without semantic guidance on what these parameters mean or how they affect the call.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('Get detailed information') on a specific resource ('OpenShift ImageStream') and includes a notable detail ('including all tags'). It distinguishes from sibling tool list_imagestreams by focusing on a single resource rather than a listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving details on a specific ImageStream, but it does not explicitly mention when to use this over list_imagestreams or provide exclusions/alternatives. Context is implied but not fully specified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 does not disclose that this is a read-only operation, any required permissions, or what the response includes. The description simply states the purpose without behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded and contains no unnecessary words. It is appropriately concise for a straightforward retrieval tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations and no output schema, the description should provide more context about what 'detailed information' includes, whether it is read-only, and any prerequisites (e.g., cluster access). The description is too minimal to be considered complete, even for a simple get operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the parameters (name, namespace, cluster_alias). While the names are relatively self-explanatory, the description adds no meaning beyond the schema, failing to compensate for the lack of parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Get), the resource (PersistentVolumeClaim), and the scope (specific). It distinguishes from the sibling tool list_pvcs by focusing on a single resource. The verb and resource 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.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The word 'specific' implies this tool is for retrieving one PVC, and the sibling list_pvcs is for listing, but there is no explicit guidance on when to use this tool versus alternatives. The usage context is implied but not clearly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for disclosing behavior. It only states the core enumeration function, revealing nothing about read-only nature, default namespace behavior, cluster selection, or potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, lean sentence with no fluff. It immediately states the action and scope, earning its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description omits critical context like default namespace behavior, cluster override capability, and any prerequisites. For a tool with no annotations, this is insufficient for full understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for its two parameters. The description only hints at the 'namespace' parameter via 'in a namespace', but does not explain the 'cluster_alias' parameter, defaults, or accepted values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'List' against the resource 'ConfigMaps' within a namespace. This distinguishes it from sibling tools like 'get_configmap' by explicitly indicating it lists multiple items rather than fetching one.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as 'get_configmap'. The description simply states the function without any context on selection criteria or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It only states a read-only list operation but fails to mention whether it spans clusters (via cluster_alias), the meaning of the 'default' namespace, or any permission requirements. The lack of clarification on cluster_alias behavior is a significant omission.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. It efficiently states the action and scope, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 optional parameters, no annotations, and an output schema, the description is incomplete. It omits key context about cluster_alias (multi-cluster support) and the default namespace behavior. While the output schema exists, the missing parameter semantics and cluster behavior leave the tool insufficiently specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description mentions 'in a namespace' which hints at the namespace parameter, but does not explain the default value, optionality, or the cluster_alias parameter at all. It fails to add meaning beyond the raw schema definitions, leaving both parameters under-specified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and the resource ('HorizontalPodAutoscalers') with a namespace scope. It distinguishes from sibling tool 'get_hpa' which targets a single HPA, 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.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: use this to list all HPAs in a namespace. However, it does not mention alternatives like 'get_hpa' for a specific HPA or any exclusions (e.g., limitations across clusters or namespaces). Guidance is minimal but not misleading.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It only states 'list' with no additional context such as pagination, output format, permissions, or cluster-specific behavior, which is insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that is front-loaded with the core purpose. It wastes no words and is appropriately sized for the simple action it describes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists, the description is too sparse for a tool with two parameters and no annotations. It provides no context about the cluster_alias option or any usage prerequisites, leaving the agent with incomplete information for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only mentions 'a namespace,' which partially addresses the namespace parameter but completely ignores cluster_alias. It fails to explain how to target a specific cluster, providing minimal added value over the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'list' and identifies the resource 'LimitRanges' with a namespace scope, clearly distinguishing it from sibling list tools for other resources. It is unambiguous about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool vs alternatives or any prerequisites. There is no mention of when to omit or specify the namespace or cluster_alias, leaving the agent without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 only states the action ('list all') with no disclosure of pagination, permission requirements, or whether the operation is strictly read-only (though 'list' implicitly suggests it). Adds little beyond the literal function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with zero filler, immediately conveying the core function. Every word earns its place and the description is front-loaded with the verb 'List'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple, but with two optional parameters and no parameter descriptions, the description does not explain cluster_alias or the namespace default. Output schema exists, but the operation's full semantics (e.g., cluster selection) are not covered, and the description is too sparse to compensate for the missing annotation context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description does not mention 'namespace' or 'cluster_alias' parameters at all. The agent must guess that 'in a namespace' maps to the namespace parameter, and cluster_alias is entirely unexplained, leaving the agent without essential information to invoke the tool correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb+resource+scope ('List all PersistentVolumeClaims in a namespace'), clearly distinguishes from the sibling get_pvc by emphasizing 'all' rather than a single resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage: use when you need to enumerate all PVCs in a namespace. No explicit comparison with get_pvc or mention of when not to use it, despite having a sibling tool that retrieves a single PVC.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description offers minimal behavioral detail. It does not explain whether scaling is synchronous, if it waits for rollout, permissions required, or behavior on non-existent StatefulSets. Since no annotations exist, the description carries the full burden but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One-sentence description, front-loaded, with no extraneous content. It is as concise as possible while conveying the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutating operation with no annotations and no output schema, the description is too terse. It fails to mention return behavior, error handling, or operational constraints that would help an agent invoke it safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description only implies the 'replicas' parameter via 'specified number of replicas' but does not explain the 'name', 'namespace', or 'cluster_alias' parameters, leaving all but the most obvious semantics uncovered. With 0% schema coverage, the description should compensate but does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool scales a StatefulSet to a specified replica count, using a specific verb and resource. It implicitly distinguishes from sibling tools targeting Deployments (scale_deployment) and DeploymentConfigs (scale_deploymentconfig).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, preconditions, or alternatives. It simply states the action without any context about when to prefer it over other scaling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description merely says 'Delete' without disclosing irreversibility, namespace defaults, or cluster alias behavior. For a destructive action, this is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. The supported kinds list is front-loaded and useful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
As a destructive tool with no annotations and no output schema, the description should explain effects, return values, and error scenarios. It only covers purpose and kind scope, leaving the agent under-informed for such an operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description partially compensates by listing supported kinds for the 'kind' parameter. However, it does not explain the semantics of namespace or cluster_alias beyond defaults already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool deletes a Kubernetes resource by kind and name, listing supported kinds. This distinguishes it from the many read-only tools and the more specific force_delete_pod.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use guidance or mention of alternatives. The supported-kinds list implies scope but does not explain when to use this tool vs force_delete_pod or other deletion methods.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It only says 'Get detailed information' without stating that it is a read-only operation, potential errors, or any security requirements. The verb 'Get' implies read-only, but no explicit transparency is given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no filler. It is front-loaded with the essential information, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple get operation, but with no output schema and no description of return format, error behavior, or the role of cluster_alias, the description is somewhat incomplete. It provides minimal context, leaving some gaps for a tool with three parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not mention any parameters, while the schema has three parameters (name, namespace, cluster_alias). It fails to compensate for the low coverage, adding no meaning beyond the parameter names and defaults already present in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Get) and the resource (specific Job). It distinguishes from list_jobs by indicating 'a specific Job' and 'detailed information', making the tool's purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage is implied: use when you need detailed information on a specific Job. However, there is no explicit guidance on when not to use it or alternatives like list_jobs or get_cronjob. The description gives no exclusions or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It implies a read-only retrieval ('get') but does not disclose permissions, error behavior, response format, or side effects. This is minimal behavioral transparency beyond the verb itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundant wording, fully accomplishing its purpose efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple getter tool, the description is functional but sparse. It lacks output schema details and does not clarify the behavior of the optional cluster_alias parameter, making it minimally complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 2 parameters with 0% description coverage. The description only implies 'name' refers to the node name, but does not explain 'cluster_alias' or its role, nor any constraints on the name field.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves detailed information about a specific node. It uses a specific verb (get) and resource (node), distinguishing it from sibling tools like list_nodes which list all nodes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus alternatives such as list_nodes or get_pod. There is no mention of prerequisites, cluster context, or case-specific scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It only states the list operation without confirming read-only safety, return shape, pagination, or the role of cluster_alias. This is minimal and leaves the agent guessing about side effects or output characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word contributes to understanding the tool's core purpose, making it exceptionally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return value details are not needed. However, the description omits any mention of the cluster_alias parameter and does not clarify the default namespace. For a simple list tool this is borderline adequate, but the missing cluster_alias context prevents a higher score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning to the parameters. It only mentions 'in a namespace,' which restates the namespace parameter name, and gives no explanation of the cluster_alias parameter or the default namespace behavior. The description adds little value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' and clearly identifies the resource as 'CronJobs' scoped 'in a namespace.' This distinguishes it from sibling tools like get_cronjob (specific CronJob) and list_jobs (Jobs), 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.
Usage Guidelines2/5
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. There is no mention of get_cronjob for detailed inspection or list_jobs for Jobs, so the agent is not told how to choose among related list/get tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 only says 'List all StatefulSets in a namespace' without mentioning the default namespace value, the cluster_alias parameter behavior, pagination, or ordering. This is minimal and does not add context beyond the tool name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with zero wasted words. It states the essential action and scope directly, making it appropriately concise for a simple list operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple, and an output schema exists, which reduces the need to describe return values. However, the description omits any mention of the cluster_alias parameter and the default namespace behavior. Given the absence of annotations, this leaves a noticeable gap in contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for parameter meanings. The phrase 'in a namespace' hints at the namespace parameter, but the cluster_alias parameter is completely unexplained. The description fails to fully compensate for the lack of schema-level documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 ('StatefulSets'), and the scope ('in a namespace'), which distinguishes it from sibling tools like get_statefulset or scale_statefulset. The verb+resource+scope is 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.
Usage Guidelines2/5
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 get_statefulset or scale_statefulset. It merely states what the tool does without mentioning any exclusions, prerequisites, or preferred scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden. It clearly indicates a read operation, but does not disclose behaviors like what happens if the deployment is not found, whether authentication is required, or how cluster_alias affects the query. The output schema helps, but the description alone is somewhat minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence that directly states the tool's purpose with no filler. It is appropriately front-loaded and every word contributes meaningful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and only three parameters, the tool is not complex, but the description still lacks key contextual information. It does not explain cluster_alias semantics, doesn't mention the sibling list_deployments_image_info for scenarios needing all deployments, and provides no fallback or error context. The output schema covers return values, but the tool is not contextually complete for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the three parameters (name, namespace, cluster_alias). Names like namespace are self-explanatory, but cluster_alias is ambiguous and could be critical for multi-cluster setups. The description provides zero guidance beyond the schema, so it adds no value here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and clearly identifies the resource ('a specific Deployment') and the data returned (image repository, tag, and version label). This distinguishes it from sibling tools like list_deployments_image_info, which operates across deployments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
'For a specific Deployment' implies a single-deployment use case, but the description does not explicitly mention when to use this over alternatives such as list_deployments_image_info or get_deployment. There is no when-not-to-use guidance, leaving clear context but no exclusions or alternative references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. The verb 'Get' implies a safe read operation, but the description does not disclose any additional behavioral details such as error conditions, response format, or whether the resource must exist. It adds minimal value beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that is front-loaded with the action and resource. There is no wasted verbiage, and it is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, annotations, or parameter descriptions, the description is insufficient for a tool with three parameters. It does not explain what 'detailed information' includes, how cluster_alias affects behavior, or how the return value is structured. The description leaves too much to inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no information about the three parameters (name, namespace, cluster_alias). The description only says 'specific Ingress,' which hints at 'name' but leaves namespace and cluster_alias unexplained. This is a significant gap since the description must compensate for the lack of schema-level descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('specific Ingress'), which is distinct from sibling tools like list_ingresses. The verb and resource are unambiguous, and the scope ('specific') signals that this is a single-object retrieval tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when detailed information about a single Ingress is needed, but it does not explicitly mention when to use this over alternatives (e.g., list_ingresses) or provide exclusions. The guidance is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool returns detailed rule content including all alerting and recording rules, which gives some behavioral context. However, it does not mention read-only nature, error behavior (e.g., not found), or any cluster/namespace handling aspects, so transparency is incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded with the core action and resource. Every word earns its place, with no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 3-parameter schema and no annotations or output schema, the description is too sparse to fully guide invocation. It covers the return value ('all alerting and recording rules') but omits critical context about parameter semantics and selection criteria, making it incomplete for an agent to know how to correctly fetch a specific rule.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate by explaining parameters. It does not mention 'name', 'namespace', or 'cluster_alias' at all. The agent is left without any guidance on how to specify which PrometheusRule to fetch or what role each parameter plays, making parameter usage entirely unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('PrometheusRule'), and adds meaningful scope by specifying it includes 'all alerting and recording rules.' This distinguishes it from sibling list_prometheus_rules, which would only list rules without detailed content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when detailed rule information is needed ('Get detailed'), but it does not explicitly mention when to use this tool versus list_prometheus_rules or other siblings. No alternatives or exclusions are provided, leaving the agent to infer the distinction from sibling names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only says 'Get detailed information.' It doesn't mention what fields are returned, if the route must exist, any permission requirements, or potential errors. This is minimal and adds little beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of nine words, front-loaded with the action and resource. No unnecessary words or repetition; it's appropriately concise for a simple getter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but with no annotations, no output schema, and zero parameter descriptions, the description is insufficient for an agent to correctly invoke the tool or understand the response. It lacks guidance on parameter usage and expected return content.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no parameter explanations. The agent must infer that 'name' refers to the route name, but 'namespace' and 'cluster_alias' are not explained at all. The description fails to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: getting detailed information about a specific OpenShift Route. The verb 'Get' and resource 'specific OpenShift Route' distinguish it from listing tools like list_routes. No ambiguity is present.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'specific OpenShift Route' indicates when to use this tool (for a single route by name) versus listing all routes. However, it doesn't explicitly mention alternatives or exclusions, such as 'use list_routes for multiple routes'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 does not state whether the operation is read-only, what permissions are needed, or what 'detailed information' includes. The verb 'Get' implies a read operation, but no further context is given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the verb and resource, and contains no filler. Every word contributes to the core meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is minimal. It does not mention how to specify the name, the role of the optional namespace or cluster_alias, or what kind of information will be returned. The sibling list_statefulsets is not referenced, and the description does not help an agent decide when to drill into a specific resource.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description only hints at the name parameter through the word 'specific' and does not explain the semantics of namespace or cluster_alias. The schema provides defaults but the description adds no additional meaning beyond what the schema already shows.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' with the resource 'StatefulSet' and the qualifier 'specific', clearly indicating a single-object retrieval operation. This cleanly distinguishes it from sibling tools like list_statefulsets or scale_statefulset.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: one would use this when they need details of a specific StatefulSet. However, there is no explicit guidance on when to use this instead of list_statefulsets or scale_statefulset, and no exclusions or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It simply states it lists all BuildConfigs, but does not mention read-only nature, how namespace defaulting works, behavior when the namespace is not found, or how cluster_alias affects the operation. This is a minimal statement that adds little beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short, front-loaded sentence with no wasted words. It efficiently conveys the core action and resource scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and an output schema exists, the description omits key contextual details: the role of cluster_alias, the fact that namespace defaults to 'default', and any guidance on multi-cluster scenarios. Given two optional parameters, the description is under-specified 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.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description does not explain either parameter. It hints at namespace through 'in a namespace' but does not clarify its default value or the meaning of cluster_alias, which is completely absent from the description. The description fails to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' and clearly identifies the resource ('OpenShift BuildConfigs') and scope ('in a namespace'). This distinguishes it from related tools like get_buildconfig (singular retrieval) and list_builds (a different resource).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing all BuildConfigs in a namespace but provides no explicit guidance on when to choose this tool over alternatives, nor any exclusions. It does not mention get_buildconfig for single-item lookups or note that cluster_alias can target different clusters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It states 'List' implying a safe read operation, but it doesn't mention cluster_alias behavior, pagination, or any prerequisites. Important context about targeting a specific cluster is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, no filler, front-loaded with the action. It is appropriately concise, though sparse in detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list tool with an output schema, the description should cover the use of the 2 params, especially cluster_alias. It fails to mention cluster_alias's role in targeting a different cluster, making it incomplete. The output schema fills in return values, but parameter behavior is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 2 parameters with 0% description coverage. The description mentions 'a namespace' which maps to the namespace parameter, but it doesn't explain cluster_alias or add any meaning beyond the schema's basic titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List all OpenShift ImageStreams in a namespace' – a specific verb (List), resource (ImageStreams), and scope (namespace). It distinguishes from sibling get_imagestream by explaining it lists all, not a single.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided about when to use this vs alternatives. The word 'all' implies this is for broad listing, but it doesn't mention get_imagestream for single retrieval or other list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool patches the pod template annotation to trigger a rolling restart, which implies a mutating operation. However, it does not explain side effects such as pod recreation, necessary permissions, or whether the operation is reversible. With no annotations provided, the description carries the full burden but only partially meets it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, concise sentence that communicates the core action and method without unnecessary words. It is front-loaded with the verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and minimal parameter descriptions, the one-sentence description leaves significant gaps. It does not cover when to use the tool, what the parameters mean, what the user should expect after execution, or any safety considerations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero description coverage, and the tool description does not explain the parameters ('name', 'namespace', 'cluster_alias'). The description only references the Deployment, leaving the parameter meanings to be inferred from their names, which may not be sufficient for an agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Trigger a rolling restart') and the resource ('Deployment'), with the mechanism ('patching the pod template annotation'). This distinguishes it from sibling tools like scale_deployment or rollback_deployment by specifying the exact operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides no guidance on when to use this tool versus alternatives such as scale_deployment or rollback_deployment. It only states what it does, leaving the agent to infer the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description is the only behavioral disclosure. It states the action but does not mention side effects (e.g., triggering a rollout, pod termination on scale-down), required permissions, or whether the operation is synchronous. This is a significant gap for a mutating operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no redundant words. It front-loads the core action and resource, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutating tool with no annotations, no output schema, and 4 parameters, the one-sentence description is too sparse. It lacks expected contextual information such as return value, verification method, and resource scope (cluster vs namespace), which are important given the available sibling tools like get_deployment_rollout_status.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero description coverage, and the description adds no parameter semantics beyond what the parameter names convey. It does not explain the meaning of 'name', 'namespace', or 'cluster_alias', nor does it describe acceptable values for 'replicas'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Scale' and clearly identifies the resource type 'Deployment' and the action 'set to specified number of replicas'. It distinguishes from sibling tools like scale_statefulset and scale_deploymentconfig by specifying the exact resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool over alternatives like scale_deploymentconfig or scale_statefulset. The usage is implied by the resource type 'Deployment' but lacks any direct comparison to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the primary action but omits important behavioral details such as whether scaling triggers a rollout, permission requirements, reversibility, or impact on ongoing deployments. This is insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, immediately states the action and target, and contains no redundant information. It is appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity and the absence of annotations and output schema, the description is too minimal. It does not mention prerequisites, side effects (like triggering rollouts), or how it relates to other deployment tools in the sibling list. The 17-word description leaves significant gaps for an agent to reason about.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no context about parameters. It does not explain what 'name' refers to, how 'replicas' is used, or the meaning of 'namespace' and 'cluster_alias'. The bare parameter names in the schema are all the agent has to work with.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Scale' and clearly identifies the resource 'OpenShift DeploymentConfig' and the outcome 'to the specified number of replicas.' It distinguishes from siblings like scale_deployment and scale_statefulset by naming the exact resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for scaling DeploymentConfig resources, which differentiates it from scale_deployment, but it does not explicitly state when to use it versus alternatives or provide any exclusion scenarios. The resource type in the description offers some contextual guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral disclosure burden. It adds 'real-time' as a behavioral trait and clarifies scope ('all nodes'), but it does not mention read-only nature, side effects, authentication, or rate limits. However, 'Get' implies a non-mutating operation, and the command analogy suggests a safe read.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. Every phrase contributes to understanding the tool's core function, and the 'oc adm top nodes' analogy provides immediate recognition without extra verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the output schema exists, the description is incomplete for effective invocation because it omits any explanation of cluster_alias. The lack of annotations and zero schema coverage mean the description is the only source for parameter semantics, and it falls short. The tool is simple, but the missing parameter clarity leaves a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention the cluster_alias parameter at all. The agent receives no explanation of what cluster_alias does, whether it is required (though schema shows it is optional with default null), or how it affects the output. The description fails to compensate for the lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('real-time CPU and memory usage for all nodes'), which clearly states the tool's purpose. It also distinguishes itself from sibling tools like top_pods (pods) and list_nodes (listing nodes) by focusing on node-level resource usage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage via the 'oc adm top nodes' analogy, providing a familiar context, but it does not explicitly state when to use this tool over alternatives like list_nodes or top_pods. There is no mention of exclusions or alternative tools, so guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral burden. It discloses grace_period_seconds=0 and the specific scenario, which adds context. However, it does not explain potential side effects, permission requirements, or irreversibility of force-deletion, leaving gaps in understanding the destructive nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the key action and use case. Every sentence earns its place with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is destructive with no annotations, no output schema, and undefined parameters. The description only covers when to use it, not what the outcome is or what the parameters mean. It feels incomplete for a force-delete operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description does not explain any of the three parameters. While the tool name and description imply that 'name' is the pod name, namespace and cluster_alias are left undefined. The description adds no parameter-level detail, so it does not compensate for the schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool force-deletes a pod stuck in Terminating state, with a specific verb ('Force-delete') and resource ('pod'). It does not explicitly differentiate from sibling tools like force_delete_all_terminating_pods, but the singular focus is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The second sentence provides explicit guidance: 'Use this when a pod will not terminate normally and is stuck.' This gives a clear use case, though it does not mention alternatives or exclusions. It is useful but not full when/when-not coverage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It indicates the action is to 'List', which implies read-only behavior, but does not disclose details such as ordering, pagination, permissions, or side effects. It adds minimal context beyond the tool name, but is not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no redundancy or filler. Every word earns its place, achieving maximum conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While an output schema exists and likely covers return values, the description still needs to provide context for tool selection and input understanding. It provides no parameter semantics or behavioral details, making it only minimally adequate for a simple list operation. The presence of a required 'name' parameter is not even implied in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention any of the three parameters (name, namespace, cluster_alias). It fails to explain how these parameters are used or relate to the Deployment, leaving the agent to rely solely on the unhelpful property names in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists revision history (ReplicaSets) for a Deployment. It uses a specific verb ('List') and resource ('revision history') that distinguishes it from sibling tools like get_deployment or rollout_restart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: you would use this tool when you need the revision history of a Deployment. However, it does not explicitly mention when-not-to-use or alternative tools, leaving the agent to infer its context from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states the scope ('in a namespace') but does not mention behavior such as whether it returns all namespaces if not specified, how cluster_alias affects execution, or any filtering limitations. The description is too terse to be transparent about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, concise sentence that immediately communicates the action and scope. There is no redundant information, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple list operation with an output schema available, so return values are covered. However, the description lacks context about the optional parameters (especially cluster_alias) and does not differentiate this tool from the many similar list tools in the sibling set. It is minimally complete but leaves room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. However, the description does not explain the meaning of 'namespace' or 'cluster_alias' beyond the schema's defaults. While 'namespace' is self-explanatory, 'cluster_alias' is not elaborated, leaving the purpose of this parameter unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('List all'), resource ('OpenShift Builds'), and scope ('in a namespace'). It distinguishes from siblings like 'list_buildconfigs' and 'get_build' by explicitly naming the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit usage guidance is provided. The intended use case (listing builds in a namespace) is implied by the tool name and description, but there is no mention of when to use this over alternatives or any prerequisites. This aligns with 'implied usage' rather than explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden. The verb 'List' implies a safe read operation, and 'all' indicates no filtering. However, it does not disclose behavior around cluster selection (cluster_alias), error handling, or permissions, leaving some gaps for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that immediately states the action and resource. It is front-loaded and contains no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list operation with an output schema, the description is mostly adequate but incomplete. It lacks any mention of cluster_alias, usage alternatives, or behavioral nuances, which prevents it from being fully self-contained given the lack of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains the namespace parameter via 'in a namespace' but completely omits the cluster_alias parameter, which is a significant gap. The default values in the schema are not mentioned either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List all') and the resource ('OpenShift DeploymentConfigs') with a namespace scope. It distinguishes itself from sibling tools like get_deploymentconfig and scale_deploymentconfig by indicating it returns all items, not a single one or an action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. The phrase 'in a namespace' implies it is for enumeration, but it does not mention that get_deploymentconfig should be used for individual resources or any other exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It explains the filtering behavior (pods in error states) and gives a sample list. However, it omits any mention of permissions, cluster/namespace behavior, or side effects. For a read-only list tool this is somewhat acceptable, but the lack of scope disclosure (e.g., how cluster_alias is used) limits transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the core purpose and uses concrete examples to convey the exact criteria. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is relatively simple and an output schema exists, the description lacks any parameter semantics and does not explicitly guide the agent on namespace/cluster scoping or when not to use it. Adequate but incomplete for a tool without annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not mention the parameters (namespace, cluster_alias) at all. The agent gets no help understanding how these parameters affect the query. This is a significant gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') with a resource ('pods') and further scopes it to 'error states' with concrete examples (CrashLoopBackOff, ImagePullBackOff, etc.). This clearly distinguishes it from sibling tools like list_pods and list_pods_not_ready.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (when you want to see failing pods) by listing error states, but it does not explicitly compare with alternatives like list_pods_not_ready or provide explicit exclusion criteria. Usage context is present but understated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states the basic list operation, omitting details about permissions, pagination, filtering, or potential side effects. This is insufficient for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It is as concise as possible while still conveying the core operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists and the tool performs a simple list operation, the description is minimally adequate. However, it fails to explain the cluster_alias parameter, which is important for multi-cluster environments, and lacks usage context despite the presence of many sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention cluster_alias at all. The only parameter-related hint is 'in a namespace', which is already evident from the schema. The description adds little value beyond the parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 Ingresses'), and the scope ('in a namespace'). It is specific and distinguishes itself from the sibling tool 'get_ingress' by emphasizing 'all'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives like 'get_ingress' or 'list_routes'. The usage is implied by the name and description, but no when-not or alternative instructions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. The verb 'List' implies a read-only operation with no side effects, which is a meaningful implicit disclosure. However, the description does not mention any potential caveats like permissions, pagination, or what happens if cluster_alias is omitted. It adds no details beyond the basic read-only implication.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence: 'List all namespaces (projects) in the cluster.' Every word contributes to the meaning, with no fluff or redundancy. It is perfectly concise for the simplicity of the operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one optional parameter, output schema exists), so the minimal description covers the basic functionality. However, the lack of any explanation for the cluster_alias parameter leaves an important gap in usage completeness. For a list operation with an output schema, this is borderline adequate but could be improved by describing the parameter and cluster selection behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description has zero schema coverage (0%) and does not mention the cluster_alias parameter at all. The parameter name and title in the schema are self-explanatory, but the description adds no value in explaining how or when to use it. Since the schema coverage is low, the description was expected to compensate, but it completely fails to do so.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' with a clear resource 'namespaces' and scope 'in the cluster', making its purpose immediately obvious. It also clarifies that 'projects' is an alias for namespaces, which helps distinguish this from sibling tools like list_clusters. The resource type alone is enough to differentiate it from all sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is given on when to use this tool versus alternatives, but the resource type (namespaces) is self-evident and no sibling tool directly overlaps. The optional cluster_alias parameter suggests a context for filtering, but the description doesn't explain when to set it or omit it. Usage is implied rather than clearly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 only states that it lists all ReplicaSets, without mentioning potential large output, cluster selection behavior, or whether the operation is read-only (though 'List' implies it). There is no added context beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly states the tool's purpose with no wasted words. It earns its place and is highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally viable. However, it lacks context about multi-cluster usage (cluster_alias) and any notes on scope or limitations, making it incomplete for a production environment with cluster-aware siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must explain the parameters. It only says 'in a namespace', which adds little beyond the schema property 'namespace'. It completely omits the 'cluster_alias' parameter, its default, or its role in multi-cluster environments.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 ('ReplicaSets'), and the scope ('in a namespace'). It is specific enough to distinguish from sibling get_* tools, and there is no ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a use case (listing ReplicaSets in a namespace) but provides no explicit guidance on when to choose this tool over alternatives, nor does it mention exclusions or prerequisites. It leaves the agent to infer the context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as whether the operation is read-only, requires special permissions, or how it handles the cluster_alias parameter. The description is purely functional with no added 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no extraneous words, achieving high conciseness. Every word contributes to the core meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists and this is a simple list operation, the description is minimal but adequate for basic invocation. However, it omits any mention of cluster_alias or multi-cluster behavior, and there are no annotations to fill the gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation of the parameters. It only implies the namespace parameter via 'in a namespace', leaving cluster_alias completely unexplained. The description does not compensate for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('OpenShift Routes') with clear scope ('in a namespace'), effectively distinguishing it from get_route. It clearly states the action and object.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear context (list all routes in a namespace) but does not explicitly mention when to use this tool versus alternatives like get_route or list_ingresses, nor any exclusions or preconditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the return type (dict mapping container names to log output) but does not mention side effects, limitations, error behavior, or prerequisites. For a read operation this is minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, with the core action front-loaded in the first sentence and the return format in the second. Every word earns its place; no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has seven parameters, no annotations, and the description only covers the primary function and return type. Parameter semantics are entirely missing, and the lack of context on optional flags like previous, tail_lines, or timestamps makes it incomplete for a production tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the seven parameters. It adds no value beyond the schema's property names, failing to compensate for the complete lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and specifies the resource 'logs from ALL containers in a multi-container Pod', which distinguishes it from single-container log tools like get_pod_logs. The return format is also mentioned, removing any ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly communicates the appropriate use case (all containers in a multi-container pod) and mentions the return structure. However, it does not explicitly name alternatives or state when not to use the tool, so it lacks exclusionary guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose what the tool does behaviorally. It explains the exact filter condition for terminating pods (deletion_timestamp set), which is useful. However, it does not disclose details about namespace/cluster scoping, read-only nature (though 'List' implies it), or any potential edge cases. It is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, with the action verb in the first and a precise definition in the second. No filler or redundant details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with an output schema, the description covers the core purpose and filter definition. However, it omits any explanation of the two optional parameters (namespace, cluster_alias), relying entirely on the schema defaults. This leaves some ambiguity about cluster-wide vs per-namespace listing, but overall the essence is captured.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides no descriptions for either parameter (0% coverage), and the description does not mention namespace or cluster_alias at all. Defaults are shown in the schema, but the meaning and scope of these parameters are left entirely to inference. This is a significant gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List pods stuck in Terminating state' – a specific verb and resource with a specific filter. It further defines the filter criterion precisely ('a pod is considered terminating if it has a deletion_timestamp set'), distinguishing it from sibling tools like list_pods or list_failing_pods.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides the criterion that defines terminating pods, which implies when you would want this tool (when you suspect pods are stuck terminating). However, it does not explicitly mention alternatives or when not to use it, such as using force_delete_pod for cleanup or list_pods for all pods.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It reveals useful traits: the first cluster automatically becomes default, and 'set_default=True' changes default status for subsequent registrations. However, it omits important details such as whether credentials are stored, what happens if the alias already exists, or whether connectivity is verified. It adds some context but not enough for full behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a single sentence states the core purpose, followed by two brief, informative sentences about default behavior and optional parameters. Every sentence earns its place without redundancy or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 parameters, no annotations, and an output schema, this description is incomplete. It does not explain how required parameters like 'alias', 'api_url', 'username', and 'password' should be used, nor does it describe potential side effects, error conditions, or preconditions (e.g., network access, valid credentials). The output schema exists but does not compensate for the lack of operational guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It adds meaning for 'oauth_url' (when to provide) and 'set_default' (purpose), but provides no additional explanation for the required parameters: 'alias', 'api_url', 'username', and 'password'. Since 5 of 7 parameters remain undocumented, the description only partially compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Register an OpenShift cluster by acquiring an OAuth token,' which uses a specific verb ('Register'), identifies the resource ('OpenShift cluster'), and differentiates from sibling tools like 'register_standard_clusters' by specifying the mechanism. This clearly states the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage context: it explains when to provide 'oauth_url' and when to set 'set_default=True', and notes the first registered cluster becomes default. However, it does not explicitly contrast this tool with alternatives like 'register_standard_clusters' or state situations where this tool should not be used. Usage is implied but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden. It discloses that it defaults to the previous revision and uses ReplicaSet history, but omits details about permissions, whether it triggers a rollout, or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the main action, and every sentence adds value: the purpose, default behavior, and mechanism are all covered in three sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations, no output schema, and incomplete parameter descriptions, the description is too sparse. It doesn't explain how to find valid revisions, what happens if the revision is invalid, or operational details of the rollback.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only clarifies that 'revision' is optional and defaults to the previous revision; name, namespace, and cluster_alias remain undocumented beyond schema defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear verb and resource: 'Roll back a Deployment to a previous revision.' It also distinguishes itself from sibling tools like rollout_restart and scale_deployment by specifying the rollback action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for rolling back deployments and notes the default behavior when revision is unspecified, but it does not explicitly compare to alternatives like get_deployment_revision_history or explain when to use this tool instead of others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the transparency burden. It adds that the status includes progress and conditions, giving some behavioral context about the return value. However, it does not address read-only nature, potential errors, or prerequisites.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, direct, and front-loaded with the key verb and resource. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and the description covers the core purpose, but without annotations or output schema, it lacks details on parameter behavior and precise return structure. Still, it's adequate for a straightforward get operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any parameter semantics. The schema provides names and types but no descriptions; the tool description adds no value for understanding name, namespace, or cluster_alias.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action (get), resource (Deployment), and specific aspect (rollout status) with details on output content (progress and conditions). This differentiates it from siblings like get_deployment or rollout_restart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies its use for checking rollout progress but provides no explicit when-to-use/when-not-to-use guidance or alternatives. It's inferable from the name, but no exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It does mention key behaviors like the default tail_lines (100), timestamps prepending RFC3339, and previous accessing terminated instances. However, it doesn't address scope behaviors like namespace/cluster alias handling or behavior when no container is specified in a multi-container pod.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with a clear purpose, followed by a bulleted option list. It avoids unnecessary prose, but the option list reads as a parameter reference rather than a narrative, which is slightly less structured for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main logging options but leaves out namespace and cluster_alias, which are part of the schema. It also doesn't provide usage context or alternative tool guidance, making it incomplete for complex multi-cluster scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It explains five of eight parameters (container, tail_lines, since_seconds, timestamps, previous) with clear semantics, but it omits name, namespace, and cluster_alias, which are present in the schema. This is partial compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear, specific verb+resource statement: 'Get logs from a Pod.' This immediately distinguishes it from sibling tools like get_pod (which retrieves pod details) and get_all_container_logs/previous_pod_logs, and the option list reinforces the log-focused scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. While the purpose implies its use for retrieving pod logs, it doesn't mention exclusions or direct the user to sibling tools for specific cases, such as retrieving logs from all containers or previous instances.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source. The verb 'List' inherently conveys read-only behavior, but the description adds no extra behavioral details (e.g., pagination, permissions, scope boundaries). It is accurate but minimally disclosive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly states the operation without extraneous words. It is appropriately concise for a simple list tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is low complexity with an output schema, but the description leaves the 'cluster_alias' parameter unexplained and does not describe the namespace default behavior. Overall, it is sufficient for a basic list but incomplete in parameter context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description only implies the 'namespace' parameter via 'in a namespace,' but does not explain the 'cluster_alias' parameter, which remains ambiguous. Since two optional params exist, the description should compensate but does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the action ('List') and resource type ('AlertmanagerConfig resources'), scoped to a namespace. This clearly differentiates it from sibling list tools for other resource types (e.g., list_prometheus_rules, list_service_monitors).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the resource name—one would use this to list AlertmanagerConfig objects—but the description does not provide explicit guidance on when to choose this over alternatives, no exclusions, and no mention of cluster_alias context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It accurately describes a read-only list operation with no side effects, but adds no details about cluster selection, default behavior, or potential errors. For a simple non-destructive operation, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded with the action and resource, with no unnecessary words. It is perfectly sized for a simple list operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and an output schema exists, which covers return values. However, the description does not explain how cluster_alias affects the operation, leaving a gap in selection context. It is complete for basic invocation but not fully self-explanatory.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the parameters. 'namespace' is inferable from the description, but 'cluster_alias' is completely unexplained. The description fails to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all DaemonSets in a namespace, with a specific verb, resource, and scope. This distinguishes it from siblings like get_daemonset, which retrieves a single DaemonSet.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage is implied: use when you need all DaemonSets in a namespace. However, there is no explicit when-not guidance or mention of alternatives such as get_daemonset for a single resource.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. 'List all' clearly indicates a read-only operation and the namespace scope, but it does not disclose any other behavioral traits such as pagination, permissions, or the effect of cluster_alias. The description is not misleading but is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the key action and resource. Every word is necessary and there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and the output schema exists, but the description fails to explain the cluster_alias parameter and any multi-cluster implications. The overall context is adequate but has clear gaps related to parameter usage and potential edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It only implies the namespace parameter via 'in a namespace' and completely ignores cluster_alias, leaving its purpose and behavior unexplained. The schema itself provides only defaults, so the agent gets little guidance on parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (List) and the resource (NetworkPolicies) with a specific scope (in a namespace). It is distinct from sibling tools as no other tool handles NetworkPolicies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when one needs to list NetworkPolicies, but it does not provide explicit when-to-use/when-not-to-use guidance or mention alternatives. It lacks any context for the cluster_alias parameter or when to choose this over other list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral details. It fails to mention that namespace defaults to 'default' and does not explain the role of cluster_alias. The read-only nature is implied by 'List' but not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, front-loading the verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the operation is simple and an output schema exists, the description omits key context about the default namespace value and cluster_alias semantics. This could lead an agent to mis-invoke the tool when targeting a specific cluster or namespace.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no descriptions for the parameters, and the tool description adds minimal insight. It references 'in a namespace' but does not explain the namespace default or the cluster_alias parameter, which the agent would need to correctly invoke the tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the verb 'List', the resource 'PrometheusRules', and clarifies they are alerting/recording rules, scoped to a namespace. This distinguishes it from sibling get_prometheus_rule which fetches a single rule.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly indicates this tool is for enumerating all PrometheusRules in a namespace, which is the typical use case. However, it does not explicitly mention alternatives or provide when-not-to-use guidance, though for a list tool the use case is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It implies a read-only list operation and adds scope context ('in a namespace', 'Prometheus pod scrape targets'), but does not mention permissions, pagination, or cluster selection behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that states the action and resource immediately. Zero waste, every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with an output schema and defaulted parameters, the description is largely sufficient. It could be more complete by noting how cluster_alias is used or differentiating from ServiceMonitors, but it is not lacking critical information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the two parameters (namespace, cluster_alias) at all. While parameter names are somewhat self-explanatory, the description adds no meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource ('List all PodMonitors') and clarifies scope ('in a namespace') plus a parenthetical explanation ('Prometheus pod scrape targets') that distinguishes it from sibling tools like list_service_monitors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied: use this to list PodMonitors in a namespace. However, it does not explicitly state when to prefer this over alternatives like list_service_monitors or provide any exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing behavior. It implies a read-only comparison and adds context about right-sizing, but it doesn't disclose potential edge cases like missing metrics or permissions. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary action, followed by a practical use case. Every word earns its place with no unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple and has an output schema, so return values are covered. The description gives a clear purpose and usage context. Minor gaps like parameter semantics and edge-case disclosure exist, but overall it is sufficient for basic selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 2 parameters with 0% coverage (no descriptions). The description does not mention namespace or cluster_alias at all, providing no additional meaning. The agent must rely solely on parameter names, which may not be sufficient for cluster_alias.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares actual pod resource usage against configured requests/limits, using a specific verb and resource. It is distinct from sibling tools like top_pods which show raw usage, and the right-sizing purpose further clarifies its niche.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear use case ('right-sizing' and identifying over/under-provisioned pods), giving context for when to use this tool. However, it does not explicitly mention alternatives or when not to use it, so it falls short of a perfect 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full transparency burden. It discloses the default-cluster reassignment side effect, which is valuable, but it does not mention whether the removal is reversible, whether it affects the actual cluster resources, or any permission requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences front-load the core action and add a relevant side effect. Every word earns its place, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter removal tool, the description covers the essential action and an important edge case (default fallback). It lacks explicit irreversibility or permission notes, but the low complexity and schema-provided alias make it sufficiently complete for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description never mentions the 'alias' parameter. The schema only provides the parameter name and title, leaving the description to add no meaning beyond the structured data; the agent must infer that 'alias' identifies the cluster to remove.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'remove' with the resource 'registered cluster', clearly distinguishing it from siblings like register_cluster and list_clusters. It also adds a key behavioral detail about the default cluster, further clarifying the tool's scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states the core action ('Remove a registered cluster') and gives context about the default-cluster fallback, making the usage situation clear. It does not explicitly mention alternatives or exclusions, but none are needed given the tool's specific role among cluster management siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden for behavioral disclosure. It explains that logs come from the previous instance and clarifies that 'previous' means crashed/terminated, which is helpful. However, it does not mention any potential error conditions (e.g., what happens if no previous instance exists), required permissions, or rate limits. The behavior is reasonably transparent for a simple read operation, but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long and front-loaded with the core purpose. The first sentence states the function; the second provides a concise equivalence. There is no redundant wording, and each sentence contributes necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has five parameters, no annotations, and relies on an output schema for return values. The description gives enough context to understand the tool's basic role and its relationship to `get_pod_logs`, but it does not cover parameter details, possible failures, or prerequisites. Given the simplicity of the operation and the existence of an output schema, the description is adequate but not fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not elaborate on any of the five parameters (name, container, namespace, tail_lines, cluster_alias). The only indirect hint is the reference to `get_pod_logs(..., previous=True)`, which implies parameter alignment but does not explicitly explain their meaning or defaults. The schema itself provides only names and types, so the description adds minimal value for parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get logs from the previous (crashed/terminated) instance of a pod container.' It uses a specific verb ('get'), identifies the resource ('previous instance of a pod container'), and distinguishes itself from the sibling `get_pod_logs` by framing it as a shortcut with `previous=True`. This leaves no ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by specifying that it targets logs from crashed/terminated instances and directly references the alternative: 'Shortcut for get_pod_logs(..., previous=True).' This tells the agent when to use this tool (to avoid setting the `previous` flag) and how it relates to the primary tool. However, it does not explicitly state when *not* to use it, such as when live logs are needed, so it falls just short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 discloses the effect on other tools (they will use this default), but does not mention whether the alias must already be registered, whether the setting is persistent, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that directly states the action and its consequence. There is no redundancy or irrelevant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool, the description covers the core purpose and effect on other tools. However, it lacks important context such as prerequisites (e.g., the alias must exist) and does not mention return behavior or errors, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no descriptions for the 'alias' parameter (0% coverage), and the description does not explicitly explain that the parameter is the cluster alias to be set as default. The meaning is only implied by the tool name and context, leaving the agent to infer parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: setting the default cluster. It also explains the context (used when no cluster_alias is provided to other tools), which distinguishes it from sibling cluster management tools such as register_cluster or list_clusters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description effectively communicates when to use this tool: to establish a default cluster so other tools do not need a cluster_alias. It doesn't explicitly name alternatives or exclusions, but for a simple setter this is sufficient contextual guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It communicates that the operation is a read-only 'Get' and adds 'real-time' qualifier, but does not elaborate on permissions, error behavior, or whether results are snapshots. The description is not misleading, but lacks rich behavioral detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the core action and resource. The 'oc adm top pods' analogy adds useful context without extra bulk. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, with an output schema to define return values, so the description does not need to explain output format. However, it lacks any mention of 'cluster_alias' and provides no guidance on choosing between related tools beyond the plural 'all pods'. This leaves some contextual gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains the 'namespace' parameter via 'in a namespace', but completely omits 'cluster_alias', which is a significant parameter given multi-cluster sibling tools. The description adds partial meaning but leaves half the parameters undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get'), resource ('pods'), and scope ('all pods in a namespace'). The analogy to 'oc adm top pods' reinforces functionality and distinguishes it from sibling tools like 'top_pod' (singular) and 'top_nodes' (different resource).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: this is for real-time CPU/memory of all pods in a namespace. While it doesn't explicitly name alternatives, the plural 'all pods' effectively excludes single-pod or node-level tools, providing implicit usage guidance. No exclusions are mentioned, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The verb 'Get' implies a non-mutating read operation, which is the primary behavioral trait. However, without any annotations, the description does not disclose potential permission requirements, cluster context behavior, or side effects. For a simple read tool this is acceptable but leaves some ambiguity about cluster_alias handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single concise sentence that immediately communicates the tool's purpose and output. No unnecessary words or repetition of schema information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (two optional parameters) and an output schema exists, so the description need not detail return values. The core function and scope are covered well. However, the omission of cluster_alias semantics and any default behavior leaves a minor completeness gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for parameter meanings. It references 'a namespace' but does not explain the 'namespace' or 'cluster_alias' parameters. The cluster_alias parameter is entirely unexplained, and its role in selecting a cluster context remains ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets image repository, tag, and version label for all Deployments in a namespace. It uses a specific verb ('Get') and clearly distinguishes itself from siblings like get_deployment_image_info (singular) and list_deployments (which lists deployments, not image info).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly indicates the use case: retrieving image metadata for all Deployments within a namespace. While it does not explicitly exclude alternatives or name sibling tools, the plural scope and mention of 'all Deployments' provide clear context for when to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses a meaningful behavioral trait (sort order) and the namespace scope. However, it does not mention other potentially relevant behavior such as whether system events are included, pagination, or the read-only nature beyond what 'List' implies. The sorting detail adds some value, but the description is not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that directly states the action, scope, and sorting behavior. No wasted words, and the most important information is front-loaded. It earns a perfect score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple listing operation, and an output schema exists to document return values. The description adequately covers the core purpose and sorting. However, it leaves the cluster_alias parameter unexplained, which is a gap given the low schema coverage. For its simplicity, this is nearly complete but not fully so.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does not explain the cluster_alias parameter at all and only implies the namespace parameter through 'in a namespace'. The schema itself provides default values and types, but the description adds insufficient meaning for the parameters, especially cluster_alias which is non-obvious.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('events') with a clear scope ('in a namespace') and a distinguishing behavioral detail (sorted by last timestamp descending). It clearly differentiates from sibling list tools like list_pods or list_services, and the namespace scoping aligns with the namespace parameter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly indicates the tool is for listing events within a namespace, which provides context for when to use it. However, it does not explicitly mention alternatives or when not to use it, such as the more specific get_pod_events. This is a clear context without exclusions, so a 4 is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It states the tool lists both used and hard limits, implying a read-only operation. However, it does not mention permissions, cluster behavior via cluster_alias, or error cases, leaving some transparency gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, compact sentence that leads with the action and resource, then adds the key detail of used vs hard limits. Every word earns its place, and there is no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description covers the core purpose adequately. The main gap is not explaining cluster_alias semantics, but the overall context is sufficient for a basic list operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds nothing about the parameters beyond the schema's names. The namespace parameter is inferred from the text, but cluster_alias is completely unexplained, so the description fails to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource ('List all ResourceQuotas') with clear scope ('in a namespace') and details what is included ('used vs hard limits'). This distinguishes it from sibling tools like list_limit_ranges or list_configmaps.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly conveys the context of when to use this tool: listing ResourceQuotas with usage details. It does not explicitly exclude alternatives or mention when not to use, but the purpose is unambiguous given the resource type.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 adds a useful safety note that no tokens or passwords are exposed, which is a behavioral trait. However, it does not explicitly state that the operation is read-only or that it returns cluster names/IDs, though the output schema may cover the return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that states the purpose and a key safety guarantee. No filler or repetition. It is appropriately front-loaded and structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool with an output schema, the description is nearly sufficient. It could be improved by explicitly distinguishing from 'list_standard_clusters' and noting that it returns all registered clusters, not just standard ones. However, the name and sibling context partially fill this gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the input schema is already complete. The description adds no parameter-specific information, which is unnecessary here. The baseline of 4 applies because the schema covers everything.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('all registered clusters'), clearly stating the tool's function. It implicitly differentiates from sibling 'list_standard_clusters' by emphasizing 'all registered clusters,' indicating a broader scope. The safety note about tokens/passwords is ancillary but does not confuse the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when listing all registered clusters, but it does not explicitly mention alternatives or exclusions. No guidance is provided for when to use 'list_standard_clusters' instead, leaving the agent to infer from the sibling name. This is functional but minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. 'List' implies a read-only operation, and the description specifies what data is returned (aliases and URLs) and the environment scope. However, it does not explicitly state that the operation is side-effect-free or require special permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with the verb and resource upfront, no unnecessary words, and clearly communicates the tool's core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter, read-only list tool with an output schema, the description adequately states the purpose and content. The only minor gap is the lack of explicit guidance on how this differs from 'list_clusters', but the simple nature of the tool makes this non-critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description adds meaning by explaining that the output consists of built-in cluster aliases and API/OAuth URLs for each environment, which helps the agent understand the result without needing parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('standard clusters'), and clarifies the output includes aliases and API/OAuth URLs for dev/uat/prod environments. This distinguishes it from the sibling tool 'list_clusters', which likely lists registered clusters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this is for retrieving built-in cluster information, but does not explicitly state when to use it versus 'list_clusters' or other cluster management tools. No alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosure. It clearly states that secret values are NOT returned, a critical security behavior, and specifies the metadata fields. It does not mention authentication or error behaviors, but for a read-only metadata fetch, this is substantial transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the primary action and resource, then adds a crucial caveat. Every word earns its place with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and the description covers the essential aspects: what is returned and what is not. There is no output schema to explain, and the parameter semantics are partially handled by the schema defaults. It is complete enough for a metadata getter, though it could briefly note that it operates on a single named secret.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for parameter documentation, but it does not mention any parameters at all. The parameter names (name, namespace, cluster_alias) are self-explanatory, but the description adds no additional meaning regarding how they are used or formatted, leaving a clear gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Get' with a clear resource 'Secret metadata' and enumerates exactly what is included (type, keys, labels). It explicitly differentiates itself from list_secrets by focusing on metadata for a single secret, and the warning that values are NOT returned further clarifies scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly conveys that this tool is for retrieving metadata only, not secret values, implying use when metadata is needed without sensitive data. However, it does not explicitly name alternative tools (e.g., list_secrets) or provide when-not-to-use conditions, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the operation returns metadata only and does not expose secret data, which is a key behavioral safety trait. It does not detail permissions, pagination, or performance, but the core non-mutating nature is conveyed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys purpose and key limitations without wordiness. Every part contributes meaningful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two optional parameters and an output schema present, so the description need not detail return values. The core purpose, scope, and safety are covered, though the unexplained cluster_alias parameter and lack of sibling differentiation slightly reduce completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it only references the 'namespace' parameter ('in a namespace') and fails to explain 'cluster_alias'. The parameter meanings are largely left undefined, leaving the agent without adequate semantic guidance for the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all Secrets in a namespace, specifies the scope ('all' and 'in a namespace'), and distinguishes from the sibling get_secret_metadata by noting it returns metadata only. The verb 'List' plus resource 'Secrets' is 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.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for usage: it lists all secrets in a namespace and explicitly notes that no secret data is exposed, indicating safe read-only usage. However, it does not explicitly mention alternatives or exclusion scenarios relative to sibling tools like get_secret_metadata, so it lacks direct 'use this instead' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It discloses the re-authentication/refresh action and the default cluster fallback, but does not mention side effects, permission requirements, or token lifecycle impacts. This is a minimal but non-misleading disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, front-loaded with the main action and followed by the alias behavior. Every sentence earns its place with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description adequately explains the purpose and alias default. It could mention prerequisites for refreshing a token, but the low complexity leaves little missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has only an optional alias parameter with default null and zero description coverage. The description adds essential meaning by explaining that alias selects a cluster and omission causes the default cluster to be used, compensating for the schema's lack of semantic detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool re-authenticates and refreshes the OAuth token for a cluster, using a specific verb and resource. It is easily distinguished from sibling cluster tools like register_cluster or set_default_cluster.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description communicates the action (re-authenticate/refresh token) and clarifies the default-cluster behavior when alias is omitted. It lacks explicit alternatives or when-not-to-use guidance, but the context is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It reveals a key behavior: top-level credentials are used by default for all aliases, and credentials_by_alias can override per alias. However, it does not disclose other behaviors like idempotency, overwriting existing aliases, or side effects, which would be expected for a registration tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences, front-loaded with the main action and immediately followed by essential behavioral notes. No filler or redundant information. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters and no annotations, the description provides enough context for an agent to select and invoke the tool correctly: it explains the core parameters and the default credential behavior. It omits details on verify_ssl and set_default_alias, but these are minor and the output schema exists, so return values are not needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It explains the purpose of username, password, and credentials_by_alias, including the relationship between them. It does not mention verify_ssl or set_default_alias, but these are reasonably self-explanatory from their names and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's specific verb and resource: 'Register all built-in cluster aliases in one call.' This distinguishes it from sibling tools like register_cluster, which presumably registers a single cluster, by emphasizing the bulk 'all built-in' scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool: when you want to register all built-in aliases at once, with an optional per-alias override. It does not explicitly mention alternatives or when not to use it, but the 'in one call' phrasing implies a bulk setup difference from register_cluster.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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