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Glama

CustomerDashboard

Create a dashboard

create_dashboard

Create a dashboard. Use type 'customer' for a multi-customer dashboard where each of your customers signs in and sees only their own rows, or 'internal' for a normal dashboard you view yourself or publish as one shared view. A 'Default' view is created automatically. Subject to your plan's dashboard limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesDashboard name.
typeNo'customer' for a per-customer, login-gated dashboard; 'internal' for a single shared dashboard. Defaults to 'internal'. This cannot be changed later.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Beyond the annotations, the description discloses two important behaviors: a Default view is created automatically, and creation is subject to the plan's dashboard limit. These are real behavioral details not visible in the schema or annotations. The description is consistent with readOnlyHint=false and destructiveHint=false.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each earning its place: the first states the core action, the second explains the crucial type distinction, and the third discloses side effects and constraints. No filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple create tool with two parameters, the description is largely complete: it explains purpose, parameter choice, automatic view creation, and a limit that may prevent success. It does not describe the response shape, but given the low complexity and no output schema, this is a minor gap rather than a blocking one.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already covers both parameters at 100%, so the baseline is 3. The description adds meaningful value by explaining what the 'customer' type actually does at runtime — each customer signs in and sees only their own rows — and by noting the plan limit, which affects whether the operation may fail. This goes beyond the schema's shorter enum descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a dashboard and immediately distinguishes the two dashboard types with concrete behavioral consequences: 'customer' gives each customer login-gated access to only their own rows, while 'internal' is a single shared view. This goes beyond the bare title and gives an agent enough to know what operation is being performed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to choose 'customer' versus 'internal', which is the main usage decision for this tool. It does not explicitly name alternative tools like create_view or update_dashboard, but the context is clear enough for an agent to select and configure this tool appropriately.

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

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TDQS

A3.9/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count2/5

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.

Completeness4/5

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.

Resources