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

Annotations only declare write/non-idempotent/non-destructive, but the description adds real semantic behavior: queries are deep-copied so the copy is independent of the original, the action happens immediately when invoked, and a user-facing reason is required for the approval card. The minimum-query precondition is likewise behavior an agent could not get from the schema.

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?

Four short sentences, front-loaded with the action and scope, then non-obvious constraints. No filler or restatement of the tool name.

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 mutating tool with no output schema, it covers side effects, independence of the copy, and preconditions well. The one remaining gap is that it never says what comes back (presumably the new dashboard's id), which an agent would want in order to chain further calls.

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 coverage is 100%, so name, reason, projectId, dashboardId and environment are already fully documented. The description only reinforces that the new name is chosen here and that reason is user-facing, which duplicates rather than extends 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 opening sentence gives a specific verb (copy) and resource (a dashboard) with an explicit new name, and the follow-up clarifies that all queries are copied too, which separates it from create_dashboard. It stops short of naming any sibling tool outright, so the routing signal is inferential rather than explicit.

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 supplies a hard precondition ('must have at least one query') and a workflow prerequisite (load the manage-dashboards skill first), which are the main things that could make a call fail. It does not say when to prefer create_dashboard or update_dashboard over duplication, so alternative selection is left to inference.

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