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Replace Case Queue Eval Rubrics

replaceCaseQueueEvalRubrics
Destructive

Replace the entire case-level evaluation rubric set on a queue's current version (1 to 12 rubrics). Existing rubrics are removed and the supplied list becomes the new set. An empty list is refused — whole-case evaluation regenerates rubrics for an empty set at the next settlement, so a cleared set would not stay cleared; remove individual rubrics instead. Targets the queue's current version (build-set), which exists once its first Agent-processed case settles — this fails with 409 before then. Cases already judged keep their original verdicts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rubricsYesThe complete case-level rubric set for the queue's current version (at least 1 rubric). Replaces every existing rubric.
queue_idYesThe queue's unique identifier

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already indicate destructiveHint: true and readOnlyHint: false, but the description adds critical behavioral context beyond that: existing rubrics are destroyed, an empty list is refused due to regeneration semantics, the tool fails with 409 before the build-set exists, and already-judged cases retain original verdicts. 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, with the core purpose front-loaded in the first sentence, followed by three sentences that each add essential caveats (empty list refusal, build-set prerequisite, verdict preservation). No filler or redundant repetition of the schema; every sentence earns its place.

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 the operation's complexity (destructive, conditional on current version, empty-set nuance), the description covers the critical decisions and prerequisites. It does not specify the return value or success confirmation, but with no output schema and annotations covering safety, this is a minor gap. Could mention expected response but is otherwise complete for correct invocation.

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%, with both queue_id and rubrics fully described, including nested object fields and constraints (minItems 1, maxItems 12). The description adds no additional parameter-specific meaning beyond the schema; it reiterates that rubrics is the complete replacement set but does not enrich parameter understanding further. Baseline 3 is appropriate.

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 clearly states the verb 'Replace' and the resource 'entire case-level evaluation rubric set on a queue's current version', with explicit scope (1 to 12 rubrics) and behavior (existing rubrics are removed). It distinguishes itself from sibling tools like createCaseQueueEvalRubric (adds one) and updateCaseQueueEvalRubric (updates one) by emphasizing the wholesale replacement of the set.

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

Usage Guidelines5/5

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

Provides explicit when-not guidance: an empty list is refused and the explanation why, directing to 'remove individual rubrics instead' (implying deleteCaseQueueEvalRubric). Also specifies the prerequisite that the queue's current version must exist (after first Agent-processed case settles) and notes the 409 failure otherwise, helping the agent decide when to invoke this vs. alternatives.

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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