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AxonityAI

Axonity Flow MCP Server

Official
by AxonityAI

restore_prompt_snippet_version

Roll back a prompt snippet's draft to a previous version using the version UUID. The current draft is snapshotted first, so the operation can be undone.

Instructions

Roll a prompt_snippet's DRAFT back to an earlier version. Takes the versionId (a UUID from list_prompt_snippet_versions), NOT the checkpoint number. The current draft is snapshotted first, so this is itself undoable. It changes only the draft — what is live stays live until a human approves a new publish.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe prompt_snippet's id.
versionIdYesThe version row's UUID.
expectedVersionYesThe draft version you last read — 409 if stale.
Behavior5/5

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

With no annotations provided, the description fully carries the burden. It discloses that the current draft is snapshotted first (making the operation undoable) and that only the draft is changed, not the live version, which requires human approval. This provides critical behavioral context.

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?

Three sentences, each adding essential information. No extraneous words. The main action is front-loaded, and the description efficiently covers purpose, parameter nuance, and behavioral impact.

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, parameter nuance, and behavioral aspects (undoability, draft vs live). It does not describe return values, but since it is a mutation tool and no output schema exists, the omission is acceptable. The context is sufficient for an agent to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds value by clarifying that versionId is a UUID from list_prompt_snippet_versions, not a checkpoint number, aiding parameter understanding beyond the schema.

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 it rolls back a prompt_snippet's DRAFT to an earlier version. It specifies the action, resource, and distinguishes the parameter versionId from a checkpoint number, aligning with the verb+resource clarity standard.

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 explains when to use the tool (to restore a draft to an earlier version) and implicitly differentiates it from other restore tools (e.g., restore_prompt_snippet). However, it could explicitly state when not to use it or mention alternatives for live version handling.

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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