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Duvo MCP

by io.github.duvoai

Replace Eval Rubrics

replaceEvalRubrics
Destructive

Replace a build's entire Agent-specific evaluation rubric set in one call (at most 5 rubrics). Existing custom rubrics are removed and the supplied list becomes the new set; pass an empty array to clear them. Defaults to the Agent's live build; pass build_id to target a specific revision.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentIdYesThe agent's unique identifier (Assignment ID)
rubricsYesThe complete custom rubric set for the build. Replaces every existing custom rubric; pass an empty array to clear them.
build_idNoReplace the custom rubrics on this build (revision). Defaults to the agent's live build when omitted.
selected_automation_revision_idNoThe automation revision this edit is being made at. Pass a draft and the edit is folded into that draft itself; pass the active revision and the edit lands on a draft branched from it. A historic revision is rejected — it cannot be activated from without an explicit rebase. A revision belonging to a different automation is ignored, and the edit targets the automation the addressed agent belongs to. Omit to target the automation's active revision.

TDQS

A4.5/5.0
Behavior5/5

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

The description explicitly discloses the destructive replacement semantics: 'Existing custom rubrics are removed and the supplied list becomes the new set; pass an empty array to clear them.' This goes well beyond the destructiveHint annotation by explaining exactly what happens to existing rubrics, making the tool's behavior transparent.

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?

Two sentences, front-loaded with the core purpose, and every clause delivers useful information: replacement semantics, max count, clearing behavior, and build target default. No wasted words.

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

Completeness5/5

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

The description is complete for a destructive mutation tool: it states what happens to existing rubrics, explains the clear option, names the default target build, and mentions the optional build_id. With full schema coverage and no output schema, this sufficiently equips an agent to invoke the tool correctly.

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 100%, so the baseline is 3. The description adds minimal semantic value beyond the schema: it mentions the 5-rubric cap and empty-array clearing, but the schema already documents these constraints and the build_id default. No significant additional meaning is provided.

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 uses a specific verb ('Replace') and clearly identifies the resource: 'a build's entire Agent-specific evaluation rubric set'. It distinguishes itself from sibling tools like createEvalRubric or updateEvalRubric by emphasizing 'entire set in one call' and the clearing behavior.

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?

It gives clear context for when to use this tool: when you need to replace the whole rubric set, clear all rubrics with an empty array, and target a specific build revision via build_id. It does not explicitly name alternative single-rubric tools, so it misses the explicit 'when-not' guidance needed for a 5.

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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