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TsvetanG2

cognigy-ai-mcp-management-server

create_snapshot

Create a snapshot of a Cognigy.AI project to capture its configuration for backup or deployment. Async operation with polling ensures the process completes.

Instructions

Creates a snapshot of a Cognigy.AI project. Snapshots capture the entire project configuration (flows, intents, endpoints, etc.) for backup or deployment. MUTATING: Set dryRun=false to create. Async operation - polls until complete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName for the snapshot (e.g., 'v1.0.0', 'pre-release-backup')
dryRunNoIf true (default), validates without creating. Set to false to actually create the snapshot.
projectIdYesThe project ID to create a snapshot of
timeoutMsNoMaximum time to wait for snapshot creation (5-600 seconds, default 120)
descriptionNoOptional description of what this snapshot contains or why it was created
pollIntervalMsNoHow often to check task status (1-10 seconds, default 3)
Behavior4/5

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

While annotations indicate readOnlyHint=false and destructiveHint=false, the description adds that it is mutating, async, and polls until complete. It also notes that dryRun defaults to true, which is useful behavioral context. No contradictions with annotations.

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, front-loaded with the primary purpose, and each sentence serves a distinct purpose: explaining what the tool does and highlighting key behavioral traits (async, dryRun). No wasted words.

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?

The description covers the core action, scope, mutation nature, and async behavior. Given no output schema, it could mention what the return object is (e.g., task ID), but the existing parameter details (like timeoutMs) partially compensate. Overall fairly 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% with detailed parameter descriptions. The description does not add significant meaning beyond the schema; it only reinforces that dryRun=false is needed to create. Baseline score of 3 is appropriate as the schema does the heavy lifting.

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 'Creates' and the resource 'snapshot of a Cognigy.AI project', and explains the snapshot captures entire project configuration for backup or deployment, making it unambiguously distinct from sibling tools like list_snapshots or delete_snapshot.

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 provides context for when to use this tool (backup or deployment) and mentions that to actually create, set dryRun=false. However, it does not explicitly exclude alternatives or specify when not to use it, though the context is clear.

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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