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TsvetanG2

cognigy-ai-mcp-management-server

get_snapshot_resources

Read-onlyIdempotent

Lists the resources (flows, locales, NLU connectors, LLMs) contained in a Cognigy.AI snapshot to inspect contents before restoring or compare versions.

Instructions

Lists resources (flows, locales, NLU connectors, LLMs) contained in a Cognigy.AI snapshot. Use this to inspect what a snapshot contains before restoring or to compare versions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of resources to return (1-100, default 25)
snapshotIdYesThe snapshot ID to list resources from
resourceTypeYesType of resources to list
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is clear. The description adds minimal behavioral detail beyond the listing action. It does not disclose any edge cases, error handling, or return format, but the annotations reduce the burden.

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 action and resource. Every sentence is informative with no redundancy. Highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema is provided, and the description does not indicate what fields the returned resources contain. While the purpose is clear, an agent would need to assume the standard resource fields. With rich annotations and full schema coverage, the completeness is acceptable but not exemplary.

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 the schema documents all parameters comprehensively. The description repeats the resource types but adds no extra semantic meaning beyond what the enum already provides. 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?

Clearly states the tool lists resources (flows, locales, NLU connectors, LLMs) inside a snapshot, distinguishing it from sibling tools like list_snapshots (which lists snapshots) and get_snapshot (which gets snapshot details).

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?

Explicitly says 'use this to inspect what a snapshot contains before restoring or to compare versions', giving clear when-to-use guidance. It does not explicitly mention when not to use, but the context is sufficient for an AI agent.

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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