datastore_investigation_bundle

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

Annotations already mark it read-only, but the description adds substantial behavioral detail: batched reads, correlated bundle vs list envelope, point-in-time snapshot semantics, output presentation guidance, and the caveat that per-datastore latency is omitted. No contradiction with 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?

Every sentence earns its place: purpose, output components, available alternatives, exclusions, and trigger context are each covered once. The [READ] tag and front-loaded purpose make the definition scannable despite its length.

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 complex bundle tool with no output schema, the description fully carries the return semantics, including what is and is not included. It also positions the tool within the workflow relative to cluster_health_summary and remediation tools, so an agent has enough context to call it correctly.

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%, so the schema already documents datastore_name, hours, and target fully. The description reinforces the exact-name requirement and suggests where to source the name, but adds little new parameter-level meaning beyond the schema.

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 opens with a concrete question and states it is a 'one correlated drill-down' for a datastore, listing exactly what the bundle contains (capacity, free space, hosts, VM rollup, alarms, event timeline). It differentiates itself from the individual list/get tools by explicitly naming the stitching alternative, and from sibling investigation bundles by the resource type.

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?

It gives a direct when-to-use instruction ('Reach for it after cluster_health_summary flags storage pressure') and names the alternative manual composition it replaces. Exclusions are explicit: no trending, no remediation, and per-datastore latency is not included, with remediation routed to vmware-aiops.

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