Kubernetes MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting specific resources and actions, but there is some overlap. For example, 'debug-pod' and 'create-ephemeral-container' both relate to pod debugging, and 'port-forward' vs 'port-forward-pod' could be confusing without careful reading of descriptions. However, the majority are well-differentiated.
Naming Consistency4/5
The naming follows a consistent kebab-case verb-noun pattern throughout, with clear conventions like 'list-*', 'get-*', 'describe-*', and action-specific verbs. Minor deviations exist, such as 'cp' (abbreviation) and 'run' (single word), but overall the pattern is predictable and readable.
Tool Count2/5
With 81 tools, the count is excessive for an MCP server, making it overwhelming and difficult for agents to navigate. While Kubernetes is a complex domain, this many tools suggests poor scoping and could lead to confusion or inefficiency in tool selection.
Completeness5/5
The toolset provides comprehensive coverage of Kubernetes operations, including CRUD, monitoring, debugging, and management tasks across resources. It supports core workflows like deployment, scaling, logging, and troubleshooting, with no apparent gaps for the domain.
Average 2.9/5 across 81 of 81 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No critical vulnerability alerts
- No high-severity vulnerability alerts
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{
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}
```
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How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states 'analyze' but doesn't disclose behavioral traits such as whether it's a read-only operation, if it requires specific permissions, what the output format is, or if it has rate limits. For a tool with no annotations, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's appropriately sized and front-loaded, though it could benefit from more detail given the lack of annotations and output 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 analyzing resource usage, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'analyze' entails, what resources are covered, or the return values, leaving significant gaps for the 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?
The input schema has 100% description coverage for its single parameter ('namespace'), so the schema already documents it well. The description doesn't add any meaning beyond the schema, as it doesn't mention parameters at all. 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.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Analyze resource usage across the cluster' clearly states the verb ('analyze') and resource ('resource usage'), but it's vague about what specific analysis is performed (e.g., CPU, memory, metrics) and doesn't distinguish it from sibling tools like 'get-cluster-metrics', 'get-node-metrics', or 'get-pod-metrics'. It provides a basic purpose but lacks specificity.
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 'get-cluster-metrics' or other metrics-related siblings. The description doesn't mention prerequisites, context, or exclusions, leaving the agent without usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Get the data' but doesn't disclose behavioral traits like authentication requirements, rate limits, error conditions (e.g., if configmap doesn't exist), output format (e.g., YAML/JSON, raw data), or whether it's read-only (implied but not explicit). The description is minimal and 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words, making it highly concise. However, it's front-loaded but under-specified—it could benefit from slightly more detail without losing efficiency, as it currently lacks context that might be needed for clarity.
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 structured data (configmap contents). It doesn't explain what 'data' includes (e.g., key-value pairs, metadata), potential errors, or usage context in Kubernetes. For a read operation with 2 parameters, more guidance is needed to be fully 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 clear descriptions for both parameters in the schema. The description adds no additional meaning beyond the schema (e.g., it doesn't explain what a configmap is, format of returned data, or interactions between parameters). Baseline is 3 since 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 the data from a configmap' clearly states the action (get) and resource (configmap), but it's vague about what 'data' specifically means (e.g., full configmap object, specific keys, metadata). It distinguishes from siblings like 'list-configmaps' (which lists multiple) and 'describe-configmap' (which provides detailed description), but doesn't explicitly differentiate from 'get-secret' or other get tools.
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 'describe-configmap' (for detailed info) or 'list-configmaps' (for listing multiple). The description implies it retrieves data, but doesn't specify use cases, prerequisites, or exclusions (e.g., vs. reading from a file or other sources).
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. 'Get' implies a read operation, but it doesn't disclose behavioral traits like whether this requires specific permissions, how events are formatted/returned, if there are rate limits, or if it's a real-time vs historical query. The description is minimal and leaves critical 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.
Conciseness4/5
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 no wasted words. However, it's arguably too concise given the lack of behavioral context and usage guidance needed for this tool category.
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 troubleshooting tool with no annotations and no output schema, the description is insufficient. It doesn't explain what constitutes an 'event', how results are structured, what time range is covered, or any limitations. Given the complexity of Kubernetes environments and the rich sibling toolset, 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?
Schema description coverage is 100%, so the schema already documents the optional 'namespace' parameter with its default behavior. The description adds no parameter information beyond what's in the schema, maintaining the baseline score of 3 since 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 Kubernetes events for troubleshooting' clearly states the verb ('Get') and resource ('Kubernetes events'), but it's vague about scope and doesn't distinguish from sibling tools like 'describe-pod' or 'get-logs' that might also be used for troubleshooting. It specifies the purpose but lacks precision about what 'events' means in this 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 many sibling tools available for Kubernetes troubleshooting (e.g., 'describe-pod', 'get-logs', 'list-pods'), there's no indication of when this specific event-fetching tool is appropriate or what problems it's best suited for.
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 'Get the data' but doesn't disclose behavioral traits such as read-only vs. destructive nature, authentication requirements, rate limits, or output format. This is inadequate for a tool that likely accesses sensitive secrets.
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. It's appropriately sized for a simple tool, though it could be more informative. No structural issues 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 no annotations and no output schema, the description is incomplete. It doesn't explain what 'data' includes (e.g., key-value pairs, metadata), potential errors, or security implications. For a secret-access tool, 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%, so the schema already documents parameters 'secret' and 'namespace'. The description adds no meaning beyond this, as it doesn't explain parameter semantics, constraints, 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.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get the data from a secret' states a clear verb ('Get') and resource ('secret'), but it's vague about what 'data' means (e.g., metadata, values, or full content). It doesn't distinguish from sibling tools like 'describe-secret' or 'list-secrets', leaving ambiguity about its specific function.
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 'describe-secret' or 'list-secrets'. The description lacks context about use cases, 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 copying but doesn't disclose behavioral traits like whether it overwrites files, requires specific permissions, handles errors, or has rate limits. The phrase 'to/from a pod' hints at bidirectional transfer but lacks operational details, making it insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly, though it sacrifices detail for brevity.
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 (file copying with 5 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain return values, error conditions, or operational constraints, leaving significant gaps for an agent to invoke it correctly in a Kubernetes 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 already documents all 5 parameters thoroughly. The description adds no additional meaning beyond implying 'pod' as a target and 'source/destination' as paths, but doesn't clarify syntax or usage beyond what the schema provides, meeting the baseline for high coverage.
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 'Copy files to/from a pod' states the basic action (copy) and resource (files, pod), but is vague about scope and directionality. It doesn't specify whether this copies between local and pod, between pods, or both, nor does it distinguish from sibling tools like 'exec' or 'port-forward' which might handle file transfers differently.
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 for pod operations (e.g., 'exec', 'debug-pod', 'port-forward'), the description lacks context about prerequisites, typical use cases, 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. While 'Create' implies a write operation, it doesn't specify whether this requires admin permissions, if namespaces are unique, what happens on conflicts, or any rate limits. The description lacks critical behavioral details needed for safe and effective use in a mutation 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 extremely concise with just three words, front-loading the key action and resource. There is no wasted language or redundancy, making it easy to scan and understand at a glance. This efficiency is appropriate for a simple tool with minimal parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation with no annotations and no output schema), the description is incomplete. It doesn't address behavioral aspects like permissions or idempotency, usage guidelines, or output expectations. For a creation tool in a likely Kubernetes context (inferred from sibling tools), more context is needed to ensure proper 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 input schema has 100% description coverage, with the 'name' parameter fully documented in the schema. The description adds no additional parameter information beyond implying a namespace is created, which is already clear from the tool name and schema. This meets the baseline score of 3, as the schema adequately covers parameter semantics without extra value from the description.
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 'Create a new namespace' clearly states the verb ('create') and resource ('namespace'), making the basic purpose understandable. However, it lacks specificity about what a namespace entails in this context and doesn't distinguish this tool from other creation tools like 'create-backup' in the sibling list. It's not tautological but remains somewhat vague about the domain.
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., permissions, context), exclusions, or related tools like 'list-namespaces' from the sibling list. Without such context, users must infer usage based on the name alone, which is insufficient for effective tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but provides almost none. 'Install a Helm chart' implies a write/mutation operation but doesn't disclose whether this requires specific permissions, what happens on conflicts, whether it's idempotent, or any side effects. For a deployment tool with zero annotation coverage, this is a critical gap in behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is maximally concise with just three words that directly convey the core function. There's zero wasted language, no unnecessary elaboration, and it's perfectly front-loaded. This is an excellent example of efficiency in tool description writing.
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 complex deployment tool with no annotations and no output schema, the description is severely incomplete. It doesn't explain what a Helm chart is, what installation entails, what the expected output looks like, or any behavioral characteristics. The combination of mutation nature, technical complexity, and lack of structured metadata means the description should provide much more context than it does.
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 all 5 parameters. The baseline score of 3 is appropriate since the schema fully documents parameters like 'name', 'chart', 'namespace', 'values', and 'version'. The description doesn't compensate but doesn't need to given the comprehensive schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Install a Helm chart' clearly states the action (install) and resource (Helm chart), making the purpose immediately understandable. It distinguishes from siblings like helm-list, helm-uninstall, and helm-upgrade by specifying the installation action. However, it doesn't explicitly differentiate from other installation tools like apply or create-namespace, which slightly limits 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 when to choose helm-install over helm-upgrade, when to use it versus kubectl apply, or any prerequisites like having Helm configured. The agent must infer usage from the tool name alone, which is insufficient for optimal tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Patch' implies a mutation, but doesn't clarify if it's idempotent, what happens on conflicts, whether it requires specific permissions, or what the typical response looks like (e.g., success/failure messages). For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with zero wasted words. It's front-loaded with the core action and target, making it easy to parse quickly. This is an example of efficient communication, though it trades brevity for completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation with 5 parameters), lack of annotations, and no output schema, the description is insufficient. It doesn't explain return values, error conditions, or behavioral nuances like idempotency. For a Kubernetes patch tool, which can have significant side effects, more context is needed to ensure safe and correct 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 all five parameters (resource, name, patch, type, namespace) with basic descriptions. The description adds no additional meaning beyond what's in the schema, such as examples of patch formats or when to use optional parameters. 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.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('Patch') and target ('a Kubernetes resource'), which provides a basic purpose. However, it's vague about what 'patch' means operationally (e.g., partial updates vs. full replacements) and doesn't distinguish it from similar tools like 'apply' or 'update' that might exist in the sibling list. It's functional but lacks specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives like 'apply' or 'update' (implied from siblings). It doesn't mention prerequisites (e.g., needing proper permissions or context) or exclusions (e.g., not for creating new resources). Without any usage context, it leaves the agent to infer based on 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 offers minimal behavioral insight. It mentions waiting for a condition but doesn't disclose how it behaves (e.g., polling frequency, blocking nature, error handling, or what happens on timeout). For a tool with potential side effects like blocking execution, this is inadequate 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 waste. It's front-loaded with the core action ('wait for a condition') and appropriately sized for its purpose, making it easy to parse 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 the complexity of a waiting/monitoring tool with no annotations and no output schema, the description is insufficient. It doesn't explain return values, error conditions, or behavioral traits like blocking vs. non-blocking. For a tool that interacts with dynamic resources, more context is needed to guide proper 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 all parameters (resource, name, condition, namespace, timeout) with descriptions. The tool description adds no additional meaning beyond what the schema provides, such as examples or constraints. 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.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'waits for a condition on a resource', which is a clear verb+action but lacks specificity about what kind of resources or conditions are involved. It doesn't distinguish itself from potential siblings like 'rollout-status' or 'debug-pod' that might also involve waiting or monitoring. The purpose is understandable but vague in scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, when-not scenarios, or compare to siblings like 'describe-pod' for status checks. Usage is implied (e.g., for monitoring resource states) but not articulated, leaving gaps for an agent to infer 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 provided, the description carries full burden but only states the basic action without disclosing behavioral traits. It doesn't mention permission requirements, whether annotations are merged or replaced, side effects, or response format. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and target, 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 mutation tool with no annotations and no output schema, the description is insufficient. It lacks details on behavior, error conditions, permissions, or output format. Given the complexity of modifying resources and the absence of structured safety 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 parameters are documented in the schema. The description adds no additional meaning about parameters beyond implying annotations are key-value pairs. This meets the baseline for high schema coverage but doesn't enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add or update') and target ('annotations on a resource'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'label' which also modifies resource metadata, leaving room for confusion about when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'label' or 'patch'. The description lacks context about appropriate scenarios, 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. 'Get available API resources' implies a read-only operation, but it doesn't specify whether this requires authentication, returns structured data, has rate limits, or what format the output takes. 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, clear sentence with no wasted words. It's appropriately sized for a simple tool with no parameters, 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.
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 API interactions and the lack of annotations and output schema, the description is insufficient. It doesn't clarify what 'available API resources' entails (e.g., resource types, versions, scopes) or how this differs from other listing tools. For a tool in this context, more detail 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.
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% (empty schema). The description doesn't need to explain parameters, so it meets the baseline expectation. No additional parameter information is required or provided.
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 available API resources' clearly states the action (get) and target (API resources), but it's vague about what 'available API resources' means in this context. It doesn't distinguish this tool from similar sibling tools like 'api-versions', 'list-all', or 'list-crds' that might also retrieve API-related information.
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 that retrieve Kubernetes resources (e.g., 'list-all', 'list-crds', 'api-versions'), there's no indication of whether this tool is for discovery, listing resource types, or something else. 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?
No annotations are provided, so the description carries full burden. It mentions applying a manifest but doesn't disclose critical behaviors: whether it's idempotent, if it creates or updates resources, what happens on errors, authentication needs, or rate limits. This is a significant gap for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 front-loaded with the core action and resource, making it easy to scan and understand quickly 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 mutation tool with no annotations and no output schema, the description is incomplete. It lacks behavioral details (e.g., idempotency, error handling), usage context, and output expectations. Given the complexity of Kubernetes operations, this leaves significant gaps for an AI agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('file' and 'namespace'). The description adds minimal value by implying the 'file' parameter can be a path or URL, but doesn't provide additional syntax or format details beyond what the schema states. 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 ('apply') and resource ('Kubernetes manifest') with source specification ('from a file or URL'). It distinguishes from siblings like 'create-namespace' or 'patch' by focusing on manifest application, though it doesn't explicitly differentiate from similar tools like 'run' or 'create-backup' that might also deploy 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?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention when to choose 'apply' over 'create-namespace' for namespace creation or 'patch' for updates, nor does it specify prerequisites like needing kubectl access or a valid manifest format.
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 only states what the tool does ('Get the status') without describing what 'status' includes, whether it's a read-only operation, potential error conditions, authentication requirements, rate limits, or output format. This leaves significant behavioral gaps for a tool that presumably queries application state.
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 unnecessary words. It's appropriately sized for a simple query tool and front-loads the essential information ('Get the status of an ArgoCD application').
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'status' means in the ArgoCD context, what information is returned, or how to interpret the results. Given the complexity of ArgoCD applications and the lack of structured output documentation, users need more context 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%, with both parameters clearly documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema - it doesn't explain what constitutes a valid application name, namespace conventions, or provide examples. 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 ('Get the status') and target resource ('ArgoCD application'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'argocd-list-apps' or 'describe-deployment', but the specificity of 'ArgoCD application' provides some implicit distinction.
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. The description doesn't mention when this tool is appropriate compared to general Kubernetes status tools or other ArgoCD-related tools in the sibling list, nor does it specify any prerequisites or contextual constraints for its use.
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 checks permissions but doesn't disclose behavioral traits such as whether it's read-only, what authentication is needed, how it handles errors, or what the output format is. This leaves significant gaps for a permission-checking 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 a single, clear sentence that efficiently conveys the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a permission-checking tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects, output format, and usage context, which are crucial for an AI agent to invoke it correctly 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?
The input schema has 100% description coverage, so parameters are well-documented in the schema. The description adds no additional meaning beyond the schema, such as examples or context for the parameters. Baseline 3 is appropriate 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 tool's purpose as checking if the current user can perform an action, which is a specific verb ('check') with a clear object ('perform an action'). However, it doesn't differentiate from sibling tools like 'list-clusterroles' or 'list-rolebindings' that might also relate to permissions, making it less than fully distinctive.
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 that involve permissions or resource operations (e.g., 'list-clusterroles', 'delete'), there's no indication of context, prerequisites, or exclusions for using 'auth-can-i'.
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 'Get cluster information', implying a read-only operation, but doesn't disclose behavioral traits like what type of information is returned, format, permissions needed, or potential side effects. 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 extremely concise ('Get cluster information') with no wasted words, making it front-loaded and easy to parse. However, this conciseness comes at the cost of detail, but it efficiently communicates the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of cluster operations and no annotations or output schema, the description is incomplete. It doesn't explain what 'cluster information' entails, the return format, or how it differs from similar tools, leaving significant gaps for an agent to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here, earning a baseline score of 4 for matching the schema's completeness.
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 cluster information' clearly states the verb ('Get') and resource ('cluster information'), but it's vague about what specific information is retrieved. It doesn't distinguish from sibling tools like 'get-cluster-metrics' or 'list-nodes', which also provide cluster-related data.
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 that might overlap (e.g., 'get-cluster-metrics', 'list-nodes'), the description lacks context about when this specific tool is appropriate, leaving the agent to guess.
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 'create' implies a mutation and 'ephemeral' hints at temporary nature, it lacks details on permissions required, side effects (e.g., impact on pod operations), or response format. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, 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 creating a container in a Kubernetes pod (a mutation operation) and the absence of both annotations and an output schema, the description is insufficient. It doesn't cover behavioral aspects like safety, permissions, or what to expect upon success/failure, leaving significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the schema already documents all parameters thoroughly. The description doesn't add any additional meaning or context beyond what's in the schema, such as explaining interactions between parameters or usage examples, resulting in a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('create') and resource ('ephemeral debug container in a pod'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'debug-pod' or 'exec', which might have overlapping debugging functionality, preventing 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 sibling tools like 'debug-pod' and 'exec' that could serve similar debugging purposes, there's no indication of specific scenarios, prerequisites, or exclusions for this tool's use.
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. 'Create a debug container' implies a mutation/write operation, but the description doesn't specify required permissions, whether this is destructive to the pod, what happens to the debug container after use, or any rate limits. This leaves significant behavioral gaps for a tool that modifies pod state.
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 purpose and 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?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'debug container' means operationally, what capabilities it provides, how it differs from regular containers, or what the expected outcome/response looks like. The context signals indicate this is a non-trivial tool (3 parameters, 1 required) that needs more complete documentation.
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 with their purposes and optionality. The description adds no additional parameter semantics beyond what's in the schema, maintaining 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 ('Create a debug container') and target resource ('in a pod'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'create-ephemeral-container' or 'exec', which might have overlapping functionality for debugging purposes.
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 prerequisites, when this approach is preferred over other debugging methods, or what distinguishes it from similar tools like 'exec' or 'create-ephemeral-container' in the sibling list.
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 specify permissions required, whether the deletion is reversible, confirmation prompts, cascading effects, or error handling. This leaves significant gaps for a high-impact operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized and front-loaded, directly stating the tool's 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?
For a destructive mutation tool with no annotations and no output schema, the description is inadequate. It doesn't cover behavioral aspects like safety warnings, return values, or error conditions, which are critical given the tool's complexity and potential impact in a Kubernetes 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 all parameters well-documented in the schema itself. The description adds no additional meaning beyond what's already in the schema (e.g., no examples of resource types, namespace defaults, or deletion strategies), 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 ('Delete') and target ('a Kubernetes resource'), providing a specific verb+resource combination. However, it doesn't differentiate this from other destructive operations like 'drain-node' or 'uncordon-node' among the many sibling tools, which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'delete' operations for specific resources (e.g., 'delete-pod' if it existed) or other destructive tools. It lacks any mention of prerequisites, exclusions, or comparative context with the extensive list of sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool 'describes details' but doesn't specify what details are included, whether it's a read-only operation, if it requires specific permissions, or what the output format looks like. This leaves significant gaps for an agent to understand 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 gets straight to the point with zero wasted words. It's appropriately sized for a simple tool and front-loads 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 Kubernetes tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'describe' means operationally, what details are returned, or how this differs from similar 'get' operations. Given the complexity of Kubernetes resources and the rich sibling toolset, 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 fully documents both parameters. The description adds no additional meaning about parameter usage, constraints, or examples beyond what's in 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 action ('describe details') and resource ('Kubernetes configmap'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get-configmap' or 'describe-pod', which would require more specificity about what 'describe' entails versus 'get' 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 like 'get-configmap' or 'list-configmaps'. There's no mention of prerequisites, context requirements, or differences in output format compared to similar tools in the sibling list.
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 'describes details' but doesn't specify what details are returned, whether it's a read-only operation, potential error conditions, or output format. For a Kubernetes tool that could return complex deployment information, 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, efficient sentence that communicates the core purpose without unnecessary words. It's appropriately sized for a straightforward tool and front-loads the essential information (describe Kubernetes deployment).
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 description tool with no annotations and no output schema, the description is inadequate. It doesn't explain what 'details' are returned (configuration, status, pods, events?), doesn't mention authentication requirements, and provides no context about the complexity of Kubernetes deployments. Given the rich sibling tool ecosystem, more completeness 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 ('deployment' and 'namespace') clearly documented in the schema. The description adds no additional parameter information beyond what's already in the structured schema, so it meets but doesn't exceed 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('describe details') and resource ('Kubernetes deployment'), making the tool's purpose immediately understandable. It doesn't differentiate from sibling tools like 'describe-pod' or 'describe-service' beyond the resource type, 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 like 'list-deployments' (for overview) or 'get-cluster-metrics' (for performance data). There's no mention of prerequisites, typical use cases, or comparison with other describe-* tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states it 'describes details' without specifying what details are returned, whether it's read-only, if it requires specific permissions, or how errors are handled. This is inadequate for a tool that likely returns complex node information.
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 purpose and appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema that likely returns detailed node information (status, capacity, conditions), the description is insufficient. It doesn't hint at the complexity of the output or behavioral aspects, leaving significant gaps for an agent to understand what to expect.
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%, so the parameter 'node' is fully documented in the schema. The description adds no additional meaning about the parameter beyond what's in the schema, 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 ('describe details') and resource ('Kubernetes node'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'list-nodes' or 'get-node-metrics', but it's not misleading or tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list-nodes' (for overview) or 'get-node-metrics' (for performance data). It lacks any context about prerequisites, typical 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?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states the action ('describe details') but doesn't disclose critical traits: whether this is a read-only operation, what details are included (e.g., status, events, specs), if it requires specific permissions, or how errors are handled. For a tool with no 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, clear sentence with zero waste—it directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly. Every part of the sentence earns its place by conveying 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 the complexity of Kubernetes operations and lack of annotations or output schema, the description is incomplete. It doesn't explain what 'details' are returned (e.g., pod status, configuration, events), potential side effects, or error conditions. For a tool that likely provides rich output, this leaves the agent without enough context to use it effectively beyond basic 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 both parameters ('pod' and 'namespace') fully documented in the schema. The description adds no additional meaning beyond the schema, such as examples of pod names or namespace contexts. 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 ('describe') and resource ('details of a Kubernetes pod'), making the purpose immediately understandable. It distinguishes from siblings like 'list-pods' or 'get-pod-metrics' by focusing on detailed description rather than listing or metrics. However, it doesn't explicitly differentiate from similar 'describe-*' tools (e.g., 'describe-deployment', 'describe-service'), which slightly limits specificity.
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 'describe-pod' over 'get-pod-metrics', 'debug-pod', or other 'describe-*' tools for different resources, nor does it specify prerequisites like needing pod access or context setup. Usage is implied only by the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe how it behaves: no information about output format, error conditions, permissions required, whether it's read-only or has side effects, or what 'details' specifically means. For a tool with zero 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, clear sentence with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential information. Every word earns its place in communicating the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'details' means, what format the output takes, or what information will be returned. Given the complexity of Kubernetes services and the lack of structured output documentation, users need more context about what to expect from this operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters are fully documented in the schema. The description doesn't add any parameter-specific information beyond what's already in the schema descriptions. It doesn't explain relationships between 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 verb ('describe') and resource ('Kubernetes service'), making the purpose immediately understandable. It distinguishes this from other describe tools (like describe-configmap, describe-deployment) by specifying the resource type, though it doesn't explicitly differentiate from list-services or get-configmap which might provide similar information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives like list-services, get-configmap, or other describe-* siblings. The description doesn't mention prerequisites, context requirements, or typical use cases for describing a service versus listing or getting 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 action without disclosing critical behavioral traits. It doesn't mention that draining typically involves evicting pods, potential service disruption, safety considerations, or what happens after draining (e.g., node becomes unschedulable). This is inadequate for a potentially destructive operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and purpose, making it immediately understandable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that performs node draining (a potentially disruptive cluster operation) with no annotations and no output schema, the description is insufficient. It doesn't explain what draining entails, typical outcomes, or safety considerations, leaving 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%, so parameters are well-documented in the schema. The description adds no additional parameter semantics beyond implying the 'node' parameter through context. 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 ('drain') and resource ('a node') with the specific context 'for maintenance'. It distinguishes from sibling tools like 'cordon-node' and 'uncordon-node' by specifying the maintenance purpose, though it doesn't explicitly contrast with 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 is provided on when to use this tool versus alternatives like 'cordon-node' or 'uncordon-node', nor are prerequisites or typical maintenance scenarios mentioned. The description only states what it does without contextual usage advice.
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 disclosing critical behavioral traits. It doesn't mention that this executes commands directly in running containers (potentially destructive), requires appropriate permissions, may have security implications, or what output to expect (e.g., stdout/stderr). The description is minimal and misses important 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 that directly states the tool's purpose with zero wasted words. It's appropriately sized for a straightforward execution tool and front-loads 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 command execution tool with no annotations and no output schema, the description is insufficient. It doesn't address the mutation nature of the operation, security requirements, expected output format, or error conditions. Given the complexity of executing commands in containers and the lack of structured metadata, more context is needed for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all parameters clearly documented in the schema itself. The description adds no additional parameter semantics beyond what's already in the schema (e.g., it doesn't explain command syntax, namespace defaults, or container selection logic). 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 ('Execute a command') and target ('in a pod container'), which is specific and unambiguous. It doesn't explicitly differentiate from sibling tools like 'run' or 'debug-pod', but the verb+resource combination is clear enough to understand the core function.
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 'run' (for creating pods), 'debug-pod' (for troubleshooting), or 'get-logs' (for viewing output). There's no mention of prerequisites, typical use cases, or exclusions, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Get' which implies a read operation, but doesn't disclose behavioral traits such as whether this requires specific permissions, what format the metrics are returned in, if there are rate limits, or if it's a real-time or aggregated view. The description is minimal and leaves critical operational details 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 extremely concise with just three words, front-loaded with the core action and resource. There's no wasted language, and it efficiently communicates the basic purpose without unnecessary elaboration, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of cluster metrics (which could include CPU, memory, network, etc.) and the lack of annotations and output schema, the description is incomplete. It doesn't specify what metrics are returned, their format, or any behavioral context. For a tool that likely provides detailed data, this minimal description leaves too many gaps for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter semantics, but that's acceptable here since there are no parameters to explain. A baseline of 4 is appropriate as the schema fully covers the absence of 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 cluster-wide metrics' clearly states the action (get) and resource (cluster-wide metrics), but it's vague about what specific metrics are included. It distinguishes from obvious siblings like 'get-node-metrics' and 'get-pod-metrics' by specifying 'cluster-wide', but doesn't clarify how it differs from other metric-related tools like 'analyze-resource-usage' or 'top-nodes'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools that might provide overlapping or related functionality (e.g., 'get-node-metrics', 'get-pod-metrics', 'analyze-resource-usage', 'top-nodes'), the description lacks any indication of context, prerequisites, or comparisons to help the 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Get' implies a read operation, but it doesn't specify whether this requires specific permissions, returns structured data or raw YAML, handles errors for non-existent CRDs, or has any rate limits. 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 with zero wasted words. It's front-loaded with the core purpose ('Get a custom resource definition'), making it immediately clear 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 the lack of annotations and output schema, the description is incomplete for a tool that likely returns detailed CRD information. It doesn't explain what 'Get' entails—whether it returns YAML, JSON, metadata, or validation schema—leaving the agent to guess about the response format and usage context in a complex Kubernetes 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?
The schema description coverage is 100%, with the 'name' parameter clearly documented in the schema. The description doesn't add any additional meaning about the parameter (e.g., format examples like 'example.com/v1' or case sensitivity), so it meets the baseline of 3 where the schema does the heavy lifting without extra value from 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 action ('Get') and resource ('custom resource definition'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list-crds' or 'describe-configmap', which would require more specific context about what makes this tool unique.
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 'list-crds' (for listing CRDs) and 'describe-configmap' (for detailed descriptions of resources), there's no indication whether this tool retrieves a single CRD by name, provides detailed metadata, or serves a different purpose entirely.
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 but offers minimal information. It states the action ('Get logs') but doesn't describe what format the logs return (text stream? structured data?), whether there are rate limits, authentication requirements, or what happens with the 'follow' parameter (continuous streaming vs. one-time fetch). For a tool with 5 parameters and no 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 states the core functionality without unnecessary words. It's appropriately sized for a straightforward tool and front-loads the essential information ('Get logs from a Kubernetes pod'). Every word earns its place with zero 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 tool's complexity (5 parameters, no output schema, no annotations), the description is insufficiently complete. It doesn't explain what the tool returns (log format, streaming behavior with 'follow'), doesn't mention error conditions (e.g., pod not found, access denied), and provides no behavioral context beyond the basic action. For a tool that could involve streaming data and multiple configuration options, 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?
The input schema has 100% description coverage, providing clear documentation for all 5 parameters. The description adds no additional parameter semantics beyond the schema's details about pod name, namespace defaulting, lines retrieval, follow behavior, and container selection. According to scoring rules, when schema_description_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 ('Get') and resource ('logs from a Kubernetes pod'), making the purpose immediately understandable. It distinguishes from many sibling tools like 'describe-pod' or 'get-pod-metrics' that provide different information. However, it doesn't explicitly differentiate from potential logging-related siblings that might exist in other 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. It doesn't mention when to choose 'get-logs' over 'describe-pod' (which might include log snippets) or 'exec' (for interactive debugging), nor does it specify prerequisites like needing pod access permissions. 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. 'Get detailed metrics' implies a read-only operation, but it doesn't specify what types of metrics are returned, whether authentication is required, if there are rate limits, or what format the output takes. This leaves significant gaps for an agent to understand 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 gets straight to the point with zero wasted words. It's appropriately sized for a simple tool with one parameter and follows good front-loading principles by immediately stating the core functionality.
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 metrics retrieval tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'detailed metrics' means in practice, what format they're returned in, or how this differs from other metrics-related tools in the server. The agent would need to guess about the tool's behavior and output.
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 'node' clearly documented as 'The name of the node'. The description doesn't add any additional semantic context beyond what the schema already provides, which is acceptable given the 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 metrics for a node'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get-cluster-metrics' or 'describe-node', which could provide similar or overlapping functionality in this 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. In a server with many sibling tools like 'get-cluster-metrics', 'describe-node', and 'top-nodes', there's no indication of what makes this tool distinct or when it's the appropriate choice.
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 'gets' metrics but doesn't disclose behavioral traits like whether this requires specific permissions, if it's a read-only operation, what format the metrics are returned in, or if there are rate limits. This leaves significant gaps for a tool that likely interacts with cluster resources.
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 directly contributes to understanding what the tool does, 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 metrics retrieval, no annotations, and no output schema, the description is insufficient. It lacks details on metrics types (e.g., CPU, memory), time ranges, aggregation methods, or error handling, leaving the agent with incomplete 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%, with clear documentation for both parameters ('pod' as required name, 'namespace' as optional with default). The description adds no additional semantic context beyond the schema, such as example pod names or namespace 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 metrics for a pod'), making the purpose immediately understandable. However, it doesn't differentiate from siblings like 'get-node-metrics' or 'get-cluster-metrics' that also retrieve metrics for different resources, leaving some ambiguity about scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'describe-pod' (which may include metrics) and 'get-cluster-metrics', there's no indication of context, prerequisites, or exclusions for selecting this specific tool.
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. 'List Helm releases' implies a read-only operation, but it doesn't specify whether this requires special permissions, how results are formatted (e.g., table vs. JSON), if it includes deleted releases, or any pagination/limiting behavior. 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 extremely concise with just three words ('List Helm releases'), front-loading the core purpose without any wasted words. It's appropriately sized for a simple listing tool with minimal parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what a 'Helm release' is in this context, what information is returned (e.g., release names, statuses, versions), or how this differs from other listing tools. For a tool in a complex Kubernetes/Helm environment with many siblings, more contextual information 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 the single parameter 'namespace' well-documented in the schema as optional and defaulting to all namespaces. The description adds no additional parameter information beyond what the schema provides, which is acceptable given the high schema coverage, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'List Helm releases' clearly states the verb ('List') and resource ('Helm releases'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list-all' or 'list-pods' that also list resources, nor does it specify what 'Helm releases' are compared to other Kubernetes resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools like 'list-all', 'list-pods', and other Helm-specific tools (e.g., 'helm-install', 'helm-status'), there's no indication of when this specific Helm listing tool is appropriate or what distinguishes it from general resource listing tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the destructive action ('Uninstall') but doesn't mention critical details like whether this is irreversible, what happens to associated resources, permission requirements, or error handling. For a destructive operation with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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, immediately conveying 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?
For a destructive tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'uninstall' entails operationally, what gets removed, potential side effects, or return values. Given the complexity and risk of Helm uninstallation, 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 additional meaning about parameters beyond what the schema provides, such as format constraints or examples. 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 action ('Uninstall') and target ('a Helm release'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'helm-list' or 'helm-upgrade' beyond the obvious action difference.
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 'delete' for non-Helm resources or 'helm-upgrade' for updates. The description lacks context about prerequisites, dependencies, or typical scenarios for uninstalling Helm releases.
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 ('upgrade') without disclosing behavioral traits. It doesn't mention whether this is a destructive operation, requires specific permissions, has side effects (e.g., pod restarts), rate limits, or what happens on failure. 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, front-loaded sentence with zero waste—'Upgrade a Helm release' directly conveys the core purpose without unnecessary words. Every part earns its place, making it highly efficient for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a Helm upgrade operation (a mutation with potential side effects), no annotations, and no output schema, the description is incomplete. It lacks crucial context like what 'upgrade' entails (e.g., rolling updates, version changes), error handling, or expected outcomes, 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%, so the schema already documents all 4 parameters (name, chart, namespace, values) with their types and basic descriptions. The description adds no additional meaning beyond what's in the schema, such as explaining parameter interactions or providing examples, but 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 'Upgrade a Helm release' clearly states the action (upgrade) and resource (Helm release), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like helm-install or helm-uninstall, which would require mentioning specific upgrade behaviors or constraints.
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 helm-install for initial deployment or helm-uninstall for removal. There's no mention of prerequisites (e.g., existing release), typical scenarios (e.g., updating chart version), or exclusions, leaving usage context entirely implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'List' implies a read-only operation, the description doesn't mention any behavioral traits such as permission requirements, rate limits, output format, or pagination behavior. This leaves significant gaps for a tool that interacts with a cluster resource.
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 three words, front-loading the essential information ('List Istio gateways') without any wasted text. Every word earns its place, 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 lack of annotations and output schema, the description is incomplete for a tool that lists cluster resources. It doesn't cover behavioral aspects like output format, error handling, or authentication needs, which are crucial for an agent to use the tool effectively in a Kubernetes/Istio 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?
The input schema has 100% description coverage, with the single parameter 'namespace' fully documented in the schema itself. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without adding 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 clearly states the action ('List') and resource ('Istio gateways'), making the purpose immediately understandable. However, it doesn't differentiate itself from sibling tools like 'istio-list-virtualservices' or general listing tools like 'list-all', which would require explicit comparison to achieve a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling listing tools available (e.g., 'istio-list-virtualservices', 'list-all', 'list-services'), the description offers no context about specific 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action ('List') without details on permissions required, output format, pagination, error handling, or rate limits. For a tool with no annotation coverage, this is insufficient to inform 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, direct sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core purpose without unnecessary elaboration, earning full marks for brevity and clarity.
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 for a tool that likely returns a list of virtual services. It doesn't explain what information is returned, how results are formatted, or any behavioral nuances, leaving significant gaps for the 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 well-documented in the schema itself. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline for high schema coverage without compensating 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 clearly states the verb ('List') and resource ('Istio virtual services'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'istio-list-gateways' or 'list-all', which could also list resources, so it doesn't fully distinguish itself from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'istio-list-gateways' or 'list-all'. It lacks context about prerequisites, exclusions, or specific scenarios where this tool is preferred, 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 this is a mutation operation ('Add or update'), but doesn't clarify whether this overwrites existing labels, merges with them, or requires specific permissions. No information about rate limits, side effects, or error conditions is provided, leaving 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 communicates the core functionality without unnecessary words. It's front-loaded with the essential action and target. Every word earns its place, making this an excellent example of conciseness in tool descriptions.
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 when labels are added/updated, whether the operation is idempotent, what permissions are required, or what the response looks like. Given the complexity of modifying Kubernetes resources, more contextual information is needed for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters are documented in the schema. The description adds no additional parameter semantics beyond what's already in the schema descriptions. It doesn't explain the format of 'labels' beyond the schema's 'key=value,key2=value2' or provide examples of valid 'resource' types. 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 ('Add or update') and target ('labels on a resource'), making the purpose immediately understandable. It distinguishes itself from siblings like 'annotate' by focusing specifically on labels rather than general annotations. However, it doesn't specify what types of resources can be labeled, 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 'annotate' or 'patch'. It doesn't mention prerequisites, permissions needed, or typical use cases. The agent must infer usage from the tool name and parameters alone, which is insufficient for optimal decision-making.
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 listing resources but fails to disclose behavioral traits like permissions needed, rate limits, output format, pagination, or error handling. This is inadequate for a tool that interacts 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, clear sentence with no wasted words, making it easy to parse and front-loaded with the core functionality. It efficiently communicates the tool's purpose without unnecessary details.
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 and the lack of annotations and output schema, the description is insufficient. It does not cover behavioral aspects, return values, or usage context, leaving gaps that could hinder an AI agent's ability to use the 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?
The input schema has 100% description coverage, with the parameter 'namespace' well-documented as optional with a default. The description adds no additional meaning beyond the schema, such as examples or constraints, but the schema's completeness justifies the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List all') and resource ('Kubernetes resources in a namespace'), making the purpose evident. However, it does not explicitly differentiate from sibling tools like 'list-pods' or 'list-deployments', which list specific resource types rather than all 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, such as more specific listing tools (e.g., 'list-pods' for pods only) or other Kubernetes operations. It lacks context about prerequisites, 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('List') but doesn't describe key behaviors: whether this is a read-only operation, what the output format looks like (e.g., list of names or full details), if it requires specific permissions, or if there are rate limits. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it 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, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every part of the sentence earns its place by specifying the tool's function efficiently.
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 cover behavioral aspects like output format, error conditions, or permissions needed, which are critical for an AI agent to use the tool correctly. While the purpose is clear, the overall context for safe and effective usage is insufficient.
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 fully documented in the schema itself (optional, defaults to current context namespace). The description adds no additional parameter information 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 description doesn't compensate but also doesn't need to.
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 ('Kubernetes configmaps in a namespace'), making the tool's purpose immediately understandable. It distinguishes itself from siblings like 'get-configmap' (which retrieves a single configmap) and 'describe-configmap' (which provides detailed information), though it doesn't explicitly mention these distinctions. The specificity is good but could be slightly enhanced with 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 siblings like 'list-all' (which might list all resources across namespaces) or 'get-configmap' (for retrieving a specific configmap), nor does it specify prerequisites such as needing Kubernetes cluster access or appropriate permissions. 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 full burden for behavioral disclosure. It mentions the namespace parameter but doesn't describe what the tool actually returns (e.g., deployment names only, full specs, status information), whether it requires specific permissions, or how it handles errors. 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, clear sentence that efficiently communicates the core purpose without any wasted words. It's appropriately sized for a simple listing tool and gets straight to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what information is returned about deployments, how results are formatted, whether there are limitations (like pagination), or what happens when the namespace doesn't exist. Given the complexity of Kubernetes deployments and the lack of structured metadata, 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 description mentions 'in a namespace' which aligns with the single parameter, but adds minimal value beyond what the schema already provides (100% coverage with clear description of the namespace parameter). The description doesn't explain namespace semantics beyond what's in the schema 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 action ('List') and resource ('Kubernetes deployments in a namespace'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list-all' or 'describe-deployment', which would require more specific context about scope or detail level.
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 like 'list-all', 'describe-deployment', and 'get-deployment-metrics' (implied by similar tools), there's no indication of when this specific listing tool is preferred or what its limitations might be.
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 disclosing behavioral traits like whether it's read-only, requires specific permissions, returns paginated results, or has rate limits. It's a basic statement that doesn't add context beyond the minimal purpose.
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 without any wasted words. It's appropriately sized for a simple tool, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 optional parameter) and no output schema, the description is minimal but inadequate. It lacks context on return values, error handling, or usage scenarios, leaving gaps that could hinder an AI agent's ability to invoke it correctly without additional inference.
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 parameter 'namespace' well-documented in the schema. The description adds no additional meaning about parameters beyond what's in the schema, so it meets the baseline of 3 for high schema coverage without compensating 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 clearly states the verb ('List') and resource ('Kubernetes endpoints in a namespace'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list-services' or 'list-all', which also list Kubernetes resources, so it misses full sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as 'list-all' for broader listings or 'describe-service' for detailed endpoint info. It lacks context on prerequisites, exclusions, or comparisons to other listing tools in the sibling set.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions listing ingresses but doesn't describe output format, pagination, permissions required, rate limits, or error conditions. For a Kubernetes tool with potential complexity, this leaves significant gaps in understanding how it 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, clear sentence that states exactly what the tool does with zero wasted words. It's appropriately sized for a simple list operation and front-loads 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 Kubernetes listing tool with no annotations and no output schema, the description is insufficient. It doesn't explain what information is returned, how results are formatted, whether authentication is needed, or how it interacts with the Kubernetes context. The description alone doesn't provide enough context for reliable 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%, with the single parameter 'namespace' fully documented in the schema. The description doesn't add any parameter semantics beyond what's already in the schema, so it meets the baseline of 3 for high schema coverage without adding 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 clearly states the action ('List') and resource ('Kubernetes ingresses in a namespace'), making the purpose immediately understandable. It doesn't explicitly distinguish from sibling tools like 'list-all' or 'list-services', but the specificity of 'ingresses' provides adequate differentiation for most 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?
No guidance is provided on when to use this tool versus alternatives like 'list-all' (which might include ingresses) or 'describe-service' (for related resources). The description only states what it does, not when it's appropriate or what prerequisites might exist.
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 does not describe traits like whether it requires read permissions, returns a filtered or full list, includes pagination, or handles errors. This leaves significant gaps in understanding the tool's behavior 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it efficient and easy to parse, with no wasted information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a tool that interacts with Kubernetes resources. It does not cover behavioral aspects like permissions, error handling, or output format, which are critical for an agent to use the tool correctly in a cluster environment, leaving significant contextual 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?
The input schema has 100% description coverage, with the parameter 'namespace' documented as optional and defaulting to the current context. The description does not add any meaning beyond this, such as explaining namespace constraints or listing behavior without a namespace. Given the high schema coverage, a baseline score of 3 is appropriate as the schema handles the parameter documentation adequately.
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 ('Kubernetes network policies in a namespace'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'list-all' or 'list-pods', which would require mentioning the specific resource type or scope to achieve 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 does not mention sibling tools like 'list-all' (which might list all resources) or 'describe-networkpolicy' (if it existed), nor does it specify prerequisites such as needing cluster access or namespace permissions, 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 it 'lists' pods, implying a read-only operation, but doesn't disclose behavioral traits like whether it requires specific permissions, how results are formatted (e.g., table vs JSON), pagination behavior, or what happens with invalid namespaces. For a tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 listing tool and front-loads the core functionality 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 Kubernetes tool with no annotations and no output schema, the description is too minimal. It doesn't explain what information is returned about pods (e.g., names, statuses, ages), how to interpret results, or any prerequisites. Given the complexity of Kubernetes operations and the lack of structured metadata, 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 the single parameter 'namespace' fully documented in the schema. The description adds no additional parameter semantics beyond what's already in the structured schema, so it meets the baseline score of 3 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 verb ('List') and resource ('Kubernetes pods'), specifying the scope ('in a namespace'). It distinguishes from general list tools like 'list-all' by focusing on pods, but doesn't explicitly differentiate from other pod-related tools like 'describe-pod' or 'get-pod-metrics'.
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 like 'list-all', 'describe-pod', 'get-pod-metrics', and 'debug-pod', there's no indication of when this specific listing function is appropriate versus other pod-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?
No annotations are provided, so the description carries the full burden. It states the action ('list') but does not disclose behavioral traits like whether it requires read permissions, returns all PVCs or a filtered subset, handles errors, or includes pagination. This leaves significant gaps for a tool that 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, direct sentence with no wasted words, making it highly concise and front-loaded. 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 the complexity of Kubernetes operations and the lack of annotations and output schema, the description is incomplete. It does not cover behavioral aspects like permissions, error handling, or output format, which are crucial for an AI agent to use the tool effectively in this 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%, with the single parameter 'namespace' fully documented in the schema. The description does not add any meaning beyond the schema, such as explaining namespace context or default behavior, 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.
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 ('Kubernetes persistent volume claims in a namespace'), making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like 'list-pv' (persistent volumes) or 'list-all', which might list PVCs among other resources, leaving some room for sibling distinction.
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 does not mention sibling tools like 'list-all' for broader listings or 'describe-pod' for detailed PVC information, nor does it specify prerequisites such as needing Kubernetes access or namespace 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 the full burden. It states the action ('List') but does not disclose behavioral traits like permissions needed, rate limits, pagination, output format, or error handling. This leaves significant gaps for a tool that interacts with Kubernetes resources.
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, clearly front-loading the core action. It is appropriately sized for a simple list tool, 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 no annotations and no output schema, the description is incomplete for a Kubernetes tool. It lacks details on behavior, output format, error cases, and how it differs from siblings, failing to provide sufficient context 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?
The input schema has 100% description coverage, with the parameter 'namespace' documented as optional and defaulting to the current context. The description does not add meaning beyond this, so it meets the baseline of 3 for high schema coverage without extra param details.
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 ('Kubernetes service accounts in a namespace'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'list-all' or 'list-pods', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as 'list-all' or other list-* tools. It lacks context about prerequisites, exclusions, or comparisons to siblings, offering minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't explain important behavioral aspects: whether this creates a persistent or temporary connection, what happens when the command terminates, whether it requires specific permissions, if it blocks execution, or what side effects might occur. For a network operation tool, 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 states the core functionality without unnecessary words. It's appropriately sized for what it communicates and is front-loaded with the essential information. There's zero waste in the phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that performs network port forwarding (a potentially complex operation with side effects), the description is insufficiently complete. With no annotations, no output schema, and no behavioral context, users lack critical information about what the tool actually does beyond the basic concept. The presence of a sibling tool 'port-forward-pod' creates additional confusion that isn't addressed.
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 doesn't add any parameter-specific information beyond what's in the schema. It doesn't explain relationships between parameters (like how localPort and targetPort interact) or provide usage examples, so it meets the baseline but doesn't enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('port forward') and target ('a Kubernetes service to a local port'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'port-forward-pod', which appears to serve a similar function for pods rather than services, leaving some ambiguity about when to choose one over the other.
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 a sibling tool named 'port-forward-pod' in the list, there's a clear need for differentiation that isn't addressed. No context about prerequisites, when-not-to-use scenarios, or comparison with other port-forwarding methods is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Restart' implies a mutation operation, but the description doesn't specify what 'restart' entails (e.g., whether it triggers a rolling restart, recreates pods, or causes downtime). It also omits critical information like required permissions, side effects (e.g., temporary service disruption), or error conditions. 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 action ('Restart a deployment') without unnecessary words. Every part of the sentence earns its place by specifying the action and target, making it easy to parse quickly. No fluff or redundancy is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation affecting deployments) and lack of annotations or output schema, the description is insufficiently complete. It doesn't explain what 'restart' means behaviorally, what the expected outcome is, or any error handling. For a tool that could disrupt services, more context on safety and effects is needed to guide proper 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 fully documents both parameters ('deployment' as required name, 'namespace' as optional with default). The description adds no additional parameter semantics beyond what's in the schema—it doesn't clarify parameter relationships, constraints, or examples. This meets the baseline score when schema coverage is high, but adds no extra 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 clearly states the action ('restart') and target resource ('a deployment'), making the purpose immediately understandable. It distinguishes itself from sibling tools like 'rollout-history' and 'rollout-status' by focusing on the restart action rather than viewing history or status. However, it doesn't explicitly differentiate from other mutation tools like 'scale-deployment' or 'set-image' that also affect 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 (e.g., deployment must exist), when not to use it (e.g., during critical operations), or how it differs from similar tools like 'scale-deployment' (which might achieve similar results through scaling to zero then back up). The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. While 'Check' implies a read-only operation, the description doesn't specify what 'rollout status' actually means, what information it returns, whether it has side effects, or any authentication/permission requirements. For a 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 gets straight to the point with zero wasted words. It's appropriately sized for a simple status-checking tool and front-loads the essential information 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 read operation with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'rollout status' means, what format the information returns, or how this differs from other deployment-related tools in the extensive sibling list. The context signals indicate this is a simple tool, but the description leaves too many practical usage questions unanswered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, both parameters are already documented in the schema. The description doesn't add any meaningful semantic context beyond what the schema provides about 'deployment' and 'namespace' parameters. The baseline score of 3 reflects adequate but unenhanced parameter documentation.
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 ('Check') and target ('rollout status of a deployment'), providing a specific verb+resource combination. However, it doesn't differentiate itself from potential sibling tools like 'rollout-history' or 'describe-deployment' that might also provide deployment status information, preventing 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 about when to use this tool versus alternatives. With many sibling tools like 'describe-deployment', 'rollout-history', 'list-deployments', and 'argocd-app-status' that might provide overlapping or related functionality, there's no indication of when this specific rollout status check is preferred or appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Run a pod' which implies a creation/execution operation, but doesn't clarify if this is a one-time execution, whether it persists, what permissions are required, or potential side effects like resource consumption. It misses key behavioral traits like whether it's idempotent or how it handles errors.
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, clear sentence that directly states the tool's purpose. There's no wasted language or unnecessary elaboration, making it easy to parse and understand 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 tool that creates/executes pods (a potentially complex operation with no annotations and no output schema), the description is insufficient. It doesn't explain what 'Run' entails operationally, what the expected outcome is, or any constraints. Given the lack of structured data to compensate, more context about behavior and results 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 minimal value by mentioning 'with a specific image' which corresponds to the 'image' parameter, but doesn't provide additional context beyond what's in 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 action ('Run') and resource ('a pod'), specifying the key parameter ('with a specific image'). It distinguishes from siblings like 'create-namespace' or 'debug-pod' by focusing on pod execution, though it doesn't explicitly differentiate from similar tools like 'exec' or 'debug-pod' that also interact with pods.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention when to choose 'run' over 'create-deployment' or 'debug-pod', nor does it specify prerequisites like needing cluster access or appropriate permissions. The description lacks context for selection among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While 'scale' implies a mutation operation, it doesn't disclose important behavioral traits: whether this requires specific RBAC permissions, if it's idempotent, what happens to existing pods during scaling, potential rate limits, or error conditions. For a Kubernetes mutation tool with zero annotation coverage, this leaves critical operational context 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 states the core functionality without unnecessary words. It's appropriately sized for a straightforward scaling operation and front-loads the essential information. Every word earns its place with zero waste or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a Kubernetes mutation tool with no annotations and no output schema, the description is incomplete. It doesn't address permissions requirements, error handling, what the tool returns (success confirmation, deployment object, or nothing), or how scaling interacts with other deployment properties. Given the complexity of Kubernetes operations and the lack of structured safety information, this description leaves too many operational questions unanswered.
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 thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain replica constraints, namespace defaults in practice, or deployment naming conventions. With complete schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.
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 ('Kubernetes deployment') with the specific outcome ('to a specified number of replicas'). It distinguishes from siblings like 'describe-deployment' or 'list-deployments' by focusing on modification rather than inspection. However, it doesn't explicitly differentiate from similar mutation tools like 'set-image' or 'patch' that also modify 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 (e.g., needing appropriate permissions), when scaling is appropriate versus other deployment modifications, or what happens if scaling fails. With many sibling tools available for Kubernetes operations, 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 full burden for behavioral disclosure. While 'Update' implies mutation, it doesn't specify whether this requires special permissions, whether it triggers a rollout restart, what happens to existing pods, or potential side effects. 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 with zero wasted words. It's appropriately sized for the tool's complexity 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 mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after the update, whether changes are immediate, what validation occurs, or what the response contains. Given the complexity of updating deployment images in 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?
Schema description coverage is 100%, so all parameters are documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema descriptions. 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 action ('Update') and target ('image of a deployment'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'patch' or 'scale-deployment' that might also modify deployments, nor does it specify this is specifically for container images rather than other deployment aspects.
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 'patch' or 'scale-deployment'. There's no mention of prerequisites, when-not-to-use scenarios, or comparison with sibling tools that might perform similar functions.
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 'resource usage' but fails to specify what metrics are shown, how data is formatted, whether it's real-time or historical, or any constraints like permissions or rate limits. This leaves significant gaps for a tool that likely interacts with system resources.
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 scan and understand quickly, which is ideal 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 monitoring resource usage, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'resource usage' includes, the output format, or behavioral aspects like data freshness or limitations, leaving the agent with inadequate information for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 100% description coverage, so the description doesn't need to add parameter details. It correctly avoids redundancy, and with 0 parameters requiring explanation from the description, it meets the baseline for adequate coverage without unnecessary repetition.
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 'Show resource usage for pods' clearly states the verb ('show') and resource ('pods'), but it's vague about what 'resource usage' specifically entails (e.g., CPU, memory, or other metrics). It doesn't differentiate from siblings like 'get-pod-metrics' or 'top-nodes', leaving ambiguity in scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'get-pod-metrics' or 'analyze-resource-usage'. The description lacks context about prerequisites, exclusions, or typical use cases, offering no help in 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. It states the tool marks a node as schedulable, which implies a mutation (changing node state) but does not disclose behavioral traits such as required permissions, whether it's idempotent, potential side effects, or error conditions. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse. Every part of the sentence earns its place by conveying essential information concisely.
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 is a mutation (implied by 'mark') with no annotations and no output schema, the description is incomplete. It lacks details on behavioral context (e.g., permissions, effects), usage guidelines, and what to expect upon execution. For a tool that modifies cluster state, this minimal description leaves significant gaps for an agent to operate safely and 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 single parameter 'node' documented as 'The name of the node to uncordon'. The description adds no additional meaning beyond this, as it does not elaborate on parameter syntax, format, or constraints. With high schema coverage, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Mark a node as schedulable' clearly states the action (mark) and resource (node) with a specific purpose (making it schedulable). It distinguishes from sibling 'cordon-node' by implying an opposite operation, though not explicitly named. It avoids tautology by not just restating the tool name 'uncordon-node'.
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 explicit guidance on when to use this tool versus alternatives. It implies usage when a node needs to be made schedulable, but does not mention prerequisites (e.g., node must be cordoned first), exclusions, or direct alternatives like 'cordon-node' for the opposite action. This leaves the agent to infer context 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 of behavioral disclosure. It states the action ('Switch to') but doesn't mention critical details like whether this changes global state, requires specific permissions, has side effects, or how errors are handled. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct 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.
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 lacks details on behavioral traits (e.g., state changes, error handling), usage context, and output expectations, leaving significant gaps for an agent to understand the tool fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents the 'context' parameter fully. The description doesn't add any additional meaning beyond what the schema provides (e.g., format examples or constraints), which aligns with 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 ('Switch to') and target resource ('kubectl context'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'current-context' or 'get-contexts', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites (e.g., needing existing contexts), exclusions, or comparisons to sibling tools like 'current-context' for checking the current 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. 'List ArgoCD applications' implies a read-only operation but doesn't specify authentication requirements, rate limits, pagination behavior, or what happens when namespace isn't provided. For a tool with zero annotation coverage, this is insufficient behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient phrase that communicates the core purpose without any wasted words. It's appropriately sized for a simple listing tool 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 simple listing tool with one optional parameter and 100% schema coverage, the description is minimally adequate. However, without annotations or output schema, the agent lacks information about authentication requirements, response format, and how this differs from other listing tools. The description meets basic requirements but could provide more 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%, with the single parameter 'namespace' well-documented in the schema. The description adds no additional parameter information beyond what's already in the structured schema. 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 'List ArgoCD applications' clearly states the verb ('List') and resource ('ArgoCD applications'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list-all' or 'list-pods' - the agent must infer that this specifically lists ArgoCD applications rather than general Kubernetes resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling listing tools available (list-all, list-pods, list-deployments, etc.), the agent must deduce from the name 'argocd-list-apps' that this is for ArgoCD-specific applications rather than general Kubernetes resources.
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 behavioral outcome ('Mark a node as unschedulable') but doesn't disclose important traits: whether this requires admin permissions, if it's reversible (implied but not stated), what happens to existing pods (they remain running), or any side effects. For a mutation tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 simple operation with one parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter mutation tool with no annotations and no output schema, the description is minimally adequate but incomplete. It explains what the tool does but lacks behavioral context, usage guidance, and output information. Given the simplicity of the operation, it's functional but could be more 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 the single parameter 'node' clearly documented in the schema as 'The name of the node to cordon'. The description adds no additional parameter information beyond what the schema provides, 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 ('Mark as unschedulable') and resource ('a node'), making the purpose immediately understandable. It doesn't explicitly distinguish from sibling tools like 'drain-node' or 'uncordon-node', but the verb 'cordon' is specific enough in Kubernetes context to imply isolation without eviction.
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 'drain-node' (which also makes nodes unschedulable but evicts pods) or 'uncordon-node' (the reverse operation). The description lacks context about typical 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?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Create a backup' implies a write operation that likely requires specific permissions and may have side effects, but the description doesn't mention authentication needs, whether the operation is reversible, potential impacts on cluster performance during backup, or what happens if the output file already exists. It provides minimal behavioral 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.
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 tool with two well-documented parameters 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a write operation with no annotations and no output schema, the description is minimally adequate but has clear gaps. It states what the tool does but doesn't cover important contextual aspects like what 'cluster resources' specifically includes, whether the backup is incremental or full, expected runtime, or what format the backup file will be in. The 100% schema coverage helps, but more behavioral context would be valuable.
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 fully documents both parameters (namespace and output). The description doesn't add any parameter-specific information beyond what's in the schema, such as format examples for the output path or namespace naming conventions. 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 action ('create') and resource ('backup of cluster resources'), providing a specific purpose. However, it doesn't differentiate this backup creation tool from potential sibling tools that might also involve backup operations (none are listed among siblings, but the description doesn't explicitly address this).
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, timing considerations, or compare it to other backup-related operations that might exist in the broader system 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 provided, the description carries the full burden of behavioral disclosure. It states the action ('describe details') but doesn't clarify what 'details' include, whether this is a read-only operation, if it requires specific permissions, or what the output format looks like. For a tool accessing sensitive resources like secrets, 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 that gets straight to the point with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (accessing sensitive Kubernetes secrets), no annotations, and no output schema, the description is minimally adequate but has clear gaps. It states what the tool does but doesn't address behavioral aspects like safety, permissions, or output format, which are important for this 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 already documents both parameters thoroughly. The description doesn't add any additional meaning about parameters beyond what's in the schema, such as format examples or constraints. 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 ('describe') and resource ('Kubernetes secret'), making the purpose immediately understandable. It distinguishes from siblings like 'get-secret' by specifying 'details' rather than just retrieval, though it doesn't explicitly contrast with 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 is provided on when to use this tool versus alternatives like 'get-secret' or 'list-secrets'. The description doesn't mention 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('List') but does not describe output format, pagination, error handling, or any constraints like rate limits or permissions required. This leaves significant gaps for a tool that interacts with kubectl contexts.
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 unnecessary words. It is front-loaded and wastes no space, 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 lack of annotations and output schema, the description is incomplete. It does not explain what the output looks like (e.g., list format, context details), behavioral aspects, or how it fits with sibling tools. For a tool in a complex kubectl environment, more context is needed to ensure proper usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter details, which is appropriate, but it could have mentioned if any implicit parameters exist (e.g., output format). Baseline is 4 for zero parameters, as the schema fully covers the lack of inputs.
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 kubectl contexts'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'current-context' or 'use-context', which are related but serve different purposes, so it misses full 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, such as 'current-context' for the active context or 'use-context' for switching contexts. There is no mention of prerequisites, exclusions, or specific scenarios for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. While 'Get the status' implies a read-only operation, it doesn't explicitly state whether this requires specific permissions, whether it's safe to run, what the output format looks like, or any rate limits. For a tool that presumably queries cluster state with no annotation coverage, this leaves significant behavioral questions unanswered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 without any wasted words. It's appropriately sized for a simple status-checking tool and front-loads the essential information. Every word earns its place in this minimal but complete statement of 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 (querying Helm release status) and the absence of both annotations and output schema, the description is minimally adequate but leaves gaps. It identifies what the tool does but doesn't provide behavioral context, usage guidance, or output information. For a tool that interacts with Helm releases in a Kubernetes environment, more context about what 'status' includes and typical use cases 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 clearly documented in the schema itself. The description adds no additional parameter information beyond what's already in the structured schema fields. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no parameter information in the description, which applies 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 action ('Get the status') and target resource ('Helm release'), making the purpose immediately understandable. It distinguishes from siblings like helm-install, helm-list, helm-uninstall, and helm-upgrade by focusing on status retrieval rather than installation, listing, removal, or updating operations. However, it doesn't explicitly differentiate from rollout-status, which also deals with status but for different 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 alternatives. It doesn't mention when to choose helm-status over helm-list (which might show status information), rollout-status (for deployment rollouts), or other status-checking tools. There's no context about prerequisites, typical use cases, or situations where this tool would be preferred or inappropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a list operation (implying read-only), but doesn't mention permissions needed, rate limits, output format, pagination, or error conditions. For a Kubernetes tool with zero 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 with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a simple list operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with one optional parameter and 100% schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it should ideally mention the return format or typical output structure to help the agent understand what to expect.
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 fully documents the optional namespace parameter. The description adds no additional parameter semantics beyond what's in the schema, but 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.
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 ('Kubernetes cronjobs in a namespace'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list-jobs' or 'list-all', which could cause confusion about scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list-jobs' or 'list-all'. It doesn't mention prerequisites, context requirements, 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states the action without mentioning permissions required, output format, pagination, error handling, or whether it's a read-only operation. This leaves significant gaps for an agent to understand how to use it effectively.
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 for a simple listing tool and front-loads the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with one optional parameter and no output schema, the description is minimally adequate but lacks important context. Without annotations or output schema, it should ideally mention the return format (e.g., list of HPA objects) or behavioral aspects like permissions. The completeness is borderline given the tool's low complexity.
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 input schema already documents the single optional parameter 'namespace' with its default behavior. The description doesn't add any parameter-specific information beyond what's in the schema, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 ('Kubernetes horizontal pod autoscalers') with scope ('in a namespace'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list-all' or 'list-deployments', which would require mentioning HPA-specific characteristics.
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 'list-all' (which might list all resources including HPAs) or 'get-pod-metrics' (which might relate to autoscaling data), nor does it specify prerequisites or exclusions for usage.
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 listing operation, which implies read-only behavior, but doesn't disclose any behavioral traits like whether it requires specific permissions, how results are formatted, if there's pagination, or what happens with invalid namespaces. 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 directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with zero wasted content.
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 listing tool with one well-documented parameter and no output schema, the description is minimally adequate. However, without annotations or output schema, it should ideally provide more behavioral context about what the listing returns and any constraints. The completeness is borderline given the lack of structured metadata.
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 input schema already fully documents the optional 'namespace' parameter with its default behavior. The description doesn't add any parameter information beyond what's in the schema, 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 ('List') and resource ('Kubernetes jobs in a namespace'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list-all', 'list-cronjobs', or 'list-pods', which would require specifying it's specifically for Job resources rather than a general listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling listing tools (e.g., 'list-all', 'list-cronjobs', 'list-pods'), the description doesn't indicate this is specifically for Job resources or suggest when to choose it over other listing commands.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action is a list operation, implying it's read-only and non-destructive, but doesn't confirm this or add context about permissions, rate limits, output format, or error conditions. For a tool with zero 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 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 earns its place by conveying essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one optional parameter) and high schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it lacks behavioral context (e.g., read-only nature, permissions) and doesn't describe the return format. For a list operation, this leaves the agent uncertain about what to expect.
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 'namespace' fully documented in the schema. The description doesn't add any parameter details beyond what the schema provides, such as clarifying the 'current context namespace' default or namespace syntax. Baseline 3 is appropriate when the schema does all the work.
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 ('Kubernetes limit ranges in a namespace'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from similar list tools like list-configmaps or list-pods, which would require mentioning the specific resource type (limit ranges) as a distinguishing factor.
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 it to sibling tools like list-all or list-resourcequotas, or indicate when limit ranges are relevant versus other resource types. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('List all') but doesn't mention permissions required, rate limits, pagination, output format, or any side effects. For a read operation in a complex system like Kubernetes, this lack of detail 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, clear sentence with no wasted words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of Kubernetes operations and the lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions, output structure, or error handling, which are crucial for effective tool use in this context.
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 parameter semantics, but this is acceptable given the schema completeness, aligning with the baseline for zero 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 'List all Kubernetes namespaces' clearly states the verb ('List') and resource ('Kubernetes namespaces'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list-all' or 'list-pods' beyond specifying the resource type, which is adequate but not optimal for sibling distinction.
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 'list-all' (which might list all resources) and 'create-namespace' (for creation), there's no explicit or implied context for choosing this specific listing tool, leaving 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 list operation but doesn't disclose behavioral traits like whether it requires specific permissions, how results are formatted, if there's pagination, or what happens on empty results. For a tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
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 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 has no annotations, no output schema, and 0 parameters, the description is too minimal. It doesn't explain what the tool returns (e.g., list format, fields included) or provide any behavioral context, leaving significant gaps for an AI agent to understand how to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description doesn't need to add parameter information, and it correctly doesn't mention any parameters, earning a baseline score of 4 for this context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('Kubernetes persistent volumes'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list-pvc' or 'list-all' which also list Kubernetes resources, so it misses full sibling distinction.
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 'list-pvc' (persistent volume claims) and 'list-all' (all resources), there's no indication of when this specific tool is appropriate or what makes it different.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While 'List' implies a read operation, it doesn't disclose important behavioral traits like whether authentication is required, if there are rate limits, what format the output takes, or if there are pagination considerations. The description is minimal and 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 that states exactly what the tool does without any wasted words. It's appropriately sized for a simple listing tool 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 simple listing tool with one optional parameter and no output schema, the description is minimally adequate. However, given the lack of annotations and the presence of many similar listing tools in the sibling set, more context about when to use this specific tool would improve completeness. The description meets basic requirements but doesn't excel.
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 fully documents the single optional parameter. The description doesn't add any parameter semantics beyond what's in the schema - it mentions 'in a namespace' which aligns with the parameter but provides no additional context about namespace selection or defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('Kubernetes resource quotas in a namespace'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list-all' or 'list-namespaces', which could provide similar listing functionality for different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling listing tools (e.g., 'list-pods', 'list-configmaps', 'list-all'), there's no indication of when resource quotas specifically should be listed or what makes this tool the appropriate choice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it's a list operation, implying read-only behavior, but doesn't disclose critical traits like whether it requires specific permissions, returns paginated results, includes default namespaces, or handles errors. For a tool with zero 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 front-loads the core purpose without any wasted words. It's appropriately sized for a simple list tool, making it easy 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 low complexity (one optional parameter) and high schema coverage, the description is minimally adequate but lacks output details (no output schema) and behavioral context. It covers the basic what but not the how or when, making it incomplete for optimal agent use without additional inference.
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 parameter 'namespace' fully documented in the schema as optional and defaulting to current context. The description adds no additional meaning beyond implying namespace scope, which is already covered. 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 action ('List') and resource ('Kubernetes role bindings') with scope ('in a namespace'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list-clusterrolebindings' or 'list-roles', which would require mentioning it's namespace-scoped versus cluster-scoped or distinguishing role bindings from roles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list-clusterrolebindings' or 'list-roles', nor does it mention prerequisites such as needing proper Kubernetes context or permissions. It lacks explicit when/when-not instructions or named alternatives, leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it's a list operation, implying read-only behavior, but doesn't mention output format, pagination, error conditions, or authentication requirements. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it 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, clear sentence with no wasted words. It's front-loaded with the core purpose and efficiently communicates the essential information without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one optional parameter) and high schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it should ideally provide more context about the return format or typical usage scenarios to help an agent understand what to expect from this operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'namespace' fully documented in the schema. The description doesn't add any additional meaning beyond what's in the schema (e.g., it doesn't clarify default behavior or namespace constraints), so it meets the baseline score 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 ('List') and resource ('Kubernetes roles in a namespace'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list-clusterroles' or 'list-rolebindings', which would require mentioning it's specifically for namespace-scoped roles rather than cluster-wide roles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention sibling tools like 'list-clusterroles' for cluster-scoped roles or 'list-rolebindings' for related resources, nor does it specify prerequisites or typical use cases for listing roles.
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 ('list') but doesn't describe what the output looks like (e.g., format, pagination), permissions required, rate limits, or error conditions. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it 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 any fluff or redundancy. 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one optional parameter) and high schema coverage, the description is minimally adequate. However, with no output schema and no annotations, it lacks details on return values, permissions, or error handling, which could be important for a Kubernetes operation. It's complete enough for basic use but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'namespace' clearly documented as optional with a default. The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline score 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 ('Kubernetes secrets in a namespace'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list-all' or 'get-secret', which could provide similar functionality, so it doesn't reach the highest 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 'list-all' (which might list all resources including secrets) or 'get-secret' (which retrieves a specific secret). There's no 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?
No annotations are provided, so the description carries full burden. It states the action ('List') but does not disclose behavioral traits like whether it requires specific permissions, returns paginated results, or includes default namespace handling beyond the schema. This leaves significant gaps for a read operation 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 a single, efficient sentence with zero waste, front-loading the core action and resource. It is appropriately sized for a simple list tool, 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 low complexity (1 optional parameter, no output schema, no annotations), the description is minimally adequate but lacks completeness. It does not cover behavioral aspects like response format or error handling, which would be helpful despite the simple schema.
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 the optional 'namespace' parameter. The description adds no additional meaning beyond what the schema provides, such as format examples or edge cases, resulting in the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('Kubernetes services') with scope ('in a namespace'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'list-all' or 'describe-service', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as 'list-all' for broader listing or 'describe-service' for detailed information. It lacks explicit when/when-not instructions or named alternatives, leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. While 'Show' implies a read-only operation, the description doesn't specify what format the history takes, whether it includes timestamps, status changes, or other details. It also doesn't mention any authentication requirements, rate limits, or potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that directly states the tool's purpose without any unnecessary words. It's perfectly front-loaded 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with 2 parameters and no output schema, the description is minimally adequate. However, without annotations or output schema, it should ideally provide more context about what the rollout history includes (e.g., revision numbers, timestamps, status changes) and how it differs from related deployment 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?
With 100% schema description coverage, both parameters are already documented in the schema. The description doesn't add any additional meaning about the parameters beyond what's in the schema descriptions. The baseline score of 3 reflects adequate but minimal value addition.
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 ('Show') and target ('rollout history of a deployment'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential siblings like 'rollout-status' or 'describe-deployment', which might also provide deployment-related information.
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 'rollout-status', 'describe-deployment', and 'list-deployments' available, there's no indication of what makes 'rollout-history' distinct or when it should be preferred over these other deployment-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'show resource usage' but doesn't specify what resources (e.g., CPU, memory), the output format, whether it's real-time or historical, or any limitations like permissions or rate limits. 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 any wasted 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 monitoring resource usage in a Kubernetes environment, the description is incomplete. With no annotations, no output schema, and a vague purpose, it lacks details on what 'resource usage' entails, the output format, or behavioral traits. This makes it inadequate for an agent to use the tool effectively without additional context.
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, meaning there are no parameters to document. The description doesn't need to add parameter semantics, so it meets the baseline of 4 for tools with no parameters, as it doesn't have to compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('show') and resource ('resource usage for nodes'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get-node-metrics' or 'describe-node', which might have overlapping functionality in a Kubernetes context, so it doesn't achieve full 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. With many sibling tools like 'get-node-metrics', 'describe-node', and 'list-nodes' that might relate to node monitoring or information, there's no indication of context or prerequisites for choosing this tool.
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. 'Get available API versions' implies a read-only operation but doesn't disclose behavioral traits such as authentication requirements, rate limits, output format, or error handling. This leaves significant gaps for an agent to understand how to interact with it effectively.
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 available API versions') that is front-loaded and wastes no words. Every part of it contributes directly to understanding the tool's 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?
Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on behavior, output, or context, making it incomplete for full agent understanding despite the simple nature.
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 info, but that's appropriate here. A baseline of 4 is applied since 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 'Get available API versions' clearly states the verb ('Get') and resource ('available API versions'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'api-resources' or 'version', which might have overlapping functionality, preventing 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 siblings like 'api-resources' and 'version' that might relate to API information, there's no indication of context, prerequisites, or exclusions for this tool's usage.
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 'Get' implies a read-only operation, the description doesn't explicitly state this or mention any side effects, authentication requirements, rate limits, or error conditions. For a kubectl tool that interacts with cluster configurations, this represents a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that communicates the essential purpose without any unnecessary words. It's perfectly front-loaded with the core functionality and contains zero redundant information, making it maximally efficient for an agent to parse and understand.
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 tool with no output schema, the description adequately communicates what the tool does at a basic level. However, given that this is a kubectl context operation (potentially involving cluster authentication and configuration), the description should ideally mention what format the context information is returned in or what happens if no context is set, especially since no output schema is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't waste space discussing non-existent parameters, earning a baseline score of 4 for not introducing confusion about parameters that don't exist.
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 the resource ('current kubectl context'), making the purpose immediately understandable. It distinguishes itself from the sibling tool 'get-contexts' by focusing on the current context rather than listing all contexts. However, it doesn't explicitly mention this distinction in the description text itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get-contexts' or 'use-context'. It doesn't mention prerequisites, typical use cases, or any contextual factors that would help an agent decide when this tool is appropriate versus other kubectl 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?
No annotations are provided, so the description carries full burden for behavioral disclosure. While 'List' implies a read-only operation, it doesn't specify output format, pagination behavior, permission requirements, or whether it shows all bindings or only those accessible to the current user. For a Kubernetes tool with zero 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 states exactly what the tool does with zero wasted words. It's appropriately sized for a simple list operation 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool with no output schema, the description is minimally complete - it tells you what resource you'll get. However, without annotations or output schema, it doesn't address important contextual aspects like permission requirements, output format, or how results are presented. The description meets basic requirements but leaves gaps an agent would need to discover through trial.
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 (schema coverage 100%), so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose. With no parameters to document, this earns a high baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('Kubernetes cluster role bindings'), making the purpose immediately understandable. It distinguishes from siblings like 'list-rolebindings' (which are namespace-scoped) by specifying 'cluster' scope. However, it doesn't explicitly differentiate from 'list-all' which might include cluster role bindings among other resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when you'd want cluster role bindings specifically versus regular role bindings, nor does it reference sibling tools like 'list-rolebindings' or 'list-all' as alternatives. The agent must infer usage context from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'List' implies a read operation, but the description doesn't specify whether this returns all cluster roles, if there's pagination, what format the output takes, or any authentication requirements. For a 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 essential purpose without any wasted words. It's appropriately sized for a simple listing operation and gets straight to the point with no unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter listing tool, the description covers the basic purpose adequately. However, without annotations or an output schema, it doesn't address important behavioral aspects like output format, pagination, or error conditions. The description is minimally viable but leaves gaps that would help an agent use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't discuss parameters since none exist, maintaining focus on the tool's purpose rather than attempting to document non-existent inputs.
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 ('Kubernetes cluster roles'), making the purpose immediately understandable. It distinguishes from other list tools by specifying the exact resource type, though it doesn't explicitly differentiate from similar tools like list-roles or list-clusterrolebindings beyond the resource name.
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 list-roles, list-clusterrolebindings, and list-all available, there's no indication of when this specific listing operation is preferred or what distinguishes it from other listing mechanisms.
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' implies a read operation, the description doesn't specify whether this requires specific permissions, what format the output takes, whether it's paginated, or if there are any rate limits. For a tool with zero annotation coverage, this represents significant gaps in behavioral understanding.
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 simple listing tool and gets straight to the point with no unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter listing tool with no output schema, the description provides the minimum viable information about what the tool does. However, without annotations or output schema, it doesn't address important behavioral aspects like output format, permissions needed, or how it differs from similar sibling tools, leaving gaps in contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema description coverage, the baseline score would be 4 even with no parameter information in the description. The description appropriately doesn't mention parameters since none exist, which is correct for this tool.
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 ('Kubernetes custom resource definitions'), making the purpose immediately understandable. However, it doesn't differentiate from similar sibling tools like 'list-all' or 'get-crd', which could cause confusion about when to use this specific tool versus alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'list-all' (which might include CRDs) and 'get-crd' (which might retrieve a specific CRD), the agent has no indication of when this particular listing tool is appropriate versus those other options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('List') but doesn't describe what the output looks like (e.g., table format, JSON), whether it's paginated, if it requires cluster permissions, or any rate limits. For a read operation in a Kubernetes context, 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, clear sentence with zero wasted words. It's front-loaded with the essential information ('List all Kubernetes nodes') and doesn't include any unnecessary details. This is an excellent example of conciseness for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally complete. It tells what the tool does but lacks important context about output format and behavioral characteristics. For a Kubernetes listing tool with many sibling alternatives, more guidance would be helpful, but the basics are covered.
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 correctly doesn't mention any parameters, which is appropriate. It gets a baseline 4 since it doesn't need to compensate for missing schema information.
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 Kubernetes nodes'), making the purpose immediately understandable. It distinguishes from siblings like 'describe-node' or 'get-node-metrics' by focusing on listing rather than describing or measuring. However, it doesn't explicitly differentiate from 'list-all' which might include nodes among other resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'list-nodes' over 'describe-node' for detailed information, 'get-node-metrics' for performance data, or 'list-all' for a broader view. No prerequisites or contextual usage hints are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action but doesn't describe what happens during execution (e.g., establishes a persistent tunnel, runs until interrupted, requires network access), potential side effects, or error conditions. For a network operation tool, this leaves critical 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 directly states the tool's purpose with zero wasted words. It's appropriately sized for a straightforward operation and is front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a network tunneling operation with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., success confirmation, tunnel details, error messages), runtime behavior, or interaction patterns. For a tool that establishes persistent connections, more contextual information 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 fully documents all four parameters (pod, namespace, localPort, targetPort) with clear descriptions. The description adds no additional parameter semantics beyond what's in the schema, which is acceptable given the high coverage, resulting in the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('port forward') and resource ('a Kubernetes pod to a local port'), distinguishing it from the sibling 'port-forward' tool (which likely forwards services or other resources). It uses precise technical terminology that unambiguously defines the tool's function.
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 the sibling 'port-forward' tool, nor does it mention prerequisites (e.g., requiring kubectl access, cluster connectivity) or typical use cases (e.g., debugging, local development). It lacks any context about when this specific pod-forwarding tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. While 'Get' implies a read-only operation, it doesn't disclose behavioral traits like authentication requirements, rate limits, or what specific version information is returned (e.g., server version, client version, API versions). This leaves significant gaps 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 with zero wasted words. It's front-loaded with the core purpose, making it easy for an agent to parse quickly without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema), the description is adequate but incomplete. It lacks details on what 'Kubernetes version information' includes (e.g., server vs. client, format) and behavioral context, which could help the agent use it effectively despite the low complexity.
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 appropriately doesn't discuss parameters, earning a high baseline score since it doesn't add unnecessary information beyond what the schema provides.
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 ('Kubernetes version information'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'api-versions' or 'current-context' that might also provide version-related information, preventing 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 siblings like 'api-versions' and 'current-context' that might overlap in providing version information, the agent receives no help in choosing between them, resulting in minimal guidance.
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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