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prompts_prompt_restore

Restore a past version of a prompt template by version_number. Creates a new version pointing at the restored content — history is preserved. Fans out to every agent using this template without a per-agent override; the response includes affected_agents as a receipt of the fan-out.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonNoOptional: why this restore is happening (shows up in history UI)
prompt_idYesID of the prompt template
in_workspaceNoRun this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected.
version_numberYesThe version_number to restore (get it from prompts.prompt_history)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / in_workspace
      Added value: +{
      +  "description": "Run this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected.",
      +  "type": "integer"
      +}
  2. Added
  3. Removed
  4. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations (which already say readOnlyHint=false, destructiveHint=false, idempotentHint=false), the description adds material behavioral context: history is preserved because restore creates a new version, and it fans out to every agent using the template without a per-agent override, returning affected_agents as a receipt. The fan-out side effect is exactly the kind of non-obvious behavior an agent must know before calling.

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 tightly packed sentences, front-loaded with the core action and parameter, then consequences, then the return receipt. No filler and no repetition of schema content.

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

Completeness5/5

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

With no output schema, the description compensates by describing the response's affected_agents field, and it covers the mutation's side effects and the history-preserving guarantee. An agent has everything it needs to call this 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 description coverage is 100%, so all four parameters are already documented, and the schema even explains that version_number comes from prompts.prompt_history. The description restates version_number's meaning but adds nothing for reason or in_workspace, so baseline 3 applies.

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 states a specific verb (restore), resource (a past version of a prompt template), and the driving parameter (version_number). It also discloses the resulting state (a new version pointing at restored content) which distinguishes it from a generic update tool.

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?

It points the agent at prompts_prompt_history as the source of version_number, establishing the correct workflow. It gives clear context for when to use it but names no explicit alternative or 'when-not' condition (e.g., use prompts_update to make a fresh edit instead of restoring).

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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