Duvo MCP

List Runs

listRuns

Read-onlyIdempotent

List runs for the current team. Supports filtering by agent, user, queue, status, etc. Messages, evaluation data, and queue metadata are included where available. Set count_only=true to skip Run row selection and enrichment. The normal response shape is returned with data: [] and the matching total.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Number of runs per page (1-100, default 20)
`since`	No	Return runs completed at or after this ISO-8601 timestamp. Runs that have not completed are excluded.
`until`	No	Return runs completed before this ISO-8601 timestamp. The upper bound is exclusive. Runs that have not completed are excluded.
`offset`	No	Number of runs to skip
`search`	No	Full-text search across run titles and case titles
`source`	No	Filter to runs created from this source (e.g. api, schedule)
`status`	No	Filter to runs with this status
`sort_by`	No	Field to sort by (default created_at)	created_at
`team_id`	No	Duvo team UUID to operate on. API keys are pinned to a single team — omit this (it falls back to the key's team) or pass that same team; a different team is rejected. OAuth callers, who can span multiple teams, should pass the target team here.
`user_id`	No	Filter to runs owned by this user; non-superadmin callers are scoped to themselves regardless of this value
`agent_id`	No	Filter to runs for this agent
`digest_id`	No
`count_only`	No	Skip row selection and enrichment. The normal list response shape is returned with an empty row array and the matching total.	false
`has_issues`	No	If true, only return runs that have evaluation issues
`sort_order`	No	Sort direction (default desc)	desc
`automation_id`	No	Filter to runs whose agent belongs to this automation
`case_queue_id`	No	Filter to runs associated with this queue
`issue_severity`	No	If set, only return runs whose latest successful evaluation has at least one failing rubric with this severity (critical \| medium \| low). Implies has_issues; legacy evaluations without severity companion fields do not match this filter.

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent, and the description adds meaningful behavioral context: inclusion of messages, evaluation data, and queue metadata, and the count_only=true behavior that skips row selection/enrichment while returning the normal shape with data: []. This goes beyond the annotations without contradicting them.

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, front-loaded with the core action, and each sentence adds distinct information (scope+filtering, included data, count_only behavior). No redundancy.

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?

Given 18 parameters, no output schema, and rich annotations, the description covers the main behavioral surface: team scope, filter dimensions, included metadata, count_only shortcut, and response shape. It could mention pagination/offset but the schema handles that, so the description is adequately complete.

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

Parameters3/5

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

Schema description coverage is 94%, so the schema already documents the 18 parameters. The description adds no new parameter information beyond restating the count_only behavior, which the schema also covers. Baseline 3 is appropriate.

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

Purpose4/5

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

Description clearly states 'List runs for the current team' with a specific verb and resource, and enumerates filtering dimensions (agent, user, queue, status). It is distinct from siblings like listCaseRuns, though it does not explicitly call out the boundary (all team runs vs case-scoped runs), so it lacks explicit sibling differentiation.

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

Usage Guidelines3/5

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

No explicit when/when-not guidance or alternative tool names are provided. The description implies usage for team-wide run listing with filters, but does not mention cases where listCaseRuns or getRun would be more appropriate.

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

B3.1/5.0

Disambiguation2/5

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.

Naming Consistency4/5

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.

Tool Count1/5

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.

Completeness4/5

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.

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