listCaseRunsList Runs (agent runs) that have claimed or received handover of a case, newest first. Capped at 50 ownership events.
| Name | Required | Description | Default |
|---|---|---|---|
| case_id | Yes | The case's unique identifier |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds behavioral details beyond annotations: ordering 'newest first' and a limit 'Capped at 50 ownership events,' which are important for an agent to know. It doesn't mention pagination or return format, but the added cap and ordering justify a score above baseline.
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?
The description is two sentences, with the core action front-loaded. The parenthetical 'agent runs' clarifies the resource, and the second sentence states the cap directly. There is zero filler or repetition of what the schema already provides.
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 read-only list operation with one parameter and no output schema, the description covers the selection criteria (claimed or received handover), ordering, and limit. It leaves the definition of 'ownership events' slightly open, but for a straightforward list tool this is adequately complete, especially with strong annotations.
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 schema provides 100% coverage for the single parameter case_id, including a clear description ('The case's unique identifier'). The tool description does not add any additional parameter-level meaning, so the schema carries the full burden, matching the baseline of 3.
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 the verb 'List' and clearly identifies the resource as 'Runs (agent runs)' with a specific qualifying condition: 'that have claimed or received handover of a case.' It also specifies ordering ('newest first') and a cap ('Capped at 50 ownership events'), which distinguishes it from broader sibling tools like listRuns or getRun.
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 implies a use case—when you need runs related to a case via ownership events—but it does not explicitly compare itself to alternatives like listRuns or mention when not to use this tool. The context is clear but not explicit about exclusions.
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.