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flaviagaia

rancher-mcp-server

by flaviagaia

get_pod_logs

Retrieve the last N log lines from a pod, with support for reading logs from a previous crashed container instance.

Instructions

Fetch the last N log lines of a pod. Use previous=True to read logs from the previous (crashed) container instance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pod_nameYes
previousNo
containerNo
namespaceYes
cluster_idYes
tail_linesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It only mentions the ability to fetch logs from a previous container, but does not state whether the operation is read-only, requires specific permissions, or has rate limits. These gaps leave the agent with 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 two short sentences with no redundant words. It efficiently conveys the core function and a key parameter detail, demonstrating excellent 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 tool has 6 parameters (3 required) and no parameter explanations, the description is too brief. It does not explain how to obtain or specify the required parameters (e.g., cluster_id, namespace, pod_name), nor does it mention the existence of an output schema. The minimal context leaves significant gaps for proper usage.

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

Parameters2/5

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

The schema description coverage is 0%, so the description must compensate. It only hints at 'tail_lines' (via 'last N') and 'previous', but provides no explanation for the other four parameters (pod_name, container, namespace, cluster_id), leaving their semantics unclear beyond the schema names.

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

Purpose5/5

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

The description clearly states the action ('Fetch') and the resource ('last N log lines of a pod'), making the tool's purpose immediately evident. It also naturally distinguishes from sibling tools like get_events or diagnose_workload, which deal with other Kubernetes data.

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

Usage Guidelines3/5

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

The description provides a specific usage hint for the 'previous' parameter, but lacks guidance on when to choose this tool over alternatives (e.g., get_events for events or diagnose_workload for performance issues). There is no mention of prerequisites or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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