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TsvetanG2

cognigy-ai-mcp-management-server

get_nodes

Read-onlyIdempotent

Retrieve list of nodes in a Cognigy.AI flow to explore conversation logic structure before reading or modifying specific nodes.

Instructions

Lists all nodes in a Cognigy.AI flow. Nodes are the building blocks of conversation logic (Say, Question, If, Code, etc.). Use this to explore flow structure before reading specific nodes or modifying the flow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of nodes to return (1-100, default 25)
flowIdYesThe flow ID to list nodes from
Behavior3/5

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint, so the description adds limited behavioral context. It confirms read-only listing behavior and provides examples of node types, but does not detail pagination or response shape. This is adequate but does not significantly surpass what annotations offer.

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?

The description is two sentences, front-loading the core action in the first sentence and adding context in the second. No unnecessary words or repetition, making it efficient and easy to parse.

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?

Given the simple operation and rich annotations, the description covers the tool's purpose and usage adequately. It lacks return value details, but the absence of an output schema reduces the need. The openWorldHint supports flexibility. Overall, it provides sufficient context for an AI agent to use correctly.

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 covers both parameters with descriptions (flowId and limit), and the description does not add new semantic details beyond naming 'nodes' and 'flow.' The mention of 'all nodes' slightly misaligns with the default limit of 25, but no explicit parameter explanation is provided. With 100% schema coverage, a score of 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 'Lists all nodes in a Cognigy.AI flow,' specifying the verb (list) and resource (nodes). It also distinguishes from siblings like get_node and search_nodes by describing the output as all nodes and mentioning node types. The use case of exploring flow structure before modification further clarifies its purpose.

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 advises using this tool 'to explore flow structure before reading specific nodes or modifying the flow,' which gives a clear context for use. It implicitly suggests avoiding this tool when a single node is needed (use get_node) or when searching is required (use search_nodes), though it does not explicitly name these alternatives.

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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