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Build Clarity Automation

buildClarityAutomation

Hand a transformation proposal for a v2 clarity process off to the workflow-builder pipeline. Builds from transformation_proposal_id when supplied, otherwise from the process's live proposal. The proposal id is the durable idempotency key, so retries return the same run and a different proposal starts a new run. Returns 202 while the LLM run completes asynchronously, or 409 when the resolved proposal is still being written.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
process_idYesThe clarity process id
transformation_proposal_idNoTransformation-proposal snapshot to build the automation from. Defaults to the process's live proposal.

TDQS

B3.3/5.0
Behavior1/5

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

The description claims the transformation_proposal_id is a 'durable idempotency key' that makes retries return the same run, implying idempotent behavior. However, the annotation explicitly sets idempotentHint=false, creating a direct contradiction. According to the rubric, this contradiction warrants a score of 1. The description does add value by disclosing async behavior and conflict responses, but the contradiction overrides.

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 extremely concise: three sentences, each with a clear purpose. The first sentence states the main action, the second explains idempotency and retry behavior, and the third describes return codes. No redundant or unnecessary information is present.

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

Completeness3/5

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

The description explains the initiation of an async workflow (202) and a conflict state (409), but does not cover what happens after the async run completes or how to retrieve results. Given that there is no output schema, the description could be more complete by mentioning potential success responses or follow-up actions. It is adequate for the triggering step but leaves the lifecycle partially open.

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

Parameters4/5

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

While the input schema already provides 100% coverage with descriptions, the description adds significant behavioral semantics: it explains that transformation_proposal_id defaults to the process's live proposal and that it serves as an idempotency key. This extra context helps the agent understand the parameter's role beyond the schema's format and type constraints.

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 and resource: 'Hand a transformation proposal for a v2 clarity process off to the workflow-builder pipeline.' It specifies two modes of operation (with or without transformation_proposal_id) and distinguishes this tool from siblings by its unique action of initiating an automation build, which no other sibling tool explicitly does.

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

Usage Guidelines2/5

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

The description explains internal behavior (idempotency key, retry semantics, return codes) but does not provide any guidance on when to use this tool versus alternatives like proposeClarityLandscapeProcess or generateClarityProcessSnapshot. There is no explicit 'when to use' or 'when not to use' context, leaving the agent to infer usage from the tool name alone.

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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