shardgroup_listList shard groups, the erasure-coding sets of shards that back V2 data engine sharded volumes, to inspect their configuration and status.
List shard groups (erasure-coding sets of shards) backing V2 data engine sharded volumes (experimental feature). Longhorn docs: https://longhorn.io/docs/1.12.1/advanced-resources/v2-data-engine/sharding/
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.6Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It adds useful context beyond the title by flagging the feature as experimental and explaining what shard groups are, and the 'List' verb implies a read-only enumeration. It does not mention return format, pagination, or ordering, but for a zero-parameter read-only list tool the risk surface is small.
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?
A single front-loaded sentence states the operation first, then adds the defining parenthetical, the experimental caveat, and a documentation link. Every clause earns its place and there is no redundant filler.
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 zero-parameter list tool with no output schema, the description covers the resource identity, the domain context (V2 data engine sharding), the experimental status, and provides a docs link for deeper reference. The only gap is lack of detail on the return shape or volume of results, which is minor for a simple enumeration.
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?
The tool has zero parameters, so the baseline is 4 and there is no parameter semantics to document. The description still adds value by specifying exactly what entity is being enumerated, which is all an agent needs to call this tool correctly.
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?
The description uses a specific verb-resource pair ('List shard groups') and expands it with a precise definition ('erasure-coding sets of shards') and scope ('backing V2 data engine sharded volumes'). This clearly distinguishes it from siblings like shard_list (lists shards, a different granularity) and shardgroup_get (fetches one group, not a list).
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 context is implied by the 'List' verb and the sibling naming pattern ('shardgroup_get' vs 'shardgroup_list', 'shard_list' vs 'shardgroup_list'), so an agent can infer this is for enumerating shard groups rather than fetching one or listing shards. However, there is no explicit when-to-use statement or contrast with alternatives, leaving selection to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.