datalens_sparkclusters_getRetrieve settings, health, and status for a Spark cluster by its ID. Use this to inspect a single cluster's configuration and operational state.
One Spark cluster: its settings, health and status. Experimental API, not measured.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Spark cluster id. |
Changes observed during successful MCP inspections.
v0.122.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=true, so the safety profile is covered. The description adds a genuinely useful operational caveat ('Experimental API, not measured'), but says nothing about error behavior for an unknown id or any access requirements, so it adds only modest context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with no waste and the payload summary front-loaded. Slightly telegraphic phrasing ('One Spark cluster:') and the ambiguous 'not measured' keep it from being fully polished.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-resource read with rich annotations and no output schema, the description covers what concept is retrieved and its experimental status. It omits only error/not-found behavior, which is a minor gap at this complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single 'id' parameter, so the schema already carries the semantics and the description adds nothing about format, source, or how to obtain an id. Baseline 3 applies 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.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (get) and resource (one Spark cluster) and enumerates what the payload contains (settings, health, status). It implicitly distinguishes itself from datalens_sparkclusters_list by saying 'One Spark cluster', but never names the sibling or the id-based lookup condition explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied: the singular 'One Spark cluster' suggests fetching by known id rather than enumerating. There is no explicit when-to-use, no pointer to datalens_sparkclusters_list as the alternative, and no note on prerequisites such as needing an existing cluster id.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.