reorder_viewsSet the tab order of a dashboard's views. Pass every view id in the order you want them shown. This is also the order they rotate in on a wall display.
| Name | Required | Description | Default |
|---|---|---|---|
| viewIds | Yes | Every view id on this dashboard, in the order you want. | |
| dashboardId | Yes | Dashboard id. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as non-readonly and idempotent. The description adds that the order is also used for wall display rotation and that every view id must be passed, making the replacement semantics explicit. 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?
Two tightly written sentences; the primary action is front-loaded, and the wall-display detail provides useful extra context without bloat.
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 two-parameter operation with no output schema and no nested objects, the description provides the key details: what the order means, the requirement to pass all view ids, and the side effect on wall displays. Minor omission is error behavior, but not critical for this simple tool.
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 input schema has 100% coverage, with viewIds already described as 'Every view id on this dashboard, in the order you want.' The description essentially repeats this instruction without adding new parameter-level details, so baseline 3 is appropriate.
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 ('Set') and resource ('tab order of a dashboard's views'), and clarifies that the order also affects wall display rotation. This clearly distinguishes the tool from siblings like update_view or list_views.
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 clear context on when to use the tool (to set view tab order) and how to use it ('Pass every view id in the order you want them shown'). It doesn't explicitly name alternatives or exclusions, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target a distinct resource+action pair, and descriptions explicitly cross-reference related tools (e.g. update_dashboard points to set_dashboard_theme and publish_dashboard). A few pairs remain close enough to cause hesitation—set_widget_layout vs update_widget's position parameter, and get_started vs get_platform_overview—but their descriptions do separate them.
Tool names consistently follow verb_noun snake_case with clear resource nouns like customer, dashboard, widget, and data_source. Minor deviations exist between add_* and create_* for creation operations, and set_* versus update_* for mutations, but the overall pattern is still predictable.
With 42 tools, the surface is much larger than the 16-25 range that already feels heavy, and several onboarding/catalog helpers (get_started, get_platform_overview, list_plans_and_limits, list_supported_data_connectors, list_widget_types) add to the count. Each tool has a distinct job, but the set would benefit from consolidation or splitting into focused sub-servers.
Core lifecycle coverage is strong: dashboards, views, widgets, data sources, customers, and publishing all have create/read/update/delete where relevant, plus test/preview/validation tools. Obvious gaps are customer-user management beyond create/delete (no password reset/update) and no direct way to move a widget between views, but agents can work around these.