Kubernetes MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting specific Kubernetes resources and actions, with clear boundaries (e.g., k8s_get_pod vs. k8s_describe_pod for different detail levels). However, some overlap exists, such as k8s_delete_resource potentially covering deletions handled by specific tools like k8s_delete_pod, which could cause minor confusion.
Naming Consistency5/5
Tool names follow a highly consistent k8s_verb_noun pattern throughout, using snake_case uniformly. This predictability makes it easy for agents to understand and navigate the toolset without naming conflicts or style variations.
Tool Count2/5
With 49 tools, the count is excessive for typical MCP server scope, likely overwhelming for agents and leading to decision paralysis. While Kubernetes is complex, this many tools suggests fragmentation rather than a well-scoped, cohesive set.
Completeness5/5
The toolset provides comprehensive coverage of Kubernetes operations, including CRUD for core resources (pods, deployments, services), lifecycle management (scale, restart, rollout), monitoring (logs, events, top), and cluster administration. No obvious gaps exist for the domain.
Average 3/5 across 49 of 49 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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.
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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?
No annotations are provided, so the description carries full burden. It mentions 'Get all common resources' but doesn't disclose behavioral traits like whether this is a read-only operation, requires specific permissions, has rate limits, or what 'common resources' entails (e.g., which Kubernetes resource types). This leaves critical operational details unspecified for a tool in a complex system like Kubernetes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, straightforward sentence that efficiently conveys the core action. It's front-loaded with the main purpose and avoids unnecessary details. However, it could be more structured by specifying what 'common resources' includes, but as-is, it's appropriately concise without waste.
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 and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'common resources' means, the return format, error handling, or prerequisites. For a tool with no structured safety or output information, this leaves significant gaps for an AI agent to operate 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?
The input schema has 100% description coverage, with the 'namespace' parameter clearly documented. The description adds no additional meaning beyond the schema, as it doesn't explain parameter usage, constraints, or defaults. However, with high schema coverage and only one parameter, the baseline score of 3 is appropriate, as the schema adequately handles parameter semantics.
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 the action ('Get all') and target ('common resources in a namespace'), which clarifies the tool's purpose. However, it's vague about what constitutes 'common resources' and doesn't differentiate from sibling tools like k8s_list_pods or k8s_list_deployments, which also retrieve resources. This leaves ambiguity about scope and uniqueness.
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 for listing specific resource types (e.g., k8s_list_pods, k8s_list_services), it fails to specify if this is for bulk retrieval or a specific subset, offering no context for selection. Usage is implied only by the action, not by explicit 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 the full burden of behavioral disclosure. 'Get Ingress details' implies a read-only operation, but it doesn't specify if it returns structured data, YAML, or status information, nor does it mention error handling (e.g., if the ingress doesn't exist) or permissions required. This is a significant gap for a tool with no 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 extremely concise with just three words, which is efficient and front-loaded. However, it may be overly terse, risking under-specification by not providing enough context for effective tool use, though it avoids unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of Kubernetes operations, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'details' include (e.g., configuration, status), return format, or error cases. For a tool with 2 parameters and no structured output, more context is needed to guide the agent 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 100%, with both parameters ('name' and 'namespace') clearly documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. Given the high schema coverage, a baseline score of 3 is appropriate as the schema does the heavy lifting.
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 'Get Ingress details' clearly indicates a read operation on Kubernetes Ingress resources, which is better than a tautology. However, it lacks specificity about what details are retrieved (e.g., configuration, status, rules) and doesn't distinguish it from sibling tools like 'k8s_list_ingresses' or 'k8s_describe_pod', making it vague rather than precise.
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 prefer it over 'k8s_list_ingresses' for listing all ingresses or 'k8s_get_resource_yaml' for raw YAML, nor does it specify prerequisites like cluster access or namespace context. This leaves the agent without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states it 'gets details' without disclosing behavioral traits. It doesn't mention if this is a read-only operation, what permissions are required, whether it returns YAML/JSON, error handling, or rate limits. The description is minimal and lacks context beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, making it easy to parse. However, it's front-loaded but overly brief, potentially under-specifying the tool's scope, which slightly reduces its effectiveness.
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 and lack of annotations or output schema, the description is incomplete. It doesn't explain what 'details' include, the return format, or error cases, leaving gaps for an agent to understand how to use this tool effectively in context with siblings.
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 100%, with clear descriptions for 'name' and 'namespace' parameters. The description doesn't add any meaning beyond the schema, such as explaining parameter interactions or default behaviors. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.
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 'Get StatefulSet details' clearly states the verb ('Get') and resource ('StatefulSet'), but it's vague about what 'details' entails compared to siblings like k8s_list_statefulsets (which lists) or k8s_describe_pod (which might provide more verbose output). It doesn't differentiate from similar get tools like k8s_get_pod or k8s_get_deployment 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. For example, it doesn't mention when to choose k8s_get_statefulset over k8s_list_statefulsets (for listing all) or k8s_describe_deployment (for a different resource), nor does it specify prerequisites like needing a specific namespace or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'Delete a pod' implies a destructive mutation but lacks critical behavioral details: whether deletion is permanent, requires specific permissions, has side effects (e.g., on deployments), or what happens on success/failure. This is inadequate for a destructive operation 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 a single, efficient sentence with zero wasted words. It's front-loaded and immediately conveys the core action, though this brevity contributes to gaps in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's destructive nature, lack of annotations, and no output schema, the description is insufficient. It doesn't cover behavioral traits, usage context, or return values. For a 3-parameter mutation tool in a complex Kubernetes environment, this leaves the agent under-informed.
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 100%, with clear parameter descriptions in the schema. The description adds no parameter semantics beyond the schema, not even hinting at the 'force' parameter's implications. Baseline 3 is appropriate since the schema does the heavy lifting, but the description provides no additional value.
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 'Delete a pod' clearly states the action (delete) and resource (pod), making the purpose immediately understandable. It distinguishes from siblings like 'k8s_delete_resource' by specifying pod deletion, but doesn't fully differentiate from other deletion tools (e.g., 'k8s_delete_configmap') 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 pod existence), when to choose this over 'k8s_delete_resource', or any safety considerations. The agent must infer usage from the 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 but only states the action without behavioral details. It doesn't disclose if this is a read-only operation, requires specific permissions, returns structured data or raw YAML, or has rate limits. 'Get' implies retrieval, but lacks transparency on execution traits.
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 extremely concise with a single phrase, 'Get DaemonSet details', which is front-loaded and wastes no words. It efficiently communicates the core purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool that likely returns complex Kubernetes resource details. It doesn't explain what 'details' include (e.g., status, configuration, metadata) or handle edge cases, leaving significant gaps for an AI agent to infer behavior.
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 100%, with clear parameter descriptions in the schema. The description adds no additional meaning beyond implying retrieval of a DaemonSet, which aligns with the schema. Baseline score of 3 is appropriate as the schema adequately documents parameters.
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 'Get DaemonSet details' clearly states the verb ('Get') and resource ('DaemonSet details'), but it's vague about what specific details are retrieved. It distinguishes from siblings like 'k8s_list_daemonsets' (which lists multiple) by implying retrieval of a single resource, but doesn't explicitly differentiate beyond that.
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. For example, it doesn't mention when to choose 'k8s_get_daemonset' over 'k8s_list_daemonsets' (for listing all) or 'k8s_describe_deployment' (for a different resource type), leaving usage context implied but unspecified.
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. 'Get logs' implies a read-only operation, but it doesn't specify permissions required, potential side effects (e.g., if logs are streamed or fetched), rate limits, or output format (e.g., text, structured data). This leaves significant gaps for a tool that interacts with Kubernetes pods.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence ('Get logs from a pod container') that is front-loaded and wastes no words. It directly states the core function without unnecessary elaboration, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of Kubernetes operations, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., authentication needs, error handling), usage context compared to siblings, and what the logs output looks like, making it inadequate for safe and effective tool invocation.
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 100%, with all 6 parameters clearly documented in the input schema (e.g., 'name' as 'Pod name', 'tail' as 'Number of lines to show from end of logs'). The description adds no additional meaning beyond this, so it meets the baseline of 3 where the schema does the heavy lifting.
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 'Get logs from a pod container' clearly states the verb ('Get logs') and resource ('pod container'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'k8s_describe_pod' or 'k8s_get_pod', which might also provide log-related information or pod details, leaving some ambiguity about when this specific tool is the best choice.
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 (e.g., 'k8s_describe_pod', 'k8s_get_pod', 'k8s_exec_pod'), there's no indication of prerequisites, typical use cases, or distinctions, leaving the agent to infer usage from the 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. It states the tool gets resources as YAML, implying a read-only operation, but doesn't disclose behavioral traits like whether it requires specific permissions, how it handles missing resources, rate limits, or output format details beyond YAML. This is inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration, earning a high score for conciseness.
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 and the lack of annotations and output schema, the description is incomplete. It doesn't explain return values, error handling, or how it interacts with sibling tools, leaving significant gaps for an agent to understand when and how to use this tool 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 100%, so the schema already documents all three parameters (resource_type, name, namespace) with clear descriptions. The description adds no additional meaning beyond what's in the schema, such as examples or constraints, but the high schema coverage justifies the baseline score of 3.
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 'Get any resource as YAML' clearly states the verb ('Get') and resource type ('any resource'), but it's vague about scope and doesn't differentiate from sibling tools like k8s_get_pod or k8s_get_deployment that fetch specific resource types. It lacks specificity about what 'any resource' means in the Kubernetes context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools like k8s_get_pod, k8s_get_deployment, etc., that fetch specific resources, the description doesn't explain why one would choose this generic tool over those specialized ones, nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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. 'Apply' implies a mutation operation that could create or update resources, but the description doesn't disclose critical behavioral traits like required permissions, whether it's idempotent, what happens on conflicts, or typical response formats. This leaves significant gaps for an agent to understand how to use it safely.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core functionality without unnecessary words. It's appropriately sized and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'apply' means in Kubernetes context (create/update), what permissions are needed, what happens on errors, or what the tool returns. For a tool that modifies cluster state, this leaves too many unknowns.
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 100%, so all parameters are documented in the schema. The description mentions 'YAML or JSON manifest' which aligns with the 'manifest' parameter, but adds no additional semantic context beyond what's already in the schema descriptions. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Apply') and resource ('YAML or JSON manifest to the cluster'), making the purpose immediately understandable. However, it doesn't distinguish this from sibling tools like k8s_create_configmap or k8s_update_deployment_image, which also create/update resources in Kubernetes.
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. With many sibling tools for creating specific resources (e.g., k8s_create_configmap) or updating deployments (k8s_update_deployment_image), the description offers no context about whether this is for general manifest application versus specific 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 full burden but offers minimal behavioral insight. It states the tool creates a ConfigMap but doesn't disclose permissions required, whether it's idempotent, what happens on conflicts, or any rate limits. 'From literal values' hints at the data format but lacks operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place by specifying the creation method ('from literal values').
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain the return value, error conditions, or prerequisites like required Kubernetes permissions. The agent lacks context on what 'success' looks like or how to handle failures.
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 100%, so the schema fully documents the three parameters (name, namespace, data). The description adds no additional parameter semantics beyond what's in the schema, such as format constraints or examples for the data object. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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') and resource ('ConfigMap'), specifying it's 'from literal values' which distinguishes it from other creation methods. However, it doesn't explicitly differentiate from sibling tools like k8s_create_secret or k8s_apply_manifest, which could also create 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. There's no mention of when to choose this over k8s_apply_manifest for ConfigMaps, or how it differs from k8s_create_secret. 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. 'Create a new namespace' implies a write/mutation operation, but it doesn't disclose any behavioral traits: no mention of required permissions (e.g., cluster-admin), whether creation is idempotent, what happens if the namespace already exists, or any rate limits. For a mutation tool 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is maximally concise - a single three-word sentence that communicates the core purpose without any wasted words. It's perfectly front-loaded with the essential 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 no annotations and no output schema, the description is insufficiently complete. It doesn't address critical context: what permissions are needed, what happens on success/failure, whether the operation is synchronous, what the return value contains, or how it differs from alternative creation methods. The 100% schema coverage helps with parameters but doesn't compensate for the missing behavioral 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 100% (the 'name' parameter is fully documented in the schema), so the baseline is 3. The description adds no additional parameter information beyond what's already in the schema - it doesn't explain naming constraints, character limits, or validation rules that might apply to namespace names.
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') and resource ('new namespace'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'k8s_apply_manifest' which could also create namespaces, but the verb+resource combination is specific enough for basic understanding.
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 siblings like 'k8s_apply_manifest' (which can create namespaces via YAML) and 'k8s_list_namespaces' (for checking existing namespaces), there's no indication of when this direct creation method is preferred or what prerequisites might be needed.
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/mutation operation, it doesn't disclose critical behavioral traits: whether this requires specific RBAC permissions, whether it's idempotent (overwrites existing secrets?), what happens on failure, or any 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized for a tool with good schema documentation and gets straight to the point without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a Kubernetes secret creation tool with no annotations and no output schema, the description is insufficient. It doesn't cover important context: what permissions are needed, whether it validates secret data format, what happens if the secret already exists, what the return value looks like, or error conditions. 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?
Schema description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description adds minimal value beyond what's in the schema - it mentions 'literal values' which hints at the 'data' parameter being key-value pairs, but this is already clear from the schema. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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') and resource ('generic secret from literal values'), providing a specific verb+resource combination. It distinguishes this from other secret-related tools like 'k8s_get_secret' or 'k8s_delete_secret' by focusing on creation, though it doesn't explicitly differentiate from 'k8s_apply_manifest' which could also create secrets.
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 this over 'k8s_apply_manifest' for secret creation, nor does it specify prerequisites like required permissions or cluster 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?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Delete' implies a destructive mutation, but the description doesn't mention whether this requires specific permissions, whether deletion is permanent, what happens to dependent resources, or any rate limits. For a destructive operation 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple deletion operation and front-loads the essential information immediately.
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 deletion tool with no annotations and no output schema, the description is incomplete. It doesn't address critical context like permission requirements, irreversible nature of deletion, what happens on success/failure, or how this differs from the more general k8s_delete_resource tool. The combination of destructive operation with minimal description creates 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 100%, so the schema already documents both parameters (name and namespace) adequately. The description adds no additional parameter information beyond what's in the schema, which meets the baseline expectation when schema coverage is high.
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 target resource ('a ConfigMap'), providing specific verb+resource combination. However, it doesn't distinguish this tool from other deletion tools like k8s_delete_namespace or k8s_delete_pod, which would require sibling differentiation for a score of 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 k8s_delete_resource (general deletion) and k8s_list_configmaps (for viewing before deletion), there's no indication of when this specific ConfigMap deletion tool is preferred or what prerequisites might be needed.
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 'Delete' implies a destructive operation, it doesn't specify critical details like whether deletion is permanent, what happens to dependent resources, confirmation requirements, or error handling. The description mentions 'force' parameter only indirectly through the schema, but doesn't explain its behavioral implications.
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 extremely concise at just 6 words, front-loading the essential action ('Delete') without any wasted words. Every word earns its place, though this conciseness comes at the cost of completeness in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive operation with no annotations and no output schema, the description is inadequate. It doesn't address critical context like what 'force' deletion means, whether namespaces are required for cluster-scoped resources, what confirmation or safety checks exist, or what the response format looks like. Given the high-stakes nature of deletion in Kubernetes, more guidance 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 100%, so the schema already documents all four parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't clarify parameter relationships, provide examples, or explain edge cases. The baseline of 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 target ('a resource by type and name'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling deletion tools like k8s_delete_configmap or k8s_delete_pod, but the generic nature is appropriate for a tool that handles multiple resource types.
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 the more specific sibling deletion tools (e.g., k8s_delete_pod, k8s_delete_configmap). It also doesn't mention prerequisites like required permissions, context, or namespace considerations, leaving the agent with insufficient context for proper 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 full burden. 'Delete' implies a destructive mutation, but the description doesn't mention whether this is irreversible, requires specific permissions, has side effects on dependent resources, or provides confirmation. For a destructive operation 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 extremely concise at just three words, front-loading the essential information with zero wasted words. Every element earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive deletion tool with no annotations and no output schema, the description is inadequate. It doesn't address behavioral aspects like irreversibility, permissions needed, or what happens to pods using the secret. Given the complexity and risk of the operation, 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 100%, with both parameters ('name' and 'namespace') clearly documented in the schema. The description adds no additional parameter information beyond what's already in the structured schema, meeting the baseline expectation.
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 secret'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like k8s_delete_configmap or k8s_delete_namespace, but the resource type is specified.
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 k8s_delete_resource or k8s_get_secret for inspection before deletion. The description simply states what it does without context about appropriate 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves information ('Get'), implying it's a read-only operation, but doesn't clarify permissions required, rate limits, error conditions, or output format. This is inadequate for a tool that likely interacts with a Kubernetes cluster.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get full description of a deployment') and adds clarifying detail ('including events and conditions') without unnecessary words. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of Kubernetes operations and lack of annotations or output schema, the description is insufficient. It doesn't address behavioral aspects like safety, permissions, or output structure, leaving gaps for an AI agent to correctly invoke this tool in a real-world 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 100%, so the schema fully documents both parameters ('name' and 'namespace'). The description doesn't add any parameter-specific details beyond what the schema provides, such as format examples or constraints, meeting the baseline for high 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 full description') and resource ('deployment'), specifying what information is included ('events and conditions'). It distinguishes from simpler 'get' tools by emphasizing comprehensiveness, though it doesn't explicitly differentiate from sibling 'k8s_describe_pod' or 'k8s_describe_service' 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 like 'k8s_get_deployment' (which might return less detail) or 'k8s_get_resource_yaml' (which might return raw YAML). The description implies it's for detailed inspection but doesn't specify use cases 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, the description carries full burden but only states it retrieves a description with events. It doesn't disclose behavioral traits like read-only nature, permissions needed, rate limits, or output format, leaving significant gaps for a tool in a Kubernetes context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the purpose ('Get full description of a pod') and adds key detail ('including events') without any wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a read-focused tool in a complex Kubernetes environment, the description is incomplete. It lacks details on return values, error handling, or behavioral context needed for 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 100%, so parameters are well-documented in the schema. The description adds no additional meaning beyond implying 'name' and 'namespace' are used to identify the pod, aligning with the baseline for high 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 full description') and resource ('a pod'), specifying it includes events. It distinguishes from siblings like 'k8s_get_pod' by emphasizing comprehensive details, though not explicitly contrasting them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'k8s_get_pod' or 'k8s_get_events' is provided. The description implies usage for detailed pod information but lacks explicit context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but provides minimal behavioral insight. It states the action but doesn't disclose critical traits: whether this is a read-only or destructive operation (e.g., commands like 'rm' could delete files), authentication needs, rate limits, output format (stdout/stderr), or error handling. This is inadequate for a tool that executes arbitrary commands in a container.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste—it directly states the tool's purpose without fluff. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (executing commands in a Kubernetes pod, which can be destructive) and lack of annotations or output schema, the description is incomplete. It fails to address safety, permissions, or result handling, leaving significant gaps for an AI agent to use it correctly in a production environment.
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 100%, so the schema fully documents all parameters (name, namespace, container, command). The description adds no additional meaning beyond the schema's parameter descriptions, such as examples for namespace defaults or command syntax nuances. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Execute a command') and target ('in a pod container'), which is specific and unambiguous. It distinguishes from siblings like k8s_get_pod_logs (read logs) or k8s_describe_pod (inspect), but doesn't explicitly contrast with them, 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?
No guidance on when to use this tool versus alternatives is provided. It doesn't mention prerequisites (e.g., pod must be running), nor does it differentiate from similar operations like shell access or debugging tools. 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves information ('Get'), implying it's a read-only operation, but doesn't confirm this or address other behavioral aspects like permissions required, error handling (e.g., if ConfigMap doesn't exist), or rate limits. The description is minimal and lacks crucial operational context 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 extremely concise—a single, front-loaded sentence that directly states the tool's function without unnecessary words. Every part of the sentence ('Get ConfigMap details and data') contributes essential information, making it efficient and easy to parse. No structural issues or redundancy are 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?
Given the complexity of Kubernetes operations and the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what 'details and data' includes (e.g., metadata, key-value pairs), potential side effects, or return format, leaving gaps for an AI agent to understand the tool's full behavior. For a read operation in a critical system like Kubernetes, 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?
The input schema has 100% description coverage, with clear documentation for both parameters ('name' and 'namespace'). The description doesn't add any parameter-specific details beyond what the schema provides, such as format examples or constraints. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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 ('ConfigMap details and data'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'k8s_list_configmaps' (which lists multiple) and 'k8s_create_configmap' (which creates), though it doesn't explicitly mention these distinctions. The description is specific but could be more precise about what 'details' includes.
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 'k8s_get_configmap' over 'k8s_list_configmaps' (for listing all) or 'k8s_describe_pod' (for different resource types), nor does it specify prerequisites like needing a specific namespace or context. Usage is implied by the name 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 states the tool 'gets' information, implying a read-only operation, but doesn't specify what 'detailed information' includes, whether it requires specific permissions, or how errors are handled. This leaves significant gaps for a tool interacting with Kubernetes deployments.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point without any unnecessary words. It's front-loaded with the core purpose and wastes no space on 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 no annotations and no output schema, the description is insufficient. It doesn't explain what 'detailed information' entails, how results are formatted, or potential error conditions. Given the complexity of Kubernetes deployments and the lack of structured metadata, more context is needed for 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?
The schema description coverage is 100%, with both parameters ('name' and 'namespace') clearly documented in the schema. The description doesn't add any meaningful context beyond what the schema already provides, such as explaining parameter interactions or constraints, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 ('detailed information about a deployment'), making the purpose immediately understandable. It doesn't specifically differentiate from sibling tools like 'k8s_describe_deployment' or 'k8s_list_deployments', 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 'k8s_describe_deployment' or 'k8s_list_deployments'. It lacks any mention of prerequisites, context, or exclusions, 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Get' implies a read-only operation, it doesn't specify what 'detailed information' includes, whether authentication is required, potential rate limits, or error conditions. For a Kubernetes tool with no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that immediately conveys the core purpose. There's no wasted verbiage or unnecessary elaboration, making it optimally concise while still being 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?
For a Kubernetes tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'detailed information' includes, how the output is structured, or provide any context about Kubernetes-specific considerations. Given the complexity of Kubernetes operations and the lack of structured metadata, more descriptive content would be helpful.
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 input schema has 100% description coverage, with the single parameter 'name' clearly documented as 'Node name'. The description adds no additional parameter semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.
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 ('detailed information about a specific node'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'k8s_describe_node' or 'k8s_list_nodes', which appear to serve similar purposes in the Kubernetes context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'k8s_describe_node' (which might provide more verbose output) and 'k8s_list_nodes' (which lists multiple nodes), the agent receives no help in selecting the appropriate tool for different scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that values are base64 encoded and hints at sensitivity with 'be careful' in the schema, but fails to detail critical aspects like authentication requirements, error handling (e.g., if secret doesn't exist), rate limits, or whether it's a read-only operation. This leaves significant gaps for safe and effective use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get secret metadata') and adds a key detail ('values are base64 encoded'). There is no wasted language, and it's appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is insufficient for a tool that interacts with sensitive Kubernetes secrets. It doesn't cover behavioral traits like safety, permissions, or output format, leaving the agent without critical context for proper invocation. This is a significant gap for a tool with potential security implications.
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 100%, so the schema fully documents the parameters (name, namespace, decode). The description adds minimal value by noting base64 encoding, which relates to the decode parameter, but doesn't provide additional context beyond what's in the schema descriptions. This meets the baseline of 3 for high 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 ('secret metadata'), and specifies that values are base64 encoded. It distinguishes from siblings like k8s_list_secrets by focusing on retrieving a specific secret rather than listing. However, it doesn't explicitly differentiate from k8s_get_resource_yaml or other get operations, keeping it at 4 instead of 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 siblings like k8s_list_secrets for listing or k8s_get_resource_yaml for YAML output, nor does it specify prerequisites such as needing a valid Kubernetes context. Usage is implied by the name and description 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 states this is a read operation ('Get'), implying it's non-destructive, but doesn't address permissions, rate limits, error conditions, or what 'detailed information' entails (e.g., format, fields). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence contributes directly to understanding the tool's function, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of Kubernetes operations and the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what 'detailed information' includes (e.g., YAML, JSON, specific fields), error handling, or dependencies. For a tool in a rich sibling set with no structured safety or output hints, 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 100%, so the schema already documents both parameters ('name' and 'namespace') adequately. The description doesn't add any parameter-specific details beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate.
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 ('detailed information about a service'), making the purpose immediately understandable. It distinguishes this from sibling tools like 'k8s_list_services' (which lists multiple services) and 'k8s_describe_service' (which provides a different output format), though it doesn't explicitly mention these distinctions.
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 'k8s_describe_service' or 'k8s_list_services'. The description lacks context about use cases, prerequisites, or exclusions, 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 the full burden of behavioral disclosure. It states the action ('List') but doesn't describe what the output looks like (e.g., list format, fields included), whether it's paginated, if it requires specific permissions, or any rate limits. This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste—it directly states the tool's purpose without unnecessary words. It's front-loaded and appropriately sized for a simple listing operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain the output format, behavioral traits like safety or permissions, or how parameters interact (e.g., mutual exclusivity of 'namespace' and 'all_namespaces'). For a tool with 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 100%, so the schema already documents both parameters ('namespace' and 'all_namespaces') with clear descriptions. The description adds no additional meaning beyond implying namespace scoping, which is already covered in the schema. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 ('DaemonSets') with scope ('in a namespace'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'k8s_get_daemonset' (which retrieves a specific DaemonSet) or 'k8s_list_pods' (which lists a different resource type), though the naming convention helps.
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 'k8s_get_daemonset' for detailed views or 'k8s_list_all' for broader listings, nor does it explain the relationship between the 'namespace' and 'all_namespaces' parameters, 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?
No annotations are provided, so the description carries full burden. It states 'List Ingresses' which implies a read-only operation, but doesn't disclose behavioral traits like authentication requirements, rate limits, output format, pagination, or error conditions. For a Kubernetes tool with no 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 a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately scannable. Every word earns its place in conveying the essential purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for effective tool use. It doesn't explain what information is returned (e.g., ingress names, rules, status), how results are formatted, or any behavioral constraints. For a Kubernetes listing tool with rich sibling context, this leaves significant 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 100%, with both parameters ('namespace' and 'all_namespaces') clearly documented in the schema. The description adds no additional parameter semantics beyond implying namespace scoping. According to guidelines, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the 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 the verb ('List') and resource ('Ingresses'), making the purpose immediately understandable. It specifies the scope ('in a namespace'), which is helpful. However, it doesn't explicitly differentiate from sibling tools like 'k8s_get_ingress' or other list tools, 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. It doesn't mention sibling tools like 'k8s_get_ingress' (for single ingress details) or 'k8s_list_all' (for broader listing), nor does it explain prerequisites or exclusions. 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action but lacks critical details: it doesn't mention that this is a read-only operation (implied by 'List'), what permissions are needed, whether it returns live or cached data, the output format (e.g., JSON table), pagination handling, or error conditions like invalid namespaces. The description is too sparse for a tool interacting with a complex system like 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 a single, efficient sentence that front-loads the core functionality ('List pods') and specifies the scope. There is no wasted verbiage, making it easy to parse quickly.
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 and the lack of annotations and output schema, the description is insufficient. It doesn't cover behavioral aspects like safety (read-only), authentication needs, rate limits, or output structure. For a tool with three parameters and no structured output definition, more context is needed to guide 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?
The description mentions 'namespace or all namespaces', which aligns with the 'namespace' and 'all_namespaces' parameters in the schema, but adds no additional meaning beyond what the schema already provides (schema description coverage is 100%). It doesn't explain the 'label_selector' parameter at all. Since the schema fully documents all parameters, the baseline score of 3 is appropriate—the description adds minimal value here.
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 ('pods') with scope ('in a namespace or all namespaces'), making the purpose immediately understandable. It doesn't explicitly differentiate from siblings like 'k8s_get_pod' (which likely retrieves a single pod) or 'k8s_top_pods' (which shows resource usage), but the listing function is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention when to prefer 'k8s_list_pods' over 'k8s_get_pod' (for a single pod) or 'k8s_top_pods' (for performance metrics), nor does it specify prerequisites like requiring cluster access or kubectl configuration.
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 action ('List') but doesn't disclose behavioral traits like whether it's read-only (implied but not explicit), what permissions are required, how results are formatted (e.g., YAML, JSON), if there's pagination, or error handling. This leaves significant gaps for a tool interacting with a Kubernetes cluster.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('List StatefulSets') and specifies the scope ('in a namespace'). There is no wasted verbiage, making it easy to parse quickly.
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 and lack of annotations or output schema, the description is incomplete. It doesn't cover behavioral aspects like safety, permissions, or output format, which are critical for an agent to use this tool effectively in a cluster environment.
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 100%, with both parameters ('namespace' and 'all_namespaces') clearly documented in the schema. The description adds no additional parameter semantics beyond implying namespace scoping, so it meets the baseline of 3 where the schema does the heavy lifting.
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 ('StatefulSets'), and specifies the scope ('in a namespace'). It distinguishes from siblings like 'k8s_get_statefulset' (singular) and 'k8s_get_all' (all resources), but doesn't explicitly differentiate from 'k8s_list_pods' or similar list 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?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention siblings like 'k8s_get_statefulset' for detailed views or 'k8s_get_all' for broader queries, nor does it specify prerequisites such as needing cluster access or appropriate permissions.
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. 'Perform a rolling restart' implies a mutation operation that will cause downtime/restart of pods, but it doesn't disclose critical behavioral traits: whether it requires specific permissions, what 'rolling' means (e.g., pod-by-pod replacement), potential side effects, or error conditions. For a mutation tool 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a tool with two simple parameters and front-loads the essential information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens during a rolling restart, what the expected outcome is, potential risks, or error handling. Given the complexity of Kubernetes operations and the lack of structured safety information, this description leaves too many questions unanswered for safe agent usage.
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 100%, so the schema already documents both parameters (name and namespace) with basic descriptions. The description doesn't add any parameter-specific information beyond what's in the schema - it doesn't explain what 'rolling restart' means for these parameters or provide usage examples. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('perform a rolling restart') and the target resource ('deployment'), making the purpose immediately understandable. It distinguishes from siblings like k8s_describe_deployment or k8s_update_deployment_image by focusing specifically on restarting. However, it doesn't explicitly differentiate from k8s_rollout_undo which might also affect deployment state.
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., deployment must exist), when to choose restart over other update methods, or what scenarios warrant a rolling restart versus other operations. With many sibling tools available, this lack of contextual guidance 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('undo') which implies a mutation, but doesn't specify whether this requires admin permissions, if it's reversible, what happens to current pods, or potential downtime. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized for a straightforward tool and front-loads the core purpose immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or important behavioral aspects like whether the undo is immediate or staged. Given the complexity of Kubernetes operations, 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 100%, so the schema already documents all three parameters (name, namespace, revision). The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining the default behavior when revision is omitted. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('undo') and target ('last rollout of a deployment'), providing a specific verb+resource combination. It distinguishes from siblings like 'k8s_rollout_history' or 'k8s_restart_deployment' by focusing on rollback functionality, though it doesn't explicitly contrast them.
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 'k8s_rollout_history' (which might show revisions) or 'k8s_update_deployment_image' (for forward changes). There's no mention of prerequisites, such as needing a deployment with rollout history, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic action. It doesn't disclose that this is a destructive/mutative operation (changing replica count affects running pods), permission requirements, potential side effects (e.g., pod creation/deletion), rate limits, or what happens on failure. For a mutation tool with zero annotation coverage, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately understandable. Every word earns its place by contributing essential information about what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects (destructive nature, permissions), error conditions, return values, or usage context. While concise, it lacks the depth needed for safe and effective use by an AI agent 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 100%, so all parameters are documented in the schema. The description adds no additional parameter semantics beyond implying the 'replicas' parameter sets the target count. It doesn't explain parameter relationships, constraints (e.g., replicas must be non-negative integer), or provide examples. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Scale') and resource ('a deployment') with a specific outcome ('to a specific number of replicas'). It distinguishes itself from siblings like k8s_get_deployment (read) or k8s_update_deployment_image (different mutation), but doesn't explicitly differentiate from k8s_scale_statefulset which performs a similar scaling operation on a different 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. It doesn't mention prerequisites (e.g., needing deployment to exist), when not to use it (e.g., for scaling other resources), or direct alternatives like k8s_scale_statefulset for statefulsets. 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, the description carries full burden but only states the scaling action without behavioral details. It doesn't disclose that this is a destructive/mutative operation, potential impacts on pods, required permissions, or rate limits, leaving critical behavioral traits unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly.
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 mutative tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral effects (e.g., pod creation/deletion), error conditions, or return values, leaving significant gaps 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 100%, so the schema already documents all parameters (name, namespace, replicas). The description adds no additional meaning beyond implying 'replicas' is the target count, matching the baseline score for high 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 ('Scale') and target resource ('a StatefulSet'), specifying the operation to change the number of replicas. It distinguishes from siblings like 'k8s_scale_deployment' by targeting StatefulSets, but doesn't explicitly differentiate 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 on when to use this tool versus alternatives is provided. It doesn't mention prerequisites like cluster access, compare to 'k8s_scale_deployment' for different resource types, or indicate scenarios like scaling for load changes versus using other tools for 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 the tool shows resource usage but doesn't describe output format (e.g., table, JSON), whether it's real-time or historical, any rate limits, permissions required, or if it's a read-only operation. This leaves significant gaps for an agent to understand how to interpret results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
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 resource monitoring, no annotations, and no output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., metrics format, units), whether it requires cluster metrics to be enabled, or how it differs from similar tools. This leaves the agent with insufficient context for 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 100%, so the schema already documents both parameters (namespace and all_namespaces). The description doesn't add any parameter-specific details beyond what's in the schema, such as how these parameters interact or default behaviors. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 ('Show') and resource ('resource usage for pods'), specifying CPU and memory metrics. It distinguishes from siblings like k8s_get_pod (which retrieves pod details) and k8s_top_nodes (which shows node metrics), though it doesn't explicitly mention these distinctions in the description 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 prefer k8s_top_pods over k8s_get_pod for resource metrics, or how it differs from k8s_top_nodes. There's no context about prerequisites, such as needing metrics-server installed in the cluster.
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 'Update' implies a mutation, it doesn't disclose critical behavioral traits: whether this triggers a rolling update, what permissions are required, potential downtime implications, or how the update interacts with existing deployment strategies. For a Kubernetes deployment mutation tool, this leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a tool with a clear, focused function and gets straight to the point without unnecessary preamble or elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a Kubernetes deployment mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't address critical context like: what happens after the update (does it return status?), whether this is a safe operation, what error conditions might occur, or how it interacts with deployment strategies. The combination of mutation functionality and lack of structured documentation creates 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 100%, so the schema already documents all four parameters with clear descriptions. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain parameter relationships, format requirements beyond the schema's 'e.g., nginx:1.21' example, or constraints on valid image references.
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 target ('container image of a deployment'), providing a specific verb+resource combination. It distinguishes this from sibling tools like k8s_restart_deployment or k8s_scale_deployment by focusing specifically on image updates rather than other deployment modifications.
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 are multiple sibling tools that modify deployments (k8s_restart_deployment, k8s_scale_deployment, k8s_rollout_undo), but the description doesn't explain when image updates are appropriate versus other deployment changes or how this differs from k8s_apply_manifest which could also update images.
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 read operation ('Get'), but doesn't disclose behavioral aspects like required permissions, rate limits, error conditions, or whether it returns structured data versus raw output. For a Kubernetes tool with no 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence efficiently conveys purpose and scope. No wasted words, front-loaded with the main action. Every element ('full description', 'including conditions, capacity, and allocatable resources') adds value.
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 single-parameter read operation with 100% schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it should ideally provide more behavioral context about what 'full description' means in practice (structured vs unstructured, typical response format). The description meets basic requirements but leaves 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 100% with the single parameter 'name' clearly documented as 'Node name'. The description doesn't add any parameter semantics beyond what the schema provides, but doesn't need to since schema coverage is complete. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 full description') and resource ('of a node'), specifying what information is included ('conditions, capacity, and allocatable resources'). It distinguishes from simpler 'get' operations by emphasizing 'full description', but doesn't explicitly differentiate from sibling 'k8s_get_node' which might provide less detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'k8s_get_node' or 'k8s_list_nodes'. The description implies it provides more detailed information than basic get operations, but doesn't explicitly state this or provide 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?
No annotations are provided, so the description carries the full burden. It mentions the output includes 'endpoints', which adds some behavioral context beyond a basic read. However, it doesn't disclose critical traits like whether this is a read-only operation, if it requires specific permissions, potential rate limits, or error conditions. The description is minimal and leaves significant behavioral aspects unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get full description of a service') and adds a useful detail ('including endpoints'). There is no wasted verbiage or redundancy, making it highly concise and well-structured 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 complexity (a read operation in Kubernetes with 2 parameters), no annotations, and no output schema, the description is minimally adequate. It specifies the resource and output detail, but lacks information on permissions, error handling, or output format. For a tool in a rich sibling set with many alternatives, more context would be beneficial, but it meets the basic threshold.
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 input schema has 100% description coverage, with clear parameter descriptions ('Service name' and 'Namespace'). The tool description doesn't add any parameter-specific semantics beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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 full description') and resource ('of a service'), and specifies what information is included ('including endpoints'). It distinguishes from siblings like 'k8s_get_service' by emphasizing a more detailed description rather than basic retrieval. However, it doesn't explicitly contrast with 'k8s_describe_pod' or 'k8s_describe_deployment' 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 like 'k8s_get_service' (which likely returns less detail) or other 'describe' tools for different resources. It lacks explicit when-to-use or when-not-to-use instructions, and doesn't mention prerequisites such as cluster access or namespace context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Get detailed information' but doesn't disclose behavioral traits like whether this is a read-only operation, what format the information is returned in (e.g., JSON, YAML), error conditions (e.g., if pod doesn't exist), or authentication requirements. This leaves significant gaps for an agent to understand how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy for an agent to parse 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?
Given the complexity (a read operation in Kubernetes with 2 parameters), no annotations, and no output schema, the description is minimally adequate. It specifies the action and target but lacks details on return format, error handling, or usage context. This is the bare minimum for a simple getter tool, leaving room for improvement in completeness.
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 100%, with both parameters ('name' and 'namespace') clearly documented in the schema. The description adds no additional parameter semantics beyond implying that 'detailed information' is retrieved for a 'specific pod', which aligns with the schema but doesn't provide extra value. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 'detailed information about a specific pod', making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'k8s_describe_pod' or 'k8s_get_pod_logs', which serve related but distinct purposes in Kubernetes 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?
No guidance is provided on when to use this tool versus alternatives. With siblings like 'k8s_describe_pod' (which might offer more verbose output) and 'k8s_list_pods' (for listing multiple pods), the description lacks any context about use cases, prerequisites, or comparisons to help an agent choose appropriately.
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 it's a list operation, implying read-only behavior, but doesn't specify whether it returns all ConfigMaps or requires pagination, what format the output takes (e.g., YAML, JSON, table), or any rate limits. For a Kubernetes tool with no annotation coverage, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states exactly what the tool does with zero wasted words. It's front-loaded with the core action and resource, making it immediately scannable and understandable.
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 100% schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it doesn't provide enough context about behavioral aspects like output format, pagination, or error handling. The description meets basic requirements but leaves important operational details unspecified.
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 100%, with both parameters ('namespace' and 'all_namespaces') clearly documented in the schema. The description mentions 'in a namespace' which aligns with the parameters but adds no additional semantic context beyond what the schema already provides. The baseline score of 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 in a namespace'), making the purpose immediately understandable. It distinguishes this tool from other list tools like k8s_list_pods or k8s_list_secrets by specifying the resource type. However, it doesn't explicitly differentiate from k8s_get_configmap (which retrieves a single ConfigMap), 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 when to use k8s_list_configmaps versus k8s_get_configmap (for single ConfigMap retrieval) or k8s_get_all (for broader resource listing). There's also no indication of prerequisites like needing namespace access or kubectl 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?
No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions that 'values are not shown', which is useful context about what information is omitted. However, it doesn't describe other critical behaviors: whether it's read-only (implied but not stated), what the output format is, if there are pagination limits, or if it requires specific RBAC permissions. For a 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 a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a simple list operation and front-loads the core functionality. Every element earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (listing Kubernetes secrets), no annotations, and no output schema, the description is minimally adequate but has clear gaps. It covers the basic action and one important limitation (values not shown), but doesn't address output format, error conditions, or permission requirements. For a Kubernetes tool that could have security implications, more context would be helpful.
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 100%, with both parameters ('namespace' and 'all_namespaces') clearly documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the 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 the verb ('List') and resource ('secrets in a namespace'), making the purpose immediately understandable. It distinguishes from siblings like k8s_get_secret by specifying it lists multiple secrets rather than retrieving a single one. However, it doesn't explicitly differentiate from k8s_list_configmaps or other list 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 when to choose this over k8s_get_secret (for single secret details) or k8s_get_all (for broader resource listing), nor does it specify prerequisites like required permissions or namespace context. The sibling tools include many list operations, but no comparative context is given.
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 'Get' operation, implying read-only behavior, but doesn't specify if it requires special permissions, what format the history is returned in (e.g., list of revisions, timestamps), or any rate limits. This leaves significant gaps for a tool that interacts with Kubernetes deployments.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core purpose, making it easy to parse quickly. Every word earns its place by directly conveying the tool's function.
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 (Kubernetes deployment history), lack of annotations, and no output schema, the description is minimally adequate. It states what the tool does but omits details like output format, error conditions, or behavioral nuances, which could hinder an agent's ability to use it effectively without trial and error.
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 100%, so the schema fully documents the 'name' and 'namespace' parameters. The description doesn't add any extra meaning beyond implying these parameters are used to identify the deployment, which is already clear from the schema. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 ('rollout history of a deployment'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'k8s_describe_deployment' or 'k8s_rollout_status', which might also provide historical or status information about deployments.
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, context, or compare it to siblings like 'k8s_rollout_status' or 'k8s_describe_deployment', leaving the agent to infer usage from the 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 what the tool does but provides no information about what 'status' includes (e.g., progress indicators, error states, completion criteria), whether it's a blocking or non-blocking operation, or what happens if the deployment doesn't exist. For a status-checking 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 a single, efficient sentence that communicates the core functionality without unnecessary words. It's appropriately sized for a straightforward status-checking tool and front-loads the essential information. Every word earns its place, making it easy to parse 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?
Given the tool's moderate complexity (checking rollout status in a Kubernetes environment), no annotations, and no output schema, the description is minimally adequate but leaves gaps. It identifies the tool's purpose but doesn't explain what constitutes 'status' or what format the information returns. For a tool that likely provides detailed rollout progress information, more context about the nature of the status check would be helpful.
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 adds no parameter information beyond what's already in the schema, which has 100% coverage with clear descriptions for both 'name' and 'namespace' parameters. The baseline score of 3 is appropriate since the schema fully documents the parameters, and the description doesn't need to repeat that information. However, it also doesn't provide additional context about parameter usage 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 ('Get the status') and resource ('deployment rollout'), making the purpose immediately understandable. It distinguishes itself from siblings like 'k8s_describe_deployment' or 'k8s_get_deployment' by focusing specifically on rollout status rather than general deployment information. However, it doesn't explicitly contrast with 'k8s_rollout_history' or 'k8s_rollout_undo', which are closely related rollout 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. With multiple sibling tools like 'k8s_describe_deployment', 'k8s_get_deployment', and 'k8s_rollout_history', there's no indication of when this specific rollout status check is preferred over those other deployment-related tools. The description is purely functional 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 the full burden of behavioral disclosure. It states the action ('Get') but doesn't describe what 'current kubectl context' entails—such as whether it returns a name, cluster details, or authentication info, or if it's read-only (implied but not explicit). For a tool with zero annotation coverage, this is insufficient, as it misses details on output format and operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's front-loaded and appropriately sized for a simple, parameterless tool, making it easy for an agent to parse 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?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate but lacks depth. It doesn't explain the return value (e.g., context name or details), which is critical since there's no output schema. For a basic read operation, it meets the bare minimum but could be more informative to fully guide the agent.
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, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter semantics, but that's acceptable here. A baseline of 4 is appropriate as the schema fully covers the lack of parameters, and the description doesn't need to compensate.
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') and resource ('current kubectl context'), making it immediately understandable. However, it doesn't explicitly differentiate from its sibling 'k8s_get_contexts', which likely lists all contexts rather than just the current one, leaving some ambiguity in sibling 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., kubectl configuration), compare it to 'k8s_get_contexts' for listing all contexts, or specify use cases like checking active context before operations. This lack of 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?
No annotations are provided, so the description carries full burden. It states it's a 'Get' operation, implying read-only behavior, but doesn't disclose any behavioral traits such as authentication requirements, rate limits, error conditions, or what 'endpoints' specifically refers to (e.g., API server endpoints). For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves in practice.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes essential information, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, no annotations, and no output schema, the description is minimally adequate. It specifies what information is retrieved ('server version and endpoints'), which helps understand the scope, but lacks details on output format, error handling, or behavioral context. For a simple read tool, it meets basic needs but could be more complete by addressing missing behavioral aspects.
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, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. A baseline of 4 is applied as per rules for 0 parameters, as the description doesn't mislead or omit necessary param info.
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 ('Kubernetes cluster information') with specific details about what information is included ('server version and endpoints'). It distinguishes itself from siblings like k8s_get_contexts or k8s_get_all by focusing on cluster-level metadata rather than contexts or all resources. However, it doesn't explicitly contrast with similar tools like k8s_current_context, which might also provide cluster-related 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 prerequisites (e.g., needing cluster access), compare to siblings like k8s_get_contexts for context-specific info or k8s_get_all for broader resource listing, or specify scenarios where cluster info is needed (e.g., setup verification). Usage is implied by the name 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 the full burden of behavioral disclosure. While 'List all available kubectl contexts' clearly indicates a read-only operation, it doesn't address important behavioral aspects like whether this requires specific permissions, how the results are formatted, whether there are rate limits, or what happens if no contexts are configured.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core functionality without any wasted words. It's appropriately sized for a simple listing operation and gets straight to the point.
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 zero-parameter read operation, the description is minimally complete but lacks important context. Without annotations or an output schema, the description doesn't address what format the contexts are returned in, whether authentication is required, or what happens in edge cases like no contexts being available.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, which is correct for this tool's design.
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 available kubectl contexts'), making it immediately understandable. However, it doesn't explicitly distinguish this from its sibling 'k8s_current_context' which presumably shows only the current context rather than listing all contexts.
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 siblings like 'k8s_current_context' and 'k8s_get_cluster_info' that might provide related information, there's no indication of when this specific listing tool is most appropriate or what distinguishes it from other context-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 full burden but only states the basic action without disclosing behavioral traits. It doesn't mention whether this is a read-only operation (though implied by 'List'), what permissions are required, how results are formatted (e.g., JSON, YAML), pagination behavior, error conditions, or rate limits. For a Kubernetes tool with potential complexity, 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 a single, efficient sentence that front-loads the core functionality ('List deployments') followed by the key scope detail. There's zero wasted language, and it's appropriately sized for a straightforward listing tool with well-documented parameters in the schema.
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 and lack of both annotations and output schema, the description is insufficient. It doesn't explain what information is returned (e.g., deployment names, statuses, metadata), how to interpret results, error handling, or authentication requirements. For a tool in a rich ecosystem with many siblings, more context is needed to ensure proper agent usage.
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 100%, with both parameters ('namespace' and 'all_namespaces') clearly documented in the schema. The description adds minimal value by mentioning the namespace scope, but doesn't provide additional semantics like parameter interactions (e.g., that 'all_namespaces=true' might override 'namespace'), default behaviors, or examples. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 namespace or all namespaces'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'k8s_get_deployment' or 'k8s_describe_deployment', which might provide more detailed information about specific deployments rather than listing them.
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 context by specifying 'in a namespace or all namespaces', which suggests when to use namespace parameter vs. all_namespaces. However, it doesn't provide explicit guidance on when to choose this tool over alternatives like 'k8s_get_deployment' (for single deployment details) or 'k8s_list_pods' (for related resources), nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 a read operation ('List'), implying non-destructive behavior, but lacks details on permissions, rate limits, output format, or pagination. For a tool with zero annotation coverage, this is insufficient behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded with the core action and resource, making it highly 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 tool's simplicity (0 parameters, no output schema) and lack of annotations, the description is minimally adequate. It states the basic purpose but misses behavioral details like output structure or cluster context, which are important for a list operation in a complex environment like Kubernetes.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param details, which is appropriate, earning a baseline score of 4 for adequately handling the lack of 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 ('List all') and resource ('namespaces in the cluster'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from similar sibling tools like 'k8s_get_all' or other list tools, which would require more specificity 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. With many sibling tools (e.g., 'k8s_get_all', 'k8s_list_pods'), there's no indication of context, prerequisites, or exclusions, leaving the agent to infer usage from the 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 mentions what information is returned (status, roles, resource info) but doesn't disclose behavioral traits like pagination, rate limits, permissions required, or whether it's a read-only operation. For a Kubernetes 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that efficiently conveys the core functionality without unnecessary words. Every element ('List all nodes', 'in the cluster', 'with their status, roles, and resource information') serves a clear purpose.
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 zero-parameter read operation with no output schema, the description adequately explains what the tool does. However, given the complexity of Kubernetes operations and lack of annotations, it should ideally mention that it's a read-only listing operation and potentially clarify output format or limitations.
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 (empty schema). The description doesn't need to explain parameters, so it appropriately focuses on the tool's purpose. No parameter information is required or missing.
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 nodes in the cluster') with specific attributes ('status, roles, and resource information'). It distinguishes from siblings like k8s_get_node (singular) and k8s_describe_node (detailed view), but doesn't explicitly mention these distinctions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like k8s_get_node, k8s_describe_node, or k8s_top_nodes. The description implies a broad listing operation but doesn't specify use cases, 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 what the tool does but lacks behavioral details such as whether it's read-only, what permissions are required, how results are formatted (e.g., list of objects), pagination, or error handling. This is a significant gap for a tool with potential operational impact in 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 a single, efficient sentence that front-loads the core purpose without unnecessary words. It directly communicates the tool's function and scope, making it easy to parse quickly.
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 and lack of annotations or output schema, the description is incomplete. It doesn't address behavioral aspects like safety (read-only vs. mutating), authentication needs, output format, or error conditions, which are crucial for an AI agent to use this tool effectively in a production environment.
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 100%, with both parameters ('namespace' and 'all_namespaces') clearly documented in the schema. The description adds minimal value by mentioning the scope options, but doesn't provide additional semantics beyond what the schema already states. Baseline 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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') and resource ('services') with scope ('in a namespace or all namespaces'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'k8s_get_service' (which appears to fetch a single service), but the 'List' verb implies a collection operation versus a specific retrieval.
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 context by specifying 'in a namespace or all namespaces', which helps understand when to use it based on scope. However, it doesn't provide explicit guidance on when to choose this over alternatives like 'k8s_get_service' or 'k8s_get_all', nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 tool shows resource usage, implying a read-only operation, but doesn't disclose behavioral traits like whether it requires specific permissions, how data is formatted, if it's real-time or cached, or any rate limits. This is inadequate 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and every part earns its place, making it highly concise and well-structured.
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 (simple read operation), no annotations, no output schema, and 0 parameters, the description is minimally adequate. It specifies what resource usage is shown (CPU/memory) and for what (nodes), but lacks details on output format, permissions, or behavioral context, leaving gaps for the agent.
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 no parameter documentation is needed. The description doesn't add parameter semantics, but this is appropriate given the lack of parameters, meeting the baseline for this scenario.
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 specific verbs ('Show resource usage') and resources ('nodes'), specifying the types of resources (CPU/memory). It distinguishes from siblings like 'k8s_describe_node' (detailed node info) and 'k8s_list_nodes' (list nodes), but doesn't explicitly mention these alternatives in the description 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 like 'k8s_describe_node' or 'k8s_list_nodes'. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage based on the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Get' implies a read-only operation, the description doesn't specify whether this requires specific permissions, how events are formatted or paginated, or any rate limits. For a tool with zero annotation coverage, this leaves significant gaps in understanding its operational behavior and constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get cluster events') and adds necessary qualification ('optionally filtered by namespace'). There is zero waste or redundancy, making it easy to parse 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?
Given the tool's moderate complexity (read operation with filtering), 100% schema coverage, and no output schema, the description is adequate but incomplete. It covers the basic purpose and filtering, but lacks details on output format, error handling, or behavioral traits. For a tool without annotations, more context would be beneficial to fully guide usage.
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 100%, with both parameters ('namespace' and 'all_namespaces') clearly documented in the schema. The description adds minimal value by mentioning optional namespace filtering, but doesn't provide additional context beyond what the schema already states. This meets the baseline score of 3 for high 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 cluster events') and resource ('cluster events'), making the purpose immediately understandable. It distinguishes this tool from other Kubernetes tools by focusing specifically on events rather than resources like pods or deployments. However, it doesn't explicitly differentiate from potential sibling tools that might also retrieve events with different filtering capabilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage guidance by mentioning 'optionally filtered by namespace,' suggesting this is the primary filtering mechanism. However, it doesn't explicitly state when to use this tool versus alternatives like k8s_get_all or other get_* tools, nor does it mention any prerequisites or exclusions. The guidance is functional but lacks comparative context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden of behavioral disclosure. It effectively communicates the destructive nature of the operation ('WARNING: This will delete all resources in the namespace'), which is crucial for a deletion tool. However, it doesn't mention other behavioral aspects like permissions required, whether the operation is reversible, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just one sentence that front-loads the core action and includes a critical warning. Every word earns its place, with no redundant information or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive tool with no annotations and no output schema, the description does well by emphasizing the dangerous nature of the operation. However, it could be more complete by mentioning prerequisites (like needing appropriate permissions) or what happens after deletion (e.g., whether the namespace name becomes available for reuse).
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 input schema has 100% description coverage, with the single parameter 'name' clearly documented as 'Namespace name to delete'. The description doesn't add any additional parameter information beyond what's in the schema, so it meets the baseline expectation when schema coverage is complete.
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 a namespace') and specifies the target resource ('namespace'), making the purpose immediately apparent. It distinguishes itself from sibling tools like 'k8s_delete_pod' or 'k8s_delete_resource' by focusing specifically on namespace deletion rather than other resource types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool through the WARNING about deleting all resources in the namespace, which implicitly suggests it should be used with caution for destructive operations. However, it doesn't explicitly mention when NOT to use it or name specific alternatives like 'k8s_list_namespaces' for checking namespace existence first.
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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