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TsvetanG2

cognigy-ai-mcp-management-server

clone_llm

Clone a Cognigy AI LLM configuration. The copy retains all settings and can be modified independently. Set dryRun=false to clone.

Instructions

Clones a Cognigy.AI large language model configuration. Creates a copy with the same settings that can be modified independently. MUTATING: Set dryRun=false to clone.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dryRunNoIf true (default), validates without cloning. Set to false to actually clone.
largeLanguageModelIdYesThe LLM ID to clone
Behavior3/5

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

Annotations already indicate mutation (readOnlyHint=false). Description adds dry-run behavior detail but lacks other side-effect info (e.g., permissions, where clone is created).

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?

Two sentences, no fluff, front-loaded with purpose. Every sentence earns its place.

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?

Adequate for a simple clone tool with two parameters and no output schema. Could mention what the clone returns (e.g., new ID). Still mostly complete.

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?

Schema coverage is 100%, so parameters are well-documented. Description adds minimal value beyond schema (reiterates dryRun usage). 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 clearly states the verb 'clones' and the resource 'large language model configuration', and distinguishes from sibling 'clone_flow' by resource type.

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?

Specifies that dryRun must be set to false to actually clone, providing clear usage guidance. Does not explicitly discuss when not to use but is adequate.

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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