restorePulseDashboardVersionRestore a previous version of a Duvo Pulse dashboard, making it live again (requires edit access). Non-destructive — it moves the head pointer to the chosen version.
| Name | Required | Description | Default |
|---|---|---|---|
| artifactId | Yes | ||
| revisionId | Yes |
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?
Beyond the annotations, it explains the mechanism ('moves the head pointer') and explicitly reassures non-destructiveness, which is valuable for an operation that sounds like a rollback. It also discloses the edit-access requirement. It doesn't discuss side effects on the previously live version, but annotations already cover destructive/read-only hints.
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 sentences with no filler; the core action and key caveats are front-loaded before the mechanism detail. Every phrase earns its place.
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, the description covers the action, permission, and non-destructive semantics. It could add a pointer to listPulseDashboardVersions as the source of revisionId, but the current text is sufficient for correct invocation.
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 0%, and the description does not explicitly map artifactId to the dashboard or revisionId to the target version; it only refers generically to 'the chosen version.' Parameter names and UUID patterns appear in the schema, but the description adds almost no semantic value for an agent deciding what to pass.
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 ('Restore') and clearly identifies the resource ('previous version of a Duvo Pulse dashboard') and the intended effect ('making it live again'). The non-destructive head-pointer mechanism further distinguishes it from destructive or revision-promotion siblings.
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: use this when a previous dashboard version should become live, and it notes the edit-access prerequisite. It does not explicitly name alternatives or exclusions, but the dashboard/version scoping and head-pointer behavior separate it from promoteRevision and revertClarityProcessSnapshot.
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.
Despite detailed descriptions, many tool names are highly ambiguous, with multiple tools covering the same conceptual actions (e.g., acceptClarityCaptureSuggestion vs. acceptClarityTeamAssignmentSuggestion, or the many deleteClarity*Interview tools). The set is so large that distinguishing between, say, listClarityFolders, listClarityProcesses, and listClarityProcessSummaries requires reading deep into descriptions, reducing agent selection accuracy.
The naming convention is predominantly verb_noun (e.g., createClarityProcess, listAgents, deleteQueue), and is remarkably consistent across the 316 tools. There are only minor deviations, such as 'fileSuggestedClarityProcesses' (verb + adjective noun) and 'bulkUpdateCasePriority' (where 'bulk' could be seen as a prefix), but overall the pattern holds strongly.
With 316 tools, this server is extremely oversized for any single agent to manage effectively. The massive number of tools suggests poor modularization—many of these tools likely belong in separate, smaller servers focused on specific domains (e.g., Clarity, Pulse, Agent management). The cognitive load for an agent to choose from 316 options is very high, leading to frequent misselection.
The tool surface covers an extraordinarily wide range of operations across the Duvo platform: agents, runs, cases, queues, Clarity processes, skills, integrations, notifications, teams, and more. Most resource types have full CRUD and lifecycle management. Notable minor gaps exist (e.g., no tools for managing specific notification batch severities dynamically, and some interview management is missing batch operations), but for the platform's scope, coverage is impressively thorough.