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memoryguard_rule_undo

Revert a V2 rule lifecycle mutation using its undo_id to restore the pre-rule state. Requires trusted actor or admin capability.

Instructions

Undo a V2 rule lifecycle mutation (including feedback/evidence compensation) using its persisted pre-rule undo_id. Requires the trusted actor or admin capability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
undo_idNo
workspaceNo
decision_idNooptional decision id alias; resolved to its undo_id
idempotency_keyNostable retry key for the compensating V2 mutation

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.7.8

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden, and it does a reasonably good job: it discloses that this is a compensating mutation, includes feedback/evidence compensation, and states the required permission level. It could be more explicit about irreversibility or failure behavior, but the core behavioral traits are present.

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 with no wasted words. The primary action and scope are front-loaded, and the auth prerequisite is stated efficiently.

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?

Given a mutation tool with no annotations and no output schema, the description is adequate but incomplete for invocation: it doesn't explain whether undo_id is mandatory, how decision_id relates to it, what workspace is used for, or what the response/result will be. An agent could still call it, but a few important constraints are left implicit.

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 descriptions already cover decision_id and idempotency_key, while undo_id and workspace are undocumented. The description adds meaning to undo_id ('persisted pre-rule undo_id'), but it does not clarify the workspace parameter or the relationship/requirement between undo_id and decision_id, which is a meaningful gap.

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 uses a specific verb and resource: 'Undo a V2 rule lifecycle mutation' and further scopes it with 'including feedback/evidence compensation'. It clearly distinguishes this undo tool from sibling rule-management tools like create, feedback, and merge.

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 clearly implies when to use the tool: when a V2 rule lifecycle mutation needs to be undone, using the persisted pre-rule undo_id. It also adds an important precondition: requires trusted actor or admin capability. It does not explicitly discuss exclusions or compare with alternatives, but no other undo sibling exists.

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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