deleteClarityProcessLinkDelete a process-to-process link from the organization's Clarity landscape when the caller can manage both endpoint teams.
| Name | Required | Description | Default |
|---|---|---|---|
| orgId | Yes | ||
| process_link_id | Yes | Unique process-link identifier |
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 destructiveHint=true and idempotentHint=true. The description adds useful context beyond those annotations by specifying the exact object affected (process-to-process link) and the authorization requirement (manage both endpoint teams). No side effects beyond deletion are disclosed, but the annotation set covers the core safety profile.
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?
One sentence with no filler; the action, object, scope, and precondition are all front-loaded. Every phrase earns its place.
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 simple two-parameter delete tool with annotations covering destructive/idempotent behavior, this is nearly complete: purpose, scope, and authorization are covered. The only minor gap is that it does not describe behavior when the link is missing or permissions are insufficient, which is not essential for selecting and invoking the tool.
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?
The description does not explicitly document orgId or process_link_id, but the schema already explains process_link_id and both parameter names are self-explanatory UUID identifiers. The mention of 'organization' and 'endpoint teams' provides light domain context for the two parameters, though it does not fully compensate for the missing orgId description in the schema.
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 uses a specific verb ('Delete') and object ('process-to-process link') with a clear scope ('organization's Clarity landscape'), which immediately distinguishes it from sibling tools like deleteClarityProcess, createClarityProcessLink, and updateClarityProcessLink. There is no ambiguity about what resource this tool acts on.
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?
It gives a clear precondition ('when the caller can manage both endpoint teams') and the resource type, so an agent knows when this tool is applicable. It does not explicitly name alternatives or when-not-to-use conditions, but for a delete operation the use case is self-evident among the sibling tool list.
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.