k8s-pilot

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v2.0.0
Disambiguation5/5
Each tool targets a distinct Kubernetes resource or operation (e.g., clusterrole_create vs clusterrole_delete, pod_logs vs pod_detail). There is no ambiguity between tools as they clearly differentiate by resource and action.
Naming Consistency2/5
Tool names mix styles: some use verb_noun (e.g., create_namespace), others use noun_verb (e.g., configmap_create). Additionally, there are inconsistencies like plural vs singular (list_namespaces vs clusterrole_list). This makes naming unpredictable.
Tool Count3/5
57 tools is high for a Kubernetes MCP server. While the scope is broad, many tools are redundant or could be combined (e.g., separate add/remove label tools for namespaces and nodes). The count exceeds typical ranges, but it is still manageable.
Completeness2/5
The server covers various resources but has notable gaps: missing deployment_create and deployment_get, no pod creation, no support for common resources like HPA, NetworkPolicy, or RBAC bindings. This limits its ability to perform complete workflows.
Average 3/5 across 57 of 57 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 9 commits in the last 12 weeks
- Last stable release on July 21, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 carries full burden for behavioral disclosure. While 'Create' implies a write/mutation operation, the description doesn't disclose important behavioral aspects: what permissions are required, whether this is idempotent, what happens if the ClusterRole already exists, or any rate limits. The 'Returns' statement is vague ('Status of the creation operation') without specifying format or possible outcomes.
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 appropriately concise with clear sections (purpose, Args, Returns). Each sentence serves a purpose, though the Args section could be more informative. The structure is front-loaded with the main purpose first, followed by parameter and return 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?
For a Kubernetes ClusterRole creation tool with 3 parameters (including a complex 'rules' array), no annotations, and no output schema, the description is insufficient. It doesn't explain the Kubernetes-specific context, doesn't provide examples of policy rules, doesn't mention error conditions, and the return value description is too vague for practical use.
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 provides minimal parameter guidance. The Args section lists parameters but offers no semantic context: 'rules: List of policy rules' doesn't explain what policy rules are, their format, or examples. For a Kubernetes ClusterRole creation, the 'rules' parameter is complex and critical but receives only a generic description.
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 'Create a ClusterRole in the cluster' which is a specific verb+resource combination. It distinguishes from siblings like clusterrole_get, clusterrole_list, and clusterrole_delete by specifying the creation action. However, it doesn't explicitly differentiate from role_create (which creates Role objects instead of ClusterRole objects).
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. It doesn't mention when to use clusterrole_create versus role_create (for namespace-scoped roles), or when to use this versus modifying existing ClusterRoles. There's also no mention of prerequisites like required permissions or cluster context setup.
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. While 'Get' implies a read operation, the description doesn't specify whether this requires authentication, what format the clusters are returned in, whether there are rate limits, or what happens if the kubeconfig file is missing or malformed. The ':return:' placeholder adds no value.
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 brief but contains a useless ':return:' placeholder that adds no information. The first sentence is clear, but the second fragment wastes space. It's appropriately sized for a simple tool but could be better structured without the placeholder.
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 read operation with no parameters and no output schema, the description is minimally adequate but leaves important questions unanswered. Without annotations or output schema, the description should ideally specify what format the clusters are returned in (list of names? full configurations?) and any authentication requirements, but it doesn't.
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 0 parameters with 100% schema description coverage, so the baseline is 4. The description correctly indicates this is a parameterless operation that retrieves all clusters, which aligns perfectly with the empty input schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Get all clusters from the kubeconfig file' which provides a clear verb ('Get') and resource ('clusters'), but it's somewhat vague about what 'clusters' means in this Kubernetes context. It doesn't distinguish itself from sibling tools like 'get_current_cluster' or 'set_current_cluster' which suggests there might be multiple cluster-related operations.
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. There's no mention of when this tool is appropriate versus 'get_current_cluster' or other cluster-related operations in the sibling list. No context about prerequisites, timing, or exclusions is 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 full burden for behavioral disclosure. It states this is a 'Get' operation which implies read-only behavior, but doesn't explicitly confirm this or mention any side effects. It doesn't disclose authentication requirements, rate limits, error conditions, or what format the 'detailed information' returns. For a Kubernetes tool with security implications, this is inadequate.
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 appropriately concise with a clear purpose statement followed by Args and Returns sections. Every sentence earns its place: the first states the purpose, the next two explain parameters, and the last describes the return. However, the formatting with quotes and line breaks could be cleaner for direct consumption by an AI agent.
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 this is a Kubernetes tool with no annotations, no output schema, and 2 parameters with 0% schema coverage, the description is incomplete. It doesn't explain what 'detailed information' includes, doesn't mention authentication or permission requirements, and doesn't provide error handling guidance. For a tool that interacts with cluster security objects, this leaves significant gaps for an AI agent.
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 description coverage is 0%, so the schema provides no parameter documentation. The description adds basic semantic meaning by explaining that 'context_name' refers to 'The Kubernetes context name' and 'name' refers to 'The ClusterRole name'. However, it doesn't provide format examples, constraints, or explain what happens if parameters are invalid. This provides minimal but essential clarification beyond the bare 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 clearly states the tool's purpose with 'Get details of a specific ClusterRole', which is a specific verb+resource combination. It distinguishes from siblings like clusterrole_list (list vs get details) and clusterrole_create/delete (read vs write operations). However, it doesn't explicitly contrast with role_get (ClusterRole vs Role), which would make it a perfect 5.
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. It doesn't mention when to use clusterrole_get versus clusterrole_list (detailed view vs listing), nor does it specify prerequisites like needing proper Kubernetes context or permissions. The agent must infer usage from the tool name and sibling relationships 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 provided, the description carries full burden but offers minimal behavioral insight. It mentions the return type ('List of ClusterRole basic information') but doesn't cover critical aspects like permissions required, rate limits, pagination, error conditions, or what 'basic information' entails. For a Kubernetes list operation with zero annotation coverage, this is inadequate.
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 efficiently structured with a clear purpose statement followed by separate Args and Returns sections. Every sentence serves a purpose, though the 'Returns' line could be more specific about what 'basic information' includes to improve utility without adding bulk.
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 Kubernetes list tool with no annotations and no output schema, the description is incomplete. It lacks details on authentication needs, potential side effects, response format, error handling, and differentiation from sibling tools. The minimal parameter and return documentation don't compensate for these gaps in a resource-intensive context.
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 description coverage is 0%, but the description includes an 'Args' section that documents the single parameter 'context_name' and its purpose ('The Kubernetes context name'). This adds meaningful semantics beyond the bare schema, though it doesn't elaborate on format constraints or examples. With one parameter fully described, it meets the baseline.
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 verb ('List') and resource ('all ClusterRoles in the cluster'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'clusterrole_get' or 'role_list', which would require more precise scope definition.
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 'clusterrole_get' (for specific ClusterRoles) or 'role_list' (for namespace-scoped Roles). The description only states what it does without contextual usage instructions 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 full burden but offers minimal behavioral insight. It mentions the tool updates an existing DaemonSet and returns status, but lacks details on permissions required, whether it's destructive (e.g., triggers pod restarts), error handling, or rate limits. For a mutation tool with zero annotation coverage, this is insufficient.
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 well-structured with a clear purpose statement followed by Args and Returns sections. It's front-loaded and avoids unnecessary fluff. However, the 'Returns' line is vague ('Status of the update operation') and could be more informative, slightly reducing efficiency.
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 4 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It covers the basic purpose and parameters but lacks critical context like behavioral traits (e.g., side effects), error scenarios, or output details, leaving significant gaps for safe and effective use.
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 description coverage is 0%, so the description must compensate. It lists all four parameters with brief explanations (e.g., 'The new container image to update'), adding meaning beyond the schema's titles. However, it doesn't clarify parameter formats (e.g., image tag syntax) or interactions, providing basic but incomplete semantic context.
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 action ('Update') and resource ('an existing DaemonSet'), specifying it's for an existing resource in a namespace. It distinguishes from siblings like 'daemonset_create' and 'daemonset_delete' by focusing on updates, though it doesn't explicitly contrast with 'daemonset_get' or 'daemonset_list'.
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. It doesn't mention prerequisites (e.g., DaemonSet must exist), compare to sibling tools like 'daemonset_create' for new resources, or specify use cases (e.g., rolling updates vs. other methods). The description only states what it does, not when to apply 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?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a read operation ('Get') but doesn't disclose whether this requires specific permissions, what happens if no cluster is set, error conditions, or the format of the returned cluster information. The ':return:' placeholder suggests output documentation 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief but includes an incomplete ':return:' section that adds no value. The first sentence is clear and front-loaded, but the second fragment is wasted space. It could be more concise by removing the placeholder or expanding it meaningfully.
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 is insufficient for a Kubernetes cluster tool. It doesn't explain what 'current cluster' means in Kubernetes context, how it's determined from kubeconfig, or what the return value contains. For a tool in a complex system like Kubernetes, more context is needed to use it effectively.
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 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description doesn't need to add parameter semantics, and it correctly avoids mentioning any parameters. A baseline of 4 is appropriate for a zero-parameter tool with complete schema coverage.
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 action ('Get') and resource ('current cluster from the kubeconfig file'), making the purpose immediately understandable. It distinguishes from sibling 'get_clusters' by specifying 'current' cluster rather than listing all clusters. However, it doesn't fully differentiate from other read operations like 'clusterrole_get' or 'configmap_get' beyond 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 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. It doesn't mention prerequisites (e.g., having a valid kubeconfig), when this is needed versus 'get_clusters', or any context about Kubernetes operations. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. While 'Get detailed information' implies a read-only operation, it doesn't explicitly state whether this requires specific permissions, what format the JSON output contains, or any rate limits or constraints. For a Kubernetes tool with no annotation coverage, this leaves significant behavioral questions unanswered.
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 well-structured and appropriately sized. It starts with a clear purpose statement, then provides separate sections for Args and Returns. Each sentence serves a distinct purpose without redundancy. The only minor improvement would be integrating the parameter explanations more naturally rather than as separate labeled sections.
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 moderate complexity (2 required parameters, no output schema, no annotations), the description provides basic but incomplete coverage. It explains what the tool does and what parameters mean, but lacks crucial context about when to use it versus siblings, what the JSON output contains, and behavioral constraints. For a Kubernetes namespace details tool, this leaves important gaps in understanding.
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 description coverage is 0%, so the schema provides no parameter descriptions. The description adds basic semantics by explaining that 'context_name' is 'The Kubernetes context name' and 'namespace' is 'The name of the namespace to get details for.' This clarifies what each parameter represents, but doesn't provide format examples, validation rules, or contextual usage guidance. Given the coverage gap, this provides moderate compensation.
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's purpose: 'Get detailed information about a specific namespace.' This specifies the verb ('Get') and resource ('namespace'), making it easy to understand what the tool does. However, it doesn't differentiate from similar tools like 'list_namespaces' or 'get_namespace_resource_quota' among the many sibling tools, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. With numerous sibling tools including 'list_namespaces' and 'get_namespace_resource_quota', there's no indication of when this detailed view is appropriate versus listing namespaces or getting quota information specifically. The description only states what it does, not when to choose 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 carries the full burden of behavioral disclosure. It states the tool returns 'JSON string containing detailed information about the node,' which is minimal but helpful. However, it lacks critical details like whether this is a read-only operation (implied but not stated), error conditions, authentication requirements, or rate limits—important for a Kubernetes tool with potential security implications.
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 appropriately sized and well-structured with clear sections for Args and Returns. Each sentence earns its place by defining the purpose and explaining parameters concisely. However, the 'JSON string' return statement could be more precise (e.g., specifying structure or key fields).
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 complexity (Kubernetes node details), lack of annotations, and no output schema, the description is minimally complete. It covers the basic purpose and parameters but lacks depth on behavioral traits, error handling, or example output. For a tool in a rich sibling set with security implications, more context would improve agent effectiveness.
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 description coverage is 0%, so the schema provides no parameter descriptions. The description adds basic semantics by explaining 'context_name' as 'The Kubernetes context name' and 'node_name' as 'The name of the node to get details for,' which clarifies their roles. However, it doesn't provide format examples, validation rules, or context on how to obtain these values, leaving gaps in usability.
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's purpose as 'Get detailed information about a specific node,' which is a specific verb+resource combination. It distinguishes from siblings like 'list_nodes' (which lists all nodes) and 'get_node_pods' (which focuses on pods on a node). However, it doesn't explicitly contrast with these siblings in the description text itself.
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. It doesn't mention when to choose 'get_node_details' over 'list_nodes' or 'get_node_pods,' nor does it specify prerequisites or contextual constraints beyond the required parameters.
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 read operation ('Get details'), implying it's non-destructive, but doesn't cover critical aspects like authentication requirements, error handling, rate limits, or what 'Detailed information' entails. This is a significant gap for a tool with zero 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first. The Args and Returns sections are structured clearly, though the 'Returns' line is vague. There's minimal waste, but the lack of richer context prevents a perfect score.
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 complexity of Kubernetes operations, no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain the return format, error cases, or dependencies, leaving the agent under-informed for a tool that interacts with cluster resources.
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?
The description lists all three parameters (context_name, namespace, name) with brief explanations, adding meaning beyond the schema's 0% coverage. However, it doesn't elaborate on format constraints, valid values, or examples, leaving the agent with basic but incomplete semantic guidance. Given the low schema coverage, this partially compensates but not fully.
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's purpose: 'Get details of a specific Ingress.' It uses a specific verb ('Get') and resource ('Ingress'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'ingress_list' or 'ingress_update,' which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. It doesn't mention sibling tools like 'ingress_list' for listing multiple ingresses or 'ingress_update' for modifications, nor does it specify prerequisites or exclusions. This leaves the agent without 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 carries full burden for behavioral disclosure. It states this is a 'Get' operation which implies read-only behavior, but doesn't explicitly confirm this is non-destructive. It doesn't mention authentication requirements, rate limits, error conditions, or what format the 'detailed information' returns. For a Kubernetes tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
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 efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence earns its place - the first states what the tool does, the Args section lists parameters, and Returns indicates output type. No wasted words or redundant 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?
For a Kubernetes tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain Kubernetes concepts (context, namespace), doesn't specify what 'detailed information' includes, and provides no error handling or permission guidance. Given the complexity of Kubernetes operations and lack of structured metadata, the description should do more to help an agent use this tool correctly.
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 description coverage is 0%, so the schema provides no parameter descriptions. The description adds basic semantics by listing the three parameters with brief labels (context_name, namespace, name), which helps understand what each parameter represents. However, it doesn't provide format requirements, examples, or explain Kubernetes-specific concepts like what a 'context' is. The description compensates partially but not fully for the schema gap.
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 'Get details of a specific pod' which is a specific verb+resource combination. It distinguishes itself from siblings like pod_list (lists multiple pods) and pod_logs (gets logs rather than general details). However, it doesn't explicitly differentiate from other 'get' tools like pod_get (if that existed) or specify what 'details' encompass.
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. It doesn't mention when to choose pod_detail over pod_list (for a single pod vs multiple), pod_logs (for logs vs general details), or other resource-specific get tools. There's no context about prerequisites or typical use cases.
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 tool retrieves details (implying read-only), but doesn't disclose behavioral traits like error handling (e.g., what happens if the PVC doesn't exist), authentication needs, rate limits, or the format of returned details. For a read operation with zero annotation coverage, this leaves significant gaps.
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 appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by structured Args and Returns sections. There's no wasted text, though the Returns section is vague ('Detailed information')—this is a completeness issue, not conciseness. The structure aids readability without being 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 moderate complexity (3 required parameters, no output schema, no annotations), the description is incomplete. It lacks details on error conditions, output format, and usage context (e.g., how it differs from pv_get). While it covers the basic purpose and parameters, it doesn't provide enough information for reliable agent invocation in a Kubernetes environment with many sibling tools.
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 description coverage is 0%, so the schema provides no parameter descriptions. The description lists the three parameters with brief explanations (e.g., 'The Kubernetes context name'), adding basic semantics beyond the schema's titles. However, it doesn't elaborate on format, constraints, or examples (e.g., valid namespace patterns), leaving room for improvement. With 0% coverage, this partial compensation justifies a baseline 3.
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's purpose with a specific verb ('Get details') and resource ('PersistentVolumeClaim'). It distinguishes itself from siblings like pvc_list (which lists multiple) and pvc_create/delete/update (which modify). However, it doesn't explicitly contrast with pv_get (which gets PersistentVolumes) or other *_get tools, keeping it at a 4 rather than 5.
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. It doesn't mention when to choose pvc_get over pvc_list (for details of a specific claim vs. listing all), nor does it reference prerequisites like needing the PVC to exist. The agent must infer usage from the tool name and parameters 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it's a deletion operation, implying it's destructive, but doesn't specify if it's irreversible, requires specific permissions, has side effects (e.g., on dependent resources), or details error handling. This is a significant gap for a mutation tool with zero 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core action, followed by structured sections for Args and Returns, making it efficient and easy to scan. However, the 'Returns' section is vague ('Status of the deletion operation'), which slightly reduces clarity without being wasteful.
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 complexity of a deletion tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks critical details like behavioral traits, error cases, and return value specifics, making it inadequate for safe and effective use by an AI agent.
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 description coverage is 0%, so the schema provides no parameter details. The description adds minimal semantics by listing parameters ('context_name' and 'name') and their roles, but doesn't explain format, constraints, or examples. This partially compensates for the schema gap but remains basic, aligning with the baseline when schema coverage is low.
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 action ('Delete') and resource ('PersistentVolume from the cluster'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'pv_list' or 'pv_get', though the verb 'Delete' makes its purpose distinct from read operations.
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 when deletion is appropriate compared to updating or other operations. It lacks context about prerequisites, dependencies, or warnings about irreversible actions, which is critical for a destructive operation.
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 full burden. It states this is an update operation but doesn't disclose behavioral traits like whether it overwrites or merges labels, requires specific permissions, has side effects on resources, or provides error handling. The mention of 'Status of the update operation' hints at a response but lacks detail on format or potential outcomes.
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 appropriately sized and front-loaded with the core purpose in the first sentence. The Args and Returns sections add structure without redundancy. However, the example in parentheses ('e.g., labels') could be more integrated, and some sentences like 'Returns: Status of the update operation' are vague, slightly reducing efficiency.
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 3 parameters with 0% schema coverage, no annotations, and no output schema, the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral context, usage guidelines, and detailed output information. For a mutation tool in a complex Kubernetes environment, this leaves significant gaps in understanding how to use it effectively.
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 description coverage is 0%, so the description must compensate. It adds meaning by explaining each parameter's purpose: 'context_name' as Kubernetes context, 'name' as PersistentVolume name, and 'labels' as new labels to apply. This clarifies semantics beyond schema types, but doesn't provide format details (e.g., label structure) or constraints, leaving gaps for the 3 parameters.
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 action ('Update') and resource ('PersistentVolume's metadata') with a specific example ('e.g., labels'). It distinguishes from siblings like pv_create, pv_delete, pv_get, and pv_list by focusing on metadata updates rather than creation, deletion, retrieval, or listing. However, it doesn't explicitly differentiate from pvc_update or other update tools beyond 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 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. It doesn't mention prerequisites (e.g., existing PersistentVolume), exclusions (e.g., cannot update other fields beyond metadata), or when to choose siblings like pvc_update for PersistentVolumeClaims instead. Usage is implied by the name and parameters but not explicitly 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 full burden. It states the action but doesn't disclose behavioral traits like required permissions, whether this is a destructive operation, error conditions, or rate limits. The description adds minimal context beyond the basic operation.
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 appropriately sized and well-structured with clear sections (purpose, Args, Returns). It's front-loaded with the core purpose, though the Args and Returns sections could be slightly more 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 3 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It explains parameters but lacks behavioral context, error handling, permissions, or detailed return format. For a mutation tool in a complex domain like Kubernetes, this leaves significant gaps.
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 description coverage is 0%, but the description provides a brief explanation of each parameter's purpose in the Args section. This adds meaningful semantics beyond the bare schema, though it doesn't fully compensate for the lack of schema descriptions (e.g., no format details for context_name or label_key).
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 action ('Remove a label from a namespace') with a specific verb and resource. It distinguishes from sibling tools like 'add_namespace_label' by specifying removal, but doesn't explicitly differentiate from other label/taint removal tools like 'remove_node_label' or 'remove_node_taint' in terms of scope.
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 is provided. The description doesn't mention prerequisites, when-not-to-use scenarios, or compare it to similar tools like 'remove_node_label' or 'remove_node_taint'. Usage is implied from the name and 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 provided, the description carries full burden but offers minimal behavioral context. It states the tool modifies a node and returns JSON with updated labels, but doesn't disclose critical details like required permissions, whether this is a destructive/mutating operation, potential side effects, error conditions, or rate limits. For a Kubernetes mutation tool, this leaves significant gaps.
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 efficiently structured with a clear purpose statement followed by parameter and return value sections. Every sentence serves a purpose with minimal redundancy. The only minor improvement would be integrating the purpose more seamlessly with the parameter explanations.
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 3-parameter mutation tool with no annotations and no output schema, the description provides basic but incomplete coverage. It explains what the tool does and documents parameters, but lacks crucial behavioral context (permissions, side effects) and detailed return value explanation beyond 'JSON string'. Given the complexity of Kubernetes operations, this leaves the agent with significant uncertainty.
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?
The description lists all three parameters with brief explanations ('The Kubernetes context name', 'The name of the node to modify', 'The label key to remove'), which adds meaningful context beyond the schema's 0% coverage. However, it doesn't provide format examples, validation rules, or explain relationships between parameters, leaving some semantic 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 action ('Remove a label from a node') with specific resource ('node') and operation ('remove label'), making the purpose immediately understandable. It distinguishes from siblings like 'add_node_label' by specifying removal rather than addition, though it doesn't explicitly contrast with 'remove_namespace_label' or other node operations.
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. It doesn't mention when label removal is appropriate versus other node modifications (like taint removal or cordoning), nor does it reference sibling tools like 'add_node_label' or 'remove_node_taint' for context. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 states the tool retrieves details but doesn't specify what 'details' include (e.g., status, pods, events), whether it's read-only (implied by 'Get'), error handling, or authentication needs. For a Kubernetes tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves beyond basic retrieval.
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 appropriately sized and well-structured with a clear purpose statement followed by parameter and return sections. It uses minimal sentences that earn their place by defining the tool and its inputs/outputs. However, the 'Returns' section is vague ('Detailed information'), which slightly reduces efficiency.
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 moderate complexity (3 required parameters, no output schema, no annotations), the description is somewhat complete but has gaps. It covers the purpose and parameters but lacks details on return values, error cases, and usage context. For a Kubernetes retrieval tool, more behavioral and contextual information would enhance completeness, though the basics are present.
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?
The description includes an 'Args' section that lists and briefly describes the three parameters (context_name, namespace, name), adding meaning beyond the input schema, which has 0% description coverage. However, it doesn't provide examples, format details (e.g., namespace naming conventions), or constraints, so it partially compensates for the schema gap but not fully.
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's purpose: 'Get details of a specific ReplicaSet.' It uses a specific verb ('Get') and resource ('ReplicaSet'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'replicaset_list' or 'replicaset_get' (if there were multiple get variants), though the specificity of 'specific ReplicaSet' implies individual retrieval versus listing.
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. It doesn't mention sibling tools like 'replicaset_list' for listing all ReplicaSets or 'replicaset_get' in contrast to other resource-specific get tools. There's no context on prerequisites, such as needing a valid Kubernetes context or namespace, beyond what the parameters imply.
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 states it's a list operation, implying read-only behavior, but doesn't clarify aspects like whether it requires specific permissions, how it handles errors, or if it returns paginated results. For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first followed by parameter and return explanations. Every sentence adds value, though the structure could be slightly improved by integrating parameter details more seamlessly rather than as a separate 'Args' section.
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 low complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the purpose and parameters but lacks details on usage guidelines, behavioral traits, and output specifics (e.g., what 'basic information' includes). For a read operation with no annotations, more context would be beneficial.
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 description coverage is 0%, so the description must compensate. It adds meaning by explaining that 'context_name' is the Kubernetes context name and 'namespace' is the Kubernetes namespace, which clarifies the parameters beyond their titles. However, it doesn't provide details like format examples or constraints, leaving some ambiguity.
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 verb ('List') and resource ('all Roles in a given namespace'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'role_get' or 'clusterrole_list', which would require mentioning it returns basic information for multiple roles rather than detailed single-role data or cluster-wide roles.
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 doesn't mention sibling tools like 'role_get' (for single role details) or 'clusterrole_list' (for cluster-wide roles), nor does it specify prerequisites such as needing proper Kubernetes access. This leaves the agent without context for tool selection.
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 it's a list operation, implying read-only behavior, but doesn't disclose critical details like authentication requirements, rate limits, pagination, error conditions, or what 'basic information' includes. For a Kubernetes tool with no annotations, this is insufficient.
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 appropriately sized and front-loaded with the core purpose in the first sentence. The Args and Returns sections add structure without unnecessary verbosity. However, the 'Returns' section is vague ('List of Secret basic information'), slightly reducing efficiency.
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 complexity of Kubernetes operations, no annotations, no output schema, and 0% schema coverage, the description is incomplete. It lacks details on authentication, error handling, output format, and differentiation from siblings. For a tool with two required parameters and no structured support, more context is needed.
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 description coverage is 0%, so the description must compensate. It lists both parameters ('context_name' and 'namespace') in the Args section, adding basic meaning beyond the schema. However, it doesn't explain what these parameters represent (e.g., Kubernetes context vs. namespace) or provide format examples, leaving gaps in understanding.
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's purpose: 'List all Secrets in a given namespace.' It specifies the verb ('List'), resource ('Secrets'), and scope ('in a given namespace'). However, it doesn't explicitly differentiate from sibling tools like 'secret_get' or 'secret_delete', which would require a 5.
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. With sibling tools like 'secret_get' (for individual secrets) and 'secret_list' (for all secrets), there's no indication of when to choose one over the other. It lacks any context about prerequisites 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 full burden. It states it's a list operation but doesn't disclose behavioral traits like whether it requires specific permissions, how it handles errors, if results are paginated, or what format 'basic information' includes. For a read operation with zero annotation coverage, this leaves significant gaps.
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 efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence adds value, and there's no redundant information. It could be slightly more front-loaded by integrating parameter hints into the main description, but overall it's well-organized and 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 moderate complexity (list operation with 2 required parameters), no annotations, and no output schema, the description is minimally adequate. It covers the purpose and parameters but lacks details on behavior, output format beyond 'basic information', error handling, or usage context. For a tool in a Kubernetes environment with many siblings, it should provide more guidance.
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 description coverage is 0%, so the schema provides no parameter descriptions. The description adds basic semantics by explaining 'context_name' as 'The Kubernetes context name' and 'namespace' as 'The Kubernetes namespace', which clarifies what these parameters represent. However, it doesn't provide format examples, constraints, or how they interact, leaving room for improvement.
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 action ('List all') and resource ('ServiceAccounts') with scope ('in a given namespace'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'serviceaccount_get' or 'serviceaccount_delete', which would require more specific comparison.
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. With sibling tools like 'serviceaccount_get' (for individual ServiceAccounts) and 'serviceaccount_list' (for all in namespace), there's no indication of when to choose one over the other, nor any prerequisites or exclusions mentioned.
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. While 'Delete' implies a destructive mutation, the description doesn't specify whether this is irreversible, what permissions are required, or how errors are handled (e.g., if the service is in use). The return statement is vague ('Status of the deletion operation'), offering minimal insight into outcomes. For a destructive tool with zero annotation coverage, this leaves critical behavioral aspects unclear.
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 well-structured and front-loaded with the core purpose in the first sentence. The Args and Returns sections are clearly separated, making it easy to parse. However, the return statement is overly vague ('Status of the deletion operation'), which slightly reduces efficiency by not conveying useful 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?
For a destructive mutation tool with no annotations and no output schema, the description is incomplete. It lacks critical context such as error conditions, side effects (e.g., impact on dependent resources), and what the return status entails. Given the complexity of Kubernetes service deletion and the absence of structured safety hints, more detailed behavioral guidance is needed for safe and effective use.
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 description coverage is 0%, so the schema provides no parameter descriptions. The description lists the three parameters with brief explanations (e.g., 'The Kubernetes context name'), which adds basic semantics beyond the schema's titles. However, it doesn't clarify format expectations (e.g., valid namespace patterns) or dependencies between parameters, leaving some ambiguity. Given the coverage gap, this provides partial but insufficient compensation.
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 action ('Delete') and resource ('a Service from the specified namespace'), making the purpose unambiguous. It distinguishes itself from sibling tools like service_get, service_list, service_create, and service_update by specifying deletion. However, it doesn't explicitly contrast with other deletion tools like configmap_delete or deployment_delete, which would require more specific differentiation.
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. It doesn't mention prerequisites (e.g., needing proper permissions), when deletion is appropriate, or what happens if the service doesn't exist. With many sibling tools available (e.g., service_get to check existence first), the lack of usage context is a significant gap.
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 states this is an update operation, implying mutation, but lacks critical details: required permissions (e.g., cluster admin vs. namespace-level access), whether changes are reversible, side effects (e.g., pod restarts), rate limits, or what the 'Status of the update operation' entails (success/failure indicators). For a mutation tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and well-structured: a clear purpose statement followed by Args and Returns sections. Every sentence adds value, with no redundant or vague phrasing. It could be slightly more concise by integrating the Args list into the main sentence, but the separation aids readability.
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 complexity (mutation tool in Kubernetes with 4 parameters, nested objects in 'labels'), no annotations, and no output schema, the description is incomplete. It lacks error handling details, authentication requirements, impact on running services, and specifics of the return status. For a tool that modifies cluster state, this leaves the agent under-informed about risks and outcomes.
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 description coverage is 0%, so the schema provides no parameter descriptions. The description adds basic semantics for all four parameters in the Args section, explaining what each represents (e.g., 'The Kubernetes context name'). However, it doesn't provide format details (e.g., label structure, namespace naming conventions), validation rules, or examples, leaving gaps in practical usage guidance.
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 verb ('Update') and resource ('an existing Service's metadata'), with a specific example ('labels'). It distinguishes from siblings like service_create, service_delete, and service_get by focusing on metadata updates rather than creation, deletion, or retrieval. However, it doesn't explicitly differentiate from other update tools (e.g., configmap_update, deployment_update) beyond 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 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. It doesn't mention prerequisites (e.g., existing service), when-not-to-use scenarios (e.g., for creating new services), or direct alternatives among siblings (e.g., service_create for new services, service_get for viewing metadata). The agent must infer usage from the tool name and context 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 provided, the description carries the full burden of behavioral disclosure. It mentions that it 'Create[s] a StatefulSet' and returns 'Status of the creation operation', but lacks critical details: required permissions, whether it's idempotent, error handling, or what the status includes. For a mutation tool with zero annotation coverage, this is insufficient.
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 well-structured with a clear purpose statement followed by Args and Returns sections. It's appropriately sized without unnecessary fluff, though the parameter explanations could be more informative to earn a higher score.
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 complexity (6 required parameters, nested object, no output schema, and no annotations), the description is incomplete. It lacks details on behavioral traits, error cases, output format, and differentiation from siblings, making it inadequate for safe and effective use by an AI agent.
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 description coverage is 0%, so the description must compensate. It lists all 6 parameters with brief explanations (e.g., 'The container image to use'), adding basic meaning beyond the schema's titles. However, it doesn't provide format details, constraints, or examples, leaving gaps in understanding.
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 verb ('Create') and resource ('a StatefulSet in the specified namespace'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'deployment_create' or 'daemonset_create' beyond mentioning StatefulSet specifically, which is implied but not contrasted.
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 'deployment_create' or 'statefulset_update', nor any prerequisites or context for usage. The description only states what it does without indicating appropriate scenarios or constraints.
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 burden but offers minimal behavioral context. It states the operation but doesn't disclose required permissions, whether it's idempotent, typical error conditions, or what 'schedulable' entails. The return format mention is vague ('JSON string containing the result').
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 appropriately sized and front-loaded: the core purpose is stated first, followed by parameter and return details. The structure is clear with labeled sections. No wasted sentences, though the return statement could be more informative.
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 is incomplete for a mutation tool. It lacks details on permissions, side effects, error handling, and the structure of the return JSON. For a Kubernetes node operation, more context is needed for safe and effective use.
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 description coverage is 0%, but the description includes an 'Args' section that documents both parameters with brief explanations. This adds meaningful semantics beyond the bare schema, though it doesn't elaborate on format constraints or provide examples. For 2 parameters, this is adequate but basic.
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 verb ('uncordon') and resource ('a node'), with the parenthetical 'mark as schedulable' providing helpful clarification. It distinguishes from sibling 'cordon_node' by being the opposite operation, though not explicitly mentioned. The purpose 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?
No explicit guidance on when to use this tool versus alternatives is provided. The description doesn't mention prerequisites (e.g., the node must be cordoned first), nor does it reference the sibling 'cordon_node' tool for context. Usage is implied but not articulated.
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 full burden for behavioral disclosure. While 'Update' implies a mutation operation, the description fails to disclose critical behavioral traits: what permissions are required, whether the update is atomic or merges with existing data, what happens if the ConfigMap doesn't exist, error conditions, or rate limits. The return value description ('Status of the update operation') is vague and unhelpful.
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 well-structured with clear sections (purpose, Args, Returns) and uses minimal words to convey essential information. The opening sentence directly states the tool's purpose, and parameter descriptions are terse but informative. No redundant or unnecessary 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?
For a mutation tool with 4 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks crucial context about behavioral implications (permissions, error handling, idempotency), doesn't explain the return format despite mentioning it, and provides no guidance on usage relative to sibling tools. The parameter documentation helps but doesn't compensate for missing behavioral transparency.
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?
With 0% schema description coverage, the description adds significant value by documenting all 4 parameters in the Args section, explaining what each parameter represents. It clarifies that 'data' contains 'The new data to update in the ConfigMap,' which provides semantic meaning beyond the schema's generic object type. However, it doesn't specify format expectations for 'data' or provide examples.
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 action ('Update') and resource ('an existing ConfigMap in the specified namespace'), making the purpose immediately understandable. It distinguishes from sibling tools like configmap_create, configmap_delete, configmap_get, and configmap_list by specifying it's for updating existing ConfigMaps. However, it doesn't explicitly differentiate from other update tools like daemonset_update or deployment_update beyond 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 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. It doesn't mention prerequisites (e.g., ConfigMap must exist), when not to use it, or how it differs from similar update operations on other resources. With many sibling tools including configmap_create and configmap_delete, the lack of comparative context leaves the agent without 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action is deletion but lacks critical details: whether this is destructive (likely yes, but not confirmed), if it requires specific Kubernetes RBAC permissions, what happens to associated resources (e.g., pods, services), or error handling (e.g., if deployment doesn't exist). The return statement is vague ('Status of the deletion operation') without specifying format or possible outcomes.
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 efficiently structured with a clear purpose statement followed by parameter and return sections. Every sentence serves a purpose: the first states the action, the next three define parameters, and the last describes returns. It's front-loaded with the core functionality, though the return statement could be more specific.
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 destructive operation like deletion with no annotations and no output schema, the description is incomplete. It lacks crucial context: safety warnings, permission requirements, impact on related resources, and detailed return value expectations. Given the complexity and risk of deleting Kubernetes deployments, more behavioral and operational guidance is 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 description explicitly lists and briefly defines all three parameters ('context_name', 'namespace', 'name'), adding meaningful context beyond the schema which has 0% description coverage and only provides titles. This compensates well for the schema's lack of documentation, though it doesn't elaborate on parameter formats (e.g., namespace naming conventions) or examples.
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 action ('Delete') and resource ('a Deployment from the specified namespace'), making the purpose immediately understandable. It distinguishes from siblings like 'deployment_create' or 'deployment_update' by specifying deletion, though it doesn't explicitly contrast with other deletion tools like 'namespace_delete' or 'pod_delete'.
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. While the description implies it's for deleting deployments, it doesn't mention prerequisites (e.g., needing proper permissions), consequences (e.g., pods being terminated), or when to choose other deletion tools like 'namespace_delete' for broader cleanup.
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 burden for behavioral disclosure. It states this is an update operation but doesn't mention whether it's idempotent, what permissions are required, whether it triggers a rolling update, or potential side effects. The return statement is vague ('Status of the update operation').
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 well-structured with a clear purpose statement followed by Args and Returns sections. It's appropriately sized for a 5-parameter tool, though the return statement could be more specific to improve front-loading of 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?
For a mutation tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what happens during the update (rolling restart? downtime?), error conditions, or what the return status contains. The sibling tools list shows this is part of a Kubernetes management system, but no Kubernetes-specific context is provided.
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?
Schema description coverage is 0%, so the description must compensate. It provides clear explanations for all 5 parameters beyond their titles, explaining what each represents (e.g., 'The Kubernetes context name', 'The new container image to update'). This adds significant value over the bare 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 clearly states the action ('Update') and resource ('an existing Deployment in the specified namespace'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'deployment_create' or 'deployment_delete', which would be needed for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'deployment_create' or 'deployment_get'. It mentions the namespace context but doesn't explain prerequisites, dependencies, or typical scenarios for deployment updates.
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 an update operation, implying mutation, but lacks details on permissions required, whether changes are idempotent or reversible, error handling, or rate limits. The return statement is vague ('Status of the update operation'), offering minimal insight into outcomes.
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 well-structured with a clear opening sentence followed by an 'Args' and 'Returns' section. It's appropriately sized for a 6-parameter tool, though the return statement could be more informative. There's no wasted text, and information is front-loaded effectively.
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 6 parameters, 0% schema coverage, no annotations, and no output schema, the description is insufficient. It covers basic parameter semantics but lacks critical behavioral details (e.g., side effects, error cases) and output specifics, leaving the agent under-informed for safe and effective use.
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?
Schema description coverage is 0%, so the description must compensate. It lists all six parameters with brief explanations (e.g., 'The new host for the Ingress'), adding meaningful context beyond the schema's titles. However, it doesn't specify formats (e.g., for 'host') or constraints (e.g., valid port ranges), leaving some 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 verb ('Update') and resource ('an existing Ingress'), and specifies the scope ('in the specified namespace'). It distinguishes from sibling tools like 'ingress_create' and 'ingress_delete' by focusing on updates, though it doesn't explicitly contrast with them. The purpose is specific and actionable.
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 like 'ingress_create' for new resources or 'ingress_get' for inspection. It mentions no prerequisites, constraints, or typical scenarios for updates, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Create a Role' and mentions a return value ('Status of the creation operation'), but lacks critical behavioral details: required permissions, whether creation is idempotent, error conditions (e.g., duplicate names), or side effects. For a mutation tool with zero annotation coverage, this is insufficient.
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 well-structured and appropriately sized. It front-loads the purpose in one sentence, followed by a clear 'Args' and 'Returns' section. Every sentence earns its place, with no redundant information. Minor improvement could be made by integrating the sections more seamlessly, but it's highly efficient.
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 complexity (Kubernetes role creation), lack of annotations, no output schema, and 0% schema description coverage, the description is incomplete. It doesn't explain what a 'Role' is, the format of 'rules', potential errors, or the meaning of the return 'Status'. For a tool with significant context, this leaves too many gaps for effective agent use.
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?
Schema description coverage is 0%, so the description must compensate. It lists all 4 parameters with brief explanations, adding meaning beyond the bare schema (e.g., 'context_name: The Kubernetes context name'). However, it doesn't explain the structure of 'rules' (policy rules) or provide examples, leaving some ambiguity. Since it documents all parameters, it scores above baseline but not perfectly.
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 verb ('Create') and resource ('a Role in the specified namespace'), making the purpose unambiguous. It distinguishes from siblings like 'clusterrole_create' by specifying 'Role' (namespace-scoped) vs 'ClusterRole' (cluster-scoped). However, it doesn't explicitly contrast with other creation tools (e.g., 'deployment_create'), which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. While the name implies creation, there's no mention of prerequisites (e.g., needing proper permissions), when to use 'role_create' vs 'clusterrole_create', or what happens if a role with the same name already exists. The description lacks any contextual usage instructions.
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 burden for behavioral disclosure. It states the action ('Add or update a label') and return format ('JSON string containing the updated namespace labels'), but lacks critical information about whether this is a mutation requiring specific permissions, if it overwrites existing labels, error conditions, or rate limits. For a Kubernetes mutation tool with zero annotation coverage, this is insufficient.
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 well-structured with a clear purpose statement followed by parameter and return sections. It's appropriately sized with no redundant information, though the 'Args:' and 'Returns:' formatting could be slightly more 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 this is a mutation tool with no annotations and no output schema, the description provides basic purpose and parameter information but lacks important context about permissions, side effects, error handling, and how it differs from similar tools. The return format is mentioned but without schema details.
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?
With 0% schema description coverage, the description provides meaningful parameter documentation through the Args section, explaining all 4 parameters clearly. It adds substantial value beyond the bare schema, though it doesn't specify format constraints (e.g., valid label key patterns) or provide examples.
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 action ('Add or update a label') and the target resource ('on a namespace'), providing specific verb+resource information. However, it doesn't explicitly differentiate from sibling tools like 'remove_namespace_label' or 'add_node_label' beyond the obvious resource difference, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'remove_namespace_label' or 'configmap_update' for similar operations. The description lacks context about prerequisites, permissions needed, or typical use cases for namespace labeling.
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 full burden. It states it's a deletion operation but lacks details on permissions required, whether deletion is reversible, side effects, or error handling. This is a significant gap for a destructive tool with zero 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the main purpose, followed by structured parameter and return sections. It is efficient with no wasted sentences, though the parameter explanations are very brief.
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 destructive tool with no annotations, no output schema, and low schema coverage, the description is incomplete. It misses critical behavioral details like safety warnings, return value specifics, or error conditions, making it inadequate for informed use.
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 description coverage is 0%, but the description adds minimal semantics by listing parameters with brief explanations ('context_name: The Kubernetes context name', 'name: The ClusterRole name'). However, it does not fully compensate for the coverage gap, as it lacks details on parameter formats or constraints.
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 ('Delete') and resource ('ClusterRole from the cluster'), making the purpose specific and unambiguous. It distinguishes from siblings like clusterrole_create, clusterrole_get, and clusterrole_list by focusing on deletion.
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 on when to use this tool versus alternatives is provided. The description does not mention prerequisites, risks, or comparisons to other deletion tools (e.g., role_delete), leaving usage context unclear.
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 burden but offers minimal behavioral insight. It states this is a read operation ('Get details'), but doesn't disclose authentication requirements, error conditions, rate limits, or what 'Detailed information' includes. For a Kubernetes tool with zero annotation coverage, this leaves significant gaps.
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 efficiently structured with a clear purpose statement followed by parameter and return sections. Every sentence earns its place, though the return statement is vague. It's appropriately sized for a simple lookup 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?
Given 3 parameters with 0% schema coverage and no output schema, the description adequately covers parameter semantics but lacks behavioral context and output details. For a read-only Kubernetes tool, it's minimally viable but doesn't address authentication, error handling, or return format specifics that would be helpful.
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 description explicitly documents all three parameters with clear semantic meaning (context_name, namespace, name), adding significant value beyond the 0% schema description coverage. While it doesn't provide format examples or constraints, it fully compensates for the schema's lack of descriptions, making parameters understandable.
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 verb 'Get' and resource 'details of a specific ConfigMap', making the purpose unambiguous. It distinguishes from sibling tools like configmap_list (which lists multiple) and configmap_create/delete/update (which modify). However, it doesn't explicitly contrast with other 'get' tools like configmap_get vs. configmap_list, so it's not a perfect 5.
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. It doesn't mention configmap_list for listing multiple ConfigMaps, or clarify prerequisites like needing proper Kubernetes access. The agent must infer usage from the name and context 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 provided, the description carries full burden but only states it's a list operation. It doesn't disclose behavioral traits like whether it requires specific permissions, how it handles errors, if results are paginated, or what 'basic information' includes. This leaves significant gaps for a Kubernetes 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 efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence earns its place with no redundant information, making it easy to scan and understand quickly.
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 tool with 2 parameters and no output schema, the description covers the basics but lacks context about Kubernetes-specific behaviors (e.g., cluster context switching, namespace existence checks). With no annotations and minimal output explanation ('basic information' is vague), it's adequate but has clear gaps.
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 description coverage is 0%, so the description must compensate. It documents both parameters in the Args section with brief explanations, adding meaning beyond the bare schema. However, it doesn't provide format examples, constraints, or default values, keeping it at a baseline level.
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 verb ('List') and resource ('ConfigMaps') with scope ('in a given namespace'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'configmap_get' or 'pod_list', which would require more specific scope or output details for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'configmap_get' (for single ConfigMap details) or 'list_namespace_resources' (for broader resource listing). It mentions the namespace parameter but doesn't explain usage context or prerequisites.
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 burden for behavioral disclosure. It states this is a creation operation but doesn't mention permissions required, whether it's idempotent, what happens on conflict, or any rate limits. The return format is vaguely described as 'JSON string containing information' without specifying structure. This is inadequate for a mutation tool with zero 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 perfectly structured and concise. It opens with a clear purpose statement, then provides organized parameter documentation in an Args section, followed by return information. Every sentence earns its place with no wasted words, and the information is front-loaded effectively.
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 Kubernetes namespace creation tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It covers parameters adequately but lacks critical behavioral context about permissions, idempotency, error conditions, and the structure of return values. The agent would struggle to use this tool correctly without additional documentation or trial-and-error.
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?
With 0% schema description coverage, the description compensates well by explaining all three parameters in the Args section. It clarifies that 'context_name' is the Kubernetes context, 'namespace' is the name for the new namespace, and 'labels' are optional key-value pairs. This adds significant value beyond the bare schema, though it doesn't provide format examples or constraints.
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 verb ('Create') and resource ('a new namespace'), making the purpose immediately understandable. It distinguishes from siblings like 'delete_namespace' and 'list_namespaces' by specifying creation rather than deletion or listing. However, it doesn't explicitly differentiate from other creation tools like 'configmap_create' or 'deployment_create' beyond 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 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. It doesn't mention prerequisites (e.g., cluster access), when not to use it (e.g., if namespace already exists), or how it relates to sibling tools like 'add_namespace_label' or 'set_namespace_resource_quota'. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states 'Create an Ingress' which implies a write/mutation operation, but doesn't describe permissions required, whether it's idempotent, error conditions, or what 'Status of the creation operation' entails. The description lacks critical behavioral context for a creation tool in a Kubernetes environment.
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 well-structured with clear sections (purpose, Args, Returns) and uses minimal sentences. The first sentence states the core purpose, followed by organized parameter documentation. No wasted words, though the Returns section could be more specific.
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 6-parameter creation tool with no annotations and no output schema, the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral context (permissions, idempotency, error handling) and detailed return value explanation. Given the complexity of Kubernetes resource creation, more guidance would be helpful.
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?
Schema description coverage is 0%, so the description must compensate. The Args section clearly documents all 6 parameters with brief explanations of what each represents (e.g., 'The Kubernetes context name', 'The backend service port'). This adds meaningful semantic context beyond the bare schema, though it doesn't provide format examples or validation rules.
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 action ('Create an Ingress') and the resource ('in the specified namespace'), providing a specific verb+resource combination. It distinguishes from sibling tools like ingress_delete, ingress_get, ingress_list, and ingress_update by specifying creation. However, it doesn't explicitly differentiate from other creation tools like deployment_create or service_create beyond 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 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. It doesn't mention prerequisites (e.g., needing an existing service), when not to use it, or compare it to similar creation tools for other resources. The agent must infer usage from the tool name and parameter list 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?
No annotations are provided, so the description carries full burden. It states 'Delete an Ingress' which implies a destructive mutation, but lacks critical behavioral details: whether deletion is permanent, requires specific permissions, has side effects (e.g., affecting associated services), or provides confirmation. The return statement 'Status of the deletion operation' is vague without specifying format or possible outcomes.
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 well-structured and front-loaded with the core purpose in the first sentence. The Args and Returns sections are organized efficiently. However, the 'Returns' line could be more specific, and there's slight redundancy in repeating 'Kubernetes' for namespace and context.
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 complexity (destructive operation with 3 parameters), no annotations, and no output schema, the description is moderately complete. It covers the basic action and parameters but lacks crucial context: no error handling, no details on return format, no permissions or safety warnings, and no differentiation from sibling tools. For a deletion tool, this leaves significant gaps.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaningful context by explaining each parameter: 'context_name: The Kubernetes context name', 'namespace: The Kubernetes namespace', and 'name: The Ingress name'. This clarifies what each parameter represents beyond the schema's basic titles, though it doesn't provide format examples or constraints.
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 verb 'Delete' and resource 'an Ingress from the specified namespace', making the purpose unambiguous. It distinguishes from siblings like ingress_get, ingress_list, and ingress_update by specifying deletion. However, it doesn't explicitly differentiate from other deletion tools like pod_delete or deployment_delete beyond 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 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. While it's clear this deletes Ingress resources, there's no mention of prerequisites (e.g., whether the Ingress must exist), consequences, or when to choose deletion over other operations like updating. The sibling list includes ingress_create, ingress_get, ingress_list, and ingress_update, but no comparison is made.
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 burden but offers minimal behavioral insight. It mentions the return type ('List of Ingress basic information') but lacks details on permissions needed, rate limits, pagination, error conditions, or what 'basic information' entails. For a read operation in Kubernetes, this leaves significant 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?
The description is well-structured and front-loaded with the core purpose, followed by clear sections for arguments and returns. Every sentence earns its place with no wasted words, 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?
For a simple list operation with 2 parameters and no output schema, the description covers the basics (purpose, args, returns) but lacks depth. Without annotations, it should ideally mention safety (read-only), typical use cases, or error handling to be more complete, though it's minimally adequate.
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 description coverage is 0%, but the description includes an 'Args' section that names and briefly explains both parameters ('context_name' and 'namespace'). This adds meaningful context beyond the bare schema, though it doesn't specify format constraints (e.g., namespace naming rules) or examples.
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 action ('List all Ingresses') and resource ('in a given namespace'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'ingress_get' or 'list_namespace_resources', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'ingress_get' (for specific Ingress details) or 'list_namespace_resources' (for broader resource listing). The description only states what it does, not when it's appropriate.
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 full burden. While 'List all nodes' implies a read operation, it doesn't disclose important behavioral traits like whether this requires specific permissions, whether it's paginated, what 'basic information' includes, or potential rate limits. The description mentions the return format but doesn't describe the structure or fields of the JSON response.
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 appropriately sized with clear sections: purpose statement, Args, and Returns. Each section is front-loaded with essential information. The structure is efficient with zero wasted sentences, though the 'Args' and 'Returns' formatting could be more integrated with the main description.
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 read operation with no annotations, no output schema, and minimal parameters, the description provides basic purpose and parameter explanation. However, it lacks important context about what 'basic information' includes, potential limitations, authentication requirements, or error conditions. Given the complexity of Kubernetes operations and the lack of structured metadata, more behavioral context would be helpful.
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?
With 0% schema description coverage and only 1 parameter, the description adds significant value by explaining that 'context_name' is 'The Kubernetes context name'. This provides essential semantic meaning that the schema lacks. The description doesn't explain what a Kubernetes context is or provide examples, but it does clarify the parameter's purpose beyond the bare 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 clearly states 'List all nodes in the Kubernetes cluster' which is a specific verb+resource combination. It distinguishes from siblings like 'get_node_details' or 'get_node_pods' by indicating it returns basic information about all nodes rather than detailed information or pods. However, it doesn't explicitly differentiate from other list operations like 'list_namespaces' beyond 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 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. It doesn't mention when to use 'list_nodes' versus 'get_node_details' for more detailed information, or 'get_node_pods' for pod information. There's no context about prerequisites or when this operation is appropriate versus other node-related operations.
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 mentions what the tool does but lacks critical details: it doesn't specify if this is a read-only operation (implied by 'Get' but not explicit), whether it requires specific permissions, potential rate limits, or how it handles errors (e.g., if the pod doesn't exist). The description adds minimal behavioral 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized, with a clear purpose statement followed by parameter and return sections. It uses bullet-like formatting for readability and avoids redundant information. However, the 'Returns' section ('Pod logs') is overly simplistic and could be more informative, slightly reducing efficiency.
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 moderate complexity (6 parameters, no annotations, no output schema), the description is partially complete. It covers the purpose and parameters adequately but lacks behavioral details (e.g., safety, error handling) and output specifics. Without an output schema, the return description is vague ('Pod logs'), leaving gaps in understanding the response format or content.
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 description includes an 'Args' section that lists all 6 parameters with brief explanations, adding meaningful semantics beyond the input schema (which has 0% description coverage). For example, it clarifies that 'container' is optional for multi-container pods and 'tail_lines' retrieves lines from the end. This compensates well for the schema's lack of descriptions, though it could provide more detail on parameter interactions or defaults.
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's purpose: 'Get logs from a pod or a specific container within the pod.' This specifies the verb ('Get logs') and resource ('pod' or 'container'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'pod_detail' or 'pod_list', which might also provide log-related information, so it falls short of a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. It doesn't mention prerequisites (e.g., needing a running pod), exclusions (e.g., not for deleted pods), or comparisons to siblings like 'pod_detail' that might offer log summaries. This lack of contextual direction leaves the agent to infer usage scenarios independently.
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 burden for behavioral disclosure. While it states this is a creation operation, it doesn't mention permission requirements, whether this is a mutating operation, potential side effects, error conditions, or what 'Status of the creation operation' actually means. For a Kubernetes resource creation tool, this is a significant gap in 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (Args, Returns) and uses bullet-like formatting. Each sentence earns its place, though the 'Returns' section could be more specific. The front-loaded purpose statement is effective, making this appropriately sized for a 6-parameter 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?
Given the complexity of Kubernetes PersistentVolume creation, no annotations, and no output schema, the description provides basic but incomplete coverage. It documents parameters well but lacks crucial context about permissions, error handling, and what the return status actually contains. For a mutating operation in a complex system, this is minimally adequate but has clear gaps.
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?
With 0% schema description coverage, the description compensates well by listing all 6 parameters with brief explanations and examples. It clarifies what each parameter represents (e.g., 'capacity: The storage capacity (e.g., "10Gi")'), which adds meaningful context beyond the bare schema. The examples for 'capacity' and 'access_modes' are particularly helpful.
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 action ('Create a PersistentVolume') and resource ('in the cluster'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'pv_update' or 'pvc_create' beyond the creation aspect, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like 'pvc_create' (PersistentVolumeClaim) or other volume-related operations. There's no mention of prerequisites, typical use cases, or when not to use this tool, leaving the agent with insufficient contextual guidance.
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 burden for behavioral disclosure. It states the action ('Remove a taint') and return format ('JSON string containing the updated node taints'), but lacks critical details like required permissions, whether this is a destructive/mutating operation, error conditions, or side effects. For a Kubernetes node modification tool, this is insufficient.
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 well-structured with clear sections (purpose, args, returns) and uses minimal, purposeful sentences. The 'Args' and 'Returns' sections are particularly efficient. However, the initial purpose statement could be slightly more informative about the tool's 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?
Given 3 parameters with 0% schema coverage and no output schema, the description provides basic parameter semantics and return format. However, for a Kubernetes node modification tool with no annotations, it lacks crucial context about permissions, side effects, error handling, and relationship to sibling tools. The description is minimally adequate but has significant gaps.
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?
Schema description coverage is 0%, so the description must compensate. It provides clear semantic explanations for all three parameters ('context_name: The Kubernetes context name', 'node_name: The name of the node to modify', 'taint_key: The taint key to remove'), adding meaningful context beyond the bare schema. However, it doesn't explain parameter formats or constraints (e.g., what constitutes a valid taint key).
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 action ('Remove a taint') and target resource ('from a node'), providing specific verb+resource pairing. However, it doesn't explicitly differentiate from sibling tools like 'remove_node_label' or 'add_node_taint', which would require a 5.
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 'add_node_taint' or 'remove_node_label', nor any prerequisites or context for usage. The description only states what it does, not when 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 carries the full burden of behavioral disclosure. It states this is a deletion operation, implying it's destructive, but doesn't specify critical details like whether deletion is irreversible, what permissions are required, potential side effects (e.g., impact on bound subjects), or error handling. For a destructive tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first, followed by parameter details and return information. Every sentence adds value, though the structure could be slightly more polished (e.g., integrating the 'Args' section more seamlessly).
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 complexity (a destructive Kubernetes operation with 3 parameters), no annotations, and no output schema, the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral details (e.g., safety, permissions) and output specifics beyond a vague 'Status of the deletion operation'. For a tool of this nature, more comprehensive guidance is warranted.
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 description includes an 'Args' section that lists and briefly explains all three parameters (context_name, namespace, name), adding meaningful context beyond the schema. With 0% schema description coverage, this compensates well by clarifying what each parameter represents, though it doesn't provide format examples or constraints.
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 action ('Delete') and resource ('a Role from the specified namespace'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'clusterrole_delete' or 'role_get', which would require mentioning it's specifically for Role resources (not ClusterRole) and that it performs deletion (not retrieval).
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 doesn't mention prerequisites (e.g., needing appropriate permissions), when not to use it (e.g., if the Role is in use), or direct alternatives like 'role_get' for checking before deletion. The context is implied (Kubernetes Role management) but not explicitly 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 the full burden of behavioral disclosure. It mentions that values in the data dictionary 'will be base64 encoded', which adds useful context beyond the schema. However, it lacks critical information such as required permissions, whether the operation is idempotent, error handling, or what 'Status of the creation operation' entails, leaving significant gaps 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a brief purpose statement followed by Args and Returns sections, making it easy to parse. It's appropriately sized with no wasted sentences, though the 'Returns' line is vague and could be more informative.
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 complexity of a Kubernetes secret creation tool with 5 parameters, no annotations, and no output schema, the description is moderately complete. It covers parameter semantics well but lacks behavioral details like permissions or error handling, and the return value description is insufficient without an output schema.
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?
Schema description coverage is 0%, so the description must compensate. It provides clear semantics for all 5 parameters, explaining their roles (e.g., 'context_name: The Kubernetes context name', 'data: A dictionary of key-value pairs (values will be base64 encoded)'), and notes the default for secret_type. This adds substantial value beyond the bare 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 clearly states the verb 'Create' and resource 'Secret in the specified namespace', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like secret_update or secret_delete, which would require a 5.
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 secret_update or secret_delete, nor are any prerequisites or context for Kubernetes operations mentioned. The description only states what the tool does, not when 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?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Create' implies a write operation, it doesn't specify permissions required, whether the operation is idempotent, what happens on conflict, or any rate limits. The return statement 'Status of the creation operation' is vague about success/failure indicators.
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 well-structured with clear sections (purpose, Args, Returns). Each sentence serves a purpose, and the parameter explanations are efficient. The front-loaded purpose statement is clear, though the Args section could be slightly more 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?
For a 6-parameter creation tool with no annotations and no output schema, the description covers parameters adequately but lacks important context. It doesn't explain Kubernetes-specific concepts, error conditions, or what the return 'Status' contains. Given the complexity (nested objects, no output schema), more behavioral context would be helpful.
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?
With 0% schema description coverage, the description compensates well by explaining all 6 parameters in the Args section. It clarifies what each parameter represents (e.g., 'selector: A dictionary of labels to select the target pods') and provides examples for complex parameters like ports. This adds significant value beyond the bare 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 clearly states the action ('Create a Service') and specifies the target resource ('in the specified namespace'). It distinguishes from sibling tools like service_get, service_list, service_update, and service_delete by focusing on creation. However, it doesn't explicitly differentiate from other creation tools like deployment_create or pod_create beyond mentioning 'Service'.
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. With many sibling tools including service_update, service_get, and other resource creation tools, there's no mention of prerequisites, when this is appropriate, or what alternatives exist for similar operations.
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 the tool deletes a StatefulSet but doesn't describe critical behaviors: whether deletion is immediate or cascading, if it requires confirmation, what happens to pods and persistent volume claims, or potential side effects. For a destructive operation, this lack of transparency is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, args, returns) and uses minimal words. Every sentence serves a purpose, though the parameter explanations could be more informative. It's appropriately sized for a deletion tool with three parameters.
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 destructive tool with no annotations and no output schema, the description is incomplete. It doesn't explain the deletion behavior (cascading effects, confirmation), return value details beyond 'Status of the deletion operation', error conditions, or permissions required. Given the complexity of Kubernetes StatefulSet deletion, this leaves critical gaps for an agent to understand the tool fully.
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?
The description lists all three parameters with brief explanations, but schema description coverage is 0%, so the schema provides no additional documentation. The parameter explanations are minimal ('The Kubernetes context name', 'The Kubernetes namespace', 'The StatefulSet name') and don't add meaningful context beyond what the parameter names imply. This meets the baseline for when schema coverage is low but doesn't fully compensate.
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 specific action ('Delete') and resource ('a StatefulSet from the specified namespace'), distinguishing it from sibling tools like statefulset_create, statefulset_get, and statefulset_list. It precisely communicates the tool's function without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. It doesn't mention prerequisites (e.g., needing appropriate permissions), when deletion is appropriate, or what happens to associated resources (e.g., persistent volumes). There's no comparison to sibling tools like statefulset_update or general deletion considerations.
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 burden for behavioral disclosure. It mentions the tool modifies a node and returns JSON, but doesn't address critical aspects like whether this requires admin permissions, if it's idempotent, potential side effects, or error conditions. This is inadequate 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 efficiently structured with a clear purpose statement followed by parameter documentation. Every sentence serves a purpose with zero waste, and information is appropriately front-loaded.
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 Kubernetes node mutation tool with no annotations and no output schema, the description provides basic parameter documentation but lacks important context about permissions, side effects, and error handling. It's minimally viable but has clear gaps for a tool that modifies infrastructure.
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?
Schema description coverage is 0%, but the description compensates well by documenting all 4 parameters with clear explanations of what each represents. The Args section adds meaningful context beyond the bare schema, though it doesn't provide format examples or constraints.
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 action ('Add or update a label') and target resource ('to a node'), providing specific verb+resource. However, it doesn't explicitly differentiate from sibling tools like 'remove_node_label' or 'add_node_taint', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 'remove_node_label' or 'add_node_taint'. The description lacks context about prerequisites, permissions needed, or typical use cases for labeling nodes in Kubernetes.
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 full burden. It states this is a creation operation but doesn't disclose behavioral traits like required permissions, whether it's idempotent, error conditions (e.g., duplicate names), or what 'Status of the creation operation' entails. This leaves significant gaps 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 efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence adds value without redundancy, making it 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?
For a mutation tool with no annotations and no output schema, the description is minimally adequate. It covers the basic purpose and parameters but lacks behavioral context, error handling, and detailed return value explanation, which are important for Kubernetes operations.
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?
With 0% schema description coverage, the description compensates well by listing all 4 parameters with brief explanations (e.g., 'The data to store in the ConfigMap'). However, it doesn't provide format details (e.g., data structure expectations) or examples, preventing a perfect score.
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 verb ('Create') and resource ('a ConfigMap in the specified namespace'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like configmap_update or configmap_get, which would be needed for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 like configmap_update or configmap_list. It also doesn't mention prerequisites (e.g., needing appropriate permissions or namespace existence) or contextual constraints.
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 full burden. It states it's a list operation, implying read-only behavior, but doesn't disclose critical traits like authentication needs, rate limits, pagination, error handling, or what 'basic information' includes. For a Kubernetes tool with zero annotation coverage, this leaves significant 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?
The description is well-structured and front-loaded with the core purpose, followed by clear Args and Returns sections. Every sentence earns its place with no wasted words, 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?
Given 2 parameters with 0% schema coverage and no output schema, the description partially compensates by documenting parameters and stating the return type. However, for a Kubernetes list tool with no annotations, it lacks details on authentication, error cases, pagination, and the structure of 'basic information', leaving room for improvement.
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?
Schema description coverage is 0%, so the description must compensate. It explicitly documents both parameters ('context_name' and 'namespace') in the Args section, adding meaning beyond the schema's titles. However, it doesn't explain parameter formats (e.g., string constraints) or provide examples, leaving some ambiguity.
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 verb 'List' and resource 'Deployments' with scope 'in a given namespace', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling list tools like 'daemonset_list' or 'statefulset_list' beyond the resource type, which is implied but not stated.
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. It doesn't mention prerequisites like cluster access, compare it to 'deployment_get' for single deployments, or explain why to choose this over other list tools. Usage context is minimal.
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 full burden. While 'Delete' implies a destructive mutation, it doesn't disclose critical behavioral traits: whether deletion is permanent/reversible, what happens to associated resources (e.g., storage), permission requirements, or error conditions. The return statement ('Status of the deletion operation') is vague without specifying format or possible outcomes.
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 efficiently structured with a clear purpose statement followed by organized Args and Returns sections. Every sentence earns its place: the first states the action, the second lists parameters, the third describes output. No redundant information or unnecessary elaboration.
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 destructive operation with 3 parameters and no annotations/output schema, the description is minimally adequate but incomplete. It covers the basic what and parameters but lacks behavioral context (safety, side effects) and detailed output information. Given the complexity of Kubernetes resource deletion, more guidance on consequences and error handling would be beneficial.
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?
Schema description coverage is 0%, but the description compensates by clearly documenting all three parameters in the Args section with meaningful names and context. Each parameter ('context_name', 'namespace', 'name') is explained in relation to Kubernetes concepts, adding semantic value beyond the bare schema. However, it doesn't provide format examples or validation rules.
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 action ('Delete') and resource ('PersistentVolumeClaim') with scope ('from the specified namespace'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'pvc_delete' vs 'pv_delete' or other deletion tools, which would require mentioning it's specifically for PersistentVolumeClaims rather than PersistentVolumes or other resources.
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. With many sibling deletion tools (e.g., 'pod_delete', 'configmap_delete', 'pv_delete'), there's no indication that this is specifically for PersistentVolumeClaims or when to choose it over other deletion operations. No prerequisites, warnings, or alternative tools are mentioned.
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 burden but only states it's a list operation. It doesn't disclose behavioral traits like whether it requires specific permissions, returns paginated results, handles errors, or provides 'basic information' details. For a read operation in Kubernetes with zero annotation coverage, this is insufficient.
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 perfectly structured and concise: purpose statement, parameter documentation, and return value description in three clear sections. Every sentence earns its place with zero 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 tool with 2 parameters and no output schema, the description covers the basics but lacks important context. It doesn't explain what 'basic information' includes, doesn't mention error handling or permissions, and doesn't differentiate from sibling tools. With no annotations, it should provide more behavioral context for adequate completeness.
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 description explicitly documents both parameters ('context_name' and 'namespace') in the Args section, adding clear meaning beyond the schema which has 0% description coverage. This fully compensates for the schema gap, though it doesn't explain parameter formats or constraints beyond naming them.
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 verb ('List') and resource ('PersistentVolumeClaims') with scope ('in a given namespace'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'pvc_get' or 'pv_list', which would require a 5.
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 like 'pvc_get' (for single PVC details) or 'pv_list' (for PersistentVolumes). It mentions the namespace parameter but doesn't explain usage context or prerequisites.
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 it's a list operation, implying read-only behavior, but doesn't cover aspects like permissions needed, rate limits, pagination, error handling, or what 'basic information' entails. This leaves significant gaps for a tool interacting with Kubernetes.
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 front-loaded with the core purpose, followed by structured sections for arguments and returns. Every sentence earns its place with no wasted words, 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?
Given the complexity of Kubernetes operations and no annotations or output schema, the description is minimally adequate. It covers the purpose and parameters but lacks details on behavior, output format ('basic information' is vague), and usage context. For a read-only list tool, it meets basic needs but leaves room for improvement.
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 description includes an 'Args' section that explains both parameters ('context_name' and 'namespace'), adding meaning beyond the input schema which has 0% description coverage. This compensates well for the schema's lack of descriptions, though it could provide more context on valid values or examples.
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 verb ('List') and resource ('all ReplicaSets in a given namespace'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'replicaset_get' or 'replicaset_update', which would require more specific scope or output 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. It doesn't mention sibling tools like 'replicaset_get' (for a single ReplicaSet) or 'replicaset_list' versus other list tools, nor does it specify prerequisites 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. While 'Get details' implies a read-only operation, it doesn't specify authentication requirements, error conditions, rate limits, or what format the detailed information will be returned in. The description mentions returns 'Detailed information about the Role' but provides no specifics about what that includes.
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 perfectly structured and concise - a clear purpose statement followed by well-organized parameter documentation. Every sentence serves a purpose with zero waste, and the information is front-loaded with the most important details first.
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 read operation with 3 parameters and no output schema, the description provides adequate but minimal coverage. It explains what the tool does and documents the parameters, but lacks information about return format, error handling, or authentication requirements. The absence of an output schema means the description should ideally provide more detail about what 'Detailed information' includes.
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 description provides clear parameter documentation in the Args section, explaining what each parameter represents (context_name, namespace, name). With 0% schema description coverage, this parameter documentation is essential and adds significant value beyond the bare schema. However, it doesn't provide examples or format requirements for the parameters.
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's purpose as 'Get details of a specific Role' with a specific verb ('Get') and resource ('Role'), making it immediately understandable. However, it doesn't explicitly differentiate from its sibling 'clusterrole_get' which performs a similar function for ClusterRoles, leaving some ambiguity about when to use each.
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. With sibling tools like 'role_list' (for listing roles) and 'clusterrole_get' (for cluster-level roles), there's no indication of when this specific role retrieval tool is appropriate versus those other options.
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 discloses the destructive nature ('Delete a namespace and all resources within it'), which is critical, but lacks details on permissions required, irreversibility, potential side effects, or error conditions. For a high-risk mutation tool, this is insufficient.
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 well-structured with a clear purpose statement followed by Args and Returns sections. It's front-loaded with the core action. The only minor inefficiency is the vague 'JSON string' return statement, which could be more specific.
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 high complexity (destructive operation), lack of annotations, and no output schema, the description is incomplete. It misses critical context like safety warnings, authentication needs, error handling, and what the JSON result contains. This leaves significant gaps for safe agent usage.
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?
Schema description coverage is 0%, so the description must compensate. It explicitly lists and describes both parameters ('context_name' and 'namespace') in the Args section, adding meaning beyond the bare schema. However, it doesn't specify format details (e.g., namespace naming conventions).
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 ('Delete') and resource ('namespace and all resources within it'), distinguishing it from sibling tools like 'create_namespace' or 'list_namespaces'. It precisely communicates the destructive scope of the 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?
No guidance is provided on when to use this tool versus alternatives. While the description implies it's for deletion, it doesn't mention prerequisites (e.g., ensuring the namespace exists), exclusions (e.g., system namespaces), or related tools like 'get_namespace_details' for verification.
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 mentions that only labels can be updated, which is useful behavioral context, but doesn't disclose other critical traits such as required permissions, whether the update is idempotent, potential side effects, or error handling. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding the tool's behavior beyond the basic operation.
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 well-structured with a purpose statement followed by 'Args' and 'Returns' sections, making it easy to parse. It's appropriately sized with no redundant information. However, the 'Returns' section is vague ('Information about the updated pod'), which slightly reduces efficiency, but overall it's front-loaded and 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 complexity (a mutation tool with 4 parameters), no annotations, and no output schema, the description is moderately complete. It explains the purpose and parameters well but lacks details on behavioral aspects like permissions, side effects, and return format. For a tool in this context, it should do more to compensate for the missing structured data, making it adequate but with clear gaps.
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?
Schema description coverage is 0%, so the description must compensate. It provides a clear 'Args' section that explains each parameter's purpose (e.g., 'context_name: The Kubernetes context name'), adding meaningful semantics beyond the bare schema. This covers all 4 parameters effectively, though it doesn't detail format constraints or examples. Given the low schema coverage, this is strong compensation, but not exhaustive.
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 'Update an existing pod's metadata (only labels can be updated for an existing pod)' which specifies the verb (update), resource (pod), and scope (metadata/labels). It distinguishes from siblings like pod_create, pod_delete, and pod_detail by focusing on metadata updates rather than creation, deletion, or general details. However, it doesn't explicitly differentiate from configmap_update or other resource updates beyond mentioning it's for pods specifically.
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 updating pod labels, as it states 'only labels can be updated for an existing pod,' which suggests this is the specific use case. However, it doesn't provide explicit guidance on when to use this versus alternatives like pod_create for new pods or other update tools for different resources. No exclusions or prerequisites are mentioned, leaving usage context somewhat implied rather than clearly defined.
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 full burden. It states this is a deletion operation, implying it's destructive, but doesn't disclose critical behavioral traits like whether deletion is permanent, if it requires specific RBAC permissions, what happens to dependent resources, or error conditions. The return statement is vague ('Status of the deletion operation') without specifying format or possible outcomes.
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 efficiently structured with a clear purpose statement followed by parameter explanations and return information. Every sentence earns its place—no wasted words. It's appropriately sized for a straightforward deletion tool with three parameters.
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 this is a destructive operation with no annotations and no output schema, the description is incomplete. It doesn't address safety considerations, permissions, or what the return 'Status' entails. For a deletion tool in a complex system like Kubernetes, more context about behavior and consequences is 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?
Schema description coverage is 0%, so the description must compensate. It provides clear semantic meaning for all three parameters (context_name, namespace, name) in the Args section, explaining what each represents in Kubernetes terms. This adds significant value beyond the bare schema, though it doesn't specify format constraints or examples.
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 specific action ('Delete a ConfigMap') and resource ('from the specified namespace'), distinguishing it from sibling tools like configmap_create, configmap_get, configmap_list, and configmap_update. It uses precise verbs and identifies the exact Kubernetes resource being manipulated.
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. While the purpose is clear, there's no mention of prerequisites (e.g., needing appropriate permissions), consequences (e.g., irreversible deletion), or when to choose deletion over other operations like update. The description assumes the user already knows when deletion is appropriate.
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 tool lists namespaces and returns JSON, but doesn't disclose critical behavioral traits such as whether it requires specific permissions, how it handles errors, if it's read-only or has side effects, or any rate limits. For a Kubernetes tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose in the first sentence, followed by clear sections for arguments and returns. Every sentence earns its place by providing essential information without redundancy. It's appropriately sized for a simple tool with one parameter.
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 low complexity (one parameter, no output schema, no annotations), the description is minimally complete: it states the purpose, explains the parameter, and hints at the return format. However, it lacks details on behavioral aspects like permissions or error handling, which are important for Kubernetes operations. Without annotations or output schema, more context would improve completeness.
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 description includes an 'Args' section that explains the single parameter 'context_name' as 'The Kubernetes context name', adding meaning beyond the schema which has 0% description coverage and only provides a title. This fully compensates for the schema gap, making the parameter clear. However, it doesn't elaborate on format or examples, keeping it from a perfect score.
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's purpose with a specific verb ('List') and resource ('all namespaces in the Kubernetes cluster'), making it immediately understandable. It distinguishes from siblings like 'get_namespace_details' by indicating it lists all namespaces rather than retrieving details for a specific one. However, it doesn't explicitly contrast with 'list_namespace_resources' or 'create_namespace', which would push it to a 5.
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 by specifying it lists all namespaces, suggesting it's for general overview rather than detailed inspection. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_namespace_details' for specific namespace info or 'list_namespace_resources' for resources within namespaces. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It states 'Create a ReplicaSet' which implies a write/mutation operation, but doesn't disclose behavioral traits like required permissions, whether it's idempotent, what happens on failure, or typical response formats. The 'Returns: Status of the creation operation' is vague about what that status includes.
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 well-structured with clear sections (purpose, Args, Returns). Each sentence earns its place, though the 'Returns' statement could be more informative. It's appropriately sized for a 6-parameter creation tool without unnecessary verbosity.
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 mutation tool with 6 parameters, 0% schema coverage, no annotations, and no output schema, the description does an adequate job explaining parameters but lacks crucial context. It doesn't cover error conditions, authentication requirements, or what the return 'Status' actually contains. Given the complexity, it should provide more operational guidance.
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?
Schema description coverage is 0%, so the description must compensate. It provides a clear Args section explaining each of the 6 parameters with meaningful context (e.g., 'The Kubernetes context name', 'Labels to apply to the ReplicaSet'). This adds substantial value beyond the bare schema, though some details like label format expectations could be more specific.
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 'Create' and resource 'ReplicaSet' with specific location 'in the specified namespace.' It distinguishes from siblings like replicaset_delete, replicaset_get, replicaset_list, and replicaset_update by focusing on creation rather than other operations.
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. It doesn't mention prerequisites (e.g., existing namespace, cluster access), compare to similar tools like deployment_create, or specify scenarios where a ReplicaSet is preferred over other workload controllers.
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 the action is a deletion but doesn't clarify if this is destructive, irreversible, requires specific permissions, or has side effects. The mention of 'Status of the deletion operation' hints at a response but lacks detail on format or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by parameter explanations and return information. Every sentence adds value without redundancy, making it appropriately sized and front-loaded for quick understanding.
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 complexity (a destructive operation with 3 parameters), no annotations, and no output schema, the description is minimally adequate. It covers the basic action and parameters but lacks details on behavioral traits, error cases, or output specifics, leaving gaps for safe agent use.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining each parameter's purpose (e.g., 'The Kubernetes context name', 'The Kubernetes namespace', 'The Secret name'), which clarifies their roles beyond the schema's basic titles. However, it doesn't provide format examples or constraints.
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 specific action ('Delete') and target resource ('a Secret from the specified namespace'), distinguishing it from sibling tools like secret_get, secret_list, secret_create, and secret_update. It precisely identifies what the tool does without being vague or tautological.
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 like secret_get or secret_list, nor does it mention prerequisites or exclusions. While the context implies deletion of a specific secret, it lacks explicit usage context compared to siblings.
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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