get_platform_overviewExplain what CustomerDashboard.io is, how multi-customer dashboards work, and how workspaces, dashboards, views, widgets and customers fit together. Call this first when you are unfamiliar with the product. No sign-in required.
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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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds genuine value beyond that: 'No sign-in required' discloses an authentication trait the annotations do not convey, and the verb 'Explain' signals that the return value is conceptual prose rather than structured records. 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?
Three short sentences, each earning its place: purpose, when-to-call, and auth requirement. The purpose is front-loaded before the usage guidance, and no filler or redundant restatement of the title exists. This is tight, efficient writing.
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, no-output-schema informational tool, the description covers everything needed to invoke it correctly: what it returns conceptually, when to call it, that it requires no authentication, and that it is non-destructive per annotations. The only slight gap is that the exact output format (e.g., markdown text vs. plain string) is unspecified, but the explanatory verb sets adequate expectations.
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 and the schema is an empty object, so there is nothing for the description to clarify. Per the 0-param baseline of 4, the description appropriately spends no space on parameter details, and the tool's scope is already clear from the purpose sentence.
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 ('Explain') tied to a clear resource: what CustomerDashboard.io is and how its core entities fit together. It is immediately distinguishable from all 40+ siblings, which are CRUD/action tools on specific resources like customers, dashboards, and widgets. The 'Call this first when unfamiliar' phrasing further cements its unique role as the platform-overview tool.
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?
The description gives explicit when-to-use guidance: 'Call this first when you are unfamiliar with the product.' It implies the inverse condition (skip when familiar) and the tool's conceptual role naturally excludes it from data-mutation tasks that siblings handle. It does not name specific alternative tools, but given there is no true sibling overlap, this is a minor gap.
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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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.