Duvo MCP

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

Name	Required	Description
`path`	Yes	Relative path to the file inside the revision, e.g. SKILL.md.
`content`	Yes	New UTF-8 text content for the file.
`skill_revision_id`	Yes	Skill revision ID.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedAug 17, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Beyond the annotations (write, destructive, idempotent), the description adds valuable behavioral context: the draft-versus-active distinction, the impact on the running skill, and the read-only constraint on historic revisions. This meaningfully explains side effects the annotations alone do not convey.

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, each carrying essential information. The main action is front-loaded, followed by the critical revision-state semantics and the read-only caveat. No filler or redundant restating of the schema.

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 fully covers the most important contextual complexity of this tool: how revisions behave differently depending on draft/active/historic state. With no output schema, return values need not be described, and the 100% parameter coverage handles the remaining specifics.

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?

Schema coverage is 100%, so the parameters are already documented. The description adds extra semantic value by implying that skill_revision_id must refer to a draft or active revision (not historic), and by framing path and content as file contents within a revision.

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 states a specific verb and resource: 'Write a text file into a skill revision.' It clearly distinguishes this file-level operation from sibling tools like updateSkillFile and updateSkillRevision by targeting files within a revision and explaining draft/active/historic 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?

The description gives clear context for when to use the tool: writing to a draft leaves the active revision untouched, while writing to the active revision changes behavior immediately. It also tells users that historic revisions are read-only and advises creating a draft to edit them, but it does not name the specific alternative tool to use.

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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