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helm_upgrade

Deploy or upgrade a Helm chart release on a Kubernetes cluster. For standard Helm deployments only; AI models use deploy_model.

Instructions

Run helm upgrade --install for a chart on a cluster.

Use this for Helm chart deployments. For deploying standard AI models, use deploy_model instead.

Write operation — recorded in the audit log.

Args: cluster_name: Target cluster. release_name: Helm release name (created if it does not exist). chart: Helm chart reference (e.g. bitnami/nginx or ./charts/myapp). namespace: Kubernetes namespace (default: 'default'). values: Helm values to override (dict, optional). gateway_id: Gateway UUID from list_clusters. Omit for single-gateway deployments; provide to disambiguate when multiple gateways share a cluster name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chartYes
valuesNo
namespaceNodefault
gateway_idNo
cluster_nameYes
release_nameYes
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses it is a write operation recorded in audit logs, and for 'release_name' it notes it is created if not existing, implying idempotency. However, it does not describe other behavioral aspects such as whether the operation is reversible, if it triggers a rollout, or if it requires any specific permissions. The description provides functional details but lacks deeper behavioral context.

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

Conciseness4/5

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

The description is concise: a one-sentence purpose, one-sentence alternative, one-sentence behavioral note, then a structured argument list. It front-loads key information and avoids redundancy. However, the argument list could be slightly more compact, and some definitions are a bit verbose (e.g., gateway_id explanation). Overall, it is well-structured and efficient.

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

Completeness2/5

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

The tool has 6 parameters, no output schema, and is a Helm upgrade operation. The description explains inputs well but fails to describe the output or return value. Since no output schema exists, the agent needs to know what to expect (e.g., release status, success message). The description also omits potential side effects beyond audit logging (e.g., rollback behavior). This gap in completeness is significant for a complex operation.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It provides clear, meaningful definitions for all 6 parameters, including examples for 'chart' (e.g., bitnami/nginx), default for 'namespace', and usage guidance for 'gateway_id' (when to omit/provide). This adds significant value beyond the schema titles. Missing type specification for 'values' (though implied) and no format for 'cluster_name' keeps it from a 5.

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

Purpose5/5

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

The description clearly states the tool runs 'helm upgrade --install for a chart on a cluster.' It specifies the verb (run helm upgrade --install) and resource (chart on a cluster). It also distinguishes from sibling 'deploy_model' by noting that for deploying standard AI models, that tool should be used instead. This makes the purpose specific and distinct.

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

Usage Guidelines4/5

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

The description explicitly says 'Use this for Helm chart deployments' and provides an alternative: 'For deploying standard AI models, use deploy_model instead.' It also notes it's a write operation recorded in the audit log, which guides usage context. However, it does not mention exclusions like when not to use it beyond the AI model case, or prerequisites like needing cluster access, which would elevate to a 5.

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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