updateSkillRevisionRename a skill revision or change its description. Works for drafts, the active revision, and historic revisions.
| Name | Required | Description | Default |
|---|---|---|---|
| revision_name | No | Optional user-defined name for this revision. Pass null to clear. | |
| skill_revision_id | Yes | Skill revision ID. | |
| revision_description | No | Optional user-defined description for this revision. Pass null to clear. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey this is a mutating but non-destructive operation (readOnlyHint=false, destructiveHint=false). The description adds one genuinely useful behavioral fact — that even historic revisions are editable, which is atypical. However, it does not disclose potential side effects of editing the active revision (e.g., impact on running skills/agents) or whether partial updates patch versus overwrite.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with zero filler. The core action is front-loaded in the first sentence, and the second sentence adds lifecycle scope that earns its place. This is an appropriately sized definition for a simple three-parameter tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity tool with full schema coverage and no output schema, the description covers what it does and across which revision states it works. The remaining gaps — routing to the generic updateRevision sibling and clarifying side effects on the active revision — are relatively minor given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters including the 'Pass null to clear' semantics for both optional fields. The description's mention of renaming and changing description merely mirrors the schema without adding new parameter-level meaning, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb+resource (rename/change a skill revision) and the exact fields mutated (name, description), which clearly separates it from createSkillRevision, deleteSkillRevision, and promoteSkillRevision. However, it does not explicitly distinguish itself from the generic updateRevision sibling, which could overlap with this tool's scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The 'Works for drafts, the active revision, and historic revisions' clause gives useful applicability context, implying the agent can use this tool on any revision lifecycle state. But it names no alternatives and gives no when-not-to-use guidance, especially against the similarly named updateRevision and updateSkillRevisionFile siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.