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Glama

Put a saved copy back

save_restore
Destructive

Restore a saved snapshot of world and character data. Creates an automatic backup of current state for undo, and rejects invalid labels or a running game.

Instructions

Overwrite the world and characters with a snapshot.

This DESTROYS what is on disk now, so it saves that first: the state being overwritten is copied to auto-before-restore and returned as undo, which save_restore accepts like any other label. A restore aimed at the wrong snapshot is therefore recoverable rather than final.

Refuses while the game is running, and refuses a label that does not exist by listing the ones that do.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeYes
undoYes
filesYes
labelYes
removedYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.3

TDQS

A4/5.0
Behavior5/5

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

The description adds substantial behavioral detail beyond the destructiveHint annotation: it explains that the current state is saved to 'auto-before-restore' and returned as 'undo', making an incorrect restore recoverable. It also discloses refusal conditions. This is rich, honest context that exceeds what annotations alone provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured: it starts with the core action, then explains the destructive behavior and the safety mechanism, then lists refusals. Each sentence adds value. It is slightly verbose but not wasteful.

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 tool has an output schema (which presumably documents return values), the description covers the key behavioral aspects: what happens on success (overwrite), the undo mechanism, and failure conditions. It does not explicitly describe the output format, but that is covered by the output schema. It is complete enough for an agent to call it 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?

The schema provides only a bare 'label' parameter with 0% description coverage. The description compensates by explaining that 'undo' is a valid label and that the tool lists existing labels when a given one is invalid. This gives the parameter contextual meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Overwrite the world and characters with a snapshot.' The title adds a synonym. It is clearly a restore operation, distinct from save_snapshot. However, it does not explicitly name sibling alternatives or differentiate them, so a 4 is appropriate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides some usage context: it refuses while the game is running, implying you should stop the game first, and it refuses non-existent labels, listing valid ones. But it does not explicitly state when to use this tool versus alternatives like save_snapshot or capture tools. No direct when-to-use/when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.