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Duvo MCP

by io.github.duvoai

Update Skill Revision File

updateSkillRevisionFile
DestructiveIdempotent

Write a text file into a skill revision. Writing into a draft leaves the active revision untouched until the draft is promoted; writing into the active revision changes what the skill runs immediately. Historic revisions are read-only: create a draft from one to edit it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesRelative path to the file inside the revision, e.g. SKILL.md.
contentYesNew UTF-8 text content for the file.
skill_revision_idYesSkill revision ID.

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=true, idempotentHint=true), the description details the concrete behavioral consequences: draft writes are deferred until promotion, active writes change runtime immediately, and historic revisions cannot be written. This adds valuable context without contradicting the 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?

Three concise sentences deliver the purpose, the behavioral nuance, and the historic-revision constraint. Every sentence earns its place with zero redundancy or fluff.

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?

The description fully conveys the revision-state model and the read-only constraint for historic revisions. No output schema exists, so return-value details aren't required. It could explicitly mention overwrite/upsert behavior, but the idempotentHint annotation partially covers that expectation.

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?

The input schema covers 100% of parameters with clear descriptions for path, content, and skill_revision_id. The description itself adds no parameter-specific details, but the schema already fully documents the semantics, so the 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 opens with a specific verb+resource action: 'Write a text file into a skill revision.' It then distinguishes draft, active, and historic revisions, which clearly separates it from generic file-update tools like updateSkillFile and other revision-related siblings.

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?

The description provides clear situational guidance: writing into a draft is safe until promotion, writing into active affects execution immediately, and historic revisions are read-only (implying a draft must be created first). It doesn't explicitly name alternative tools, but the context is sufficiently directive.

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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