Skip to main content
Glama

undo_list

List recorded undo tokens for governance actions. Returns entries with original tool, inverse tool, and note to review before applying.

Instructions

[READ] List recorded, not-yet-applied undo tokens (most recent first).

Each entry names the original tool, the inverse tool that undo_apply would run, and a human note. Use the undoId with undo_apply.

Returns {"undos": [...], "returned": N, "limit": L, "truncated": bool}. truncated is measured (one extra row is fetched), not guessed from a length coincidence: when it is true there are MORE tokens than shown, so re-run with a higher limit rather than reporting the list as complete.

Each entry carries effectVerified. False means the original write lost its response, so the change it reverses is PROBABLE, not confirmed — check the live state before applying, and do not report the result as a restore of a state that may never have been reached.

Args: limit: Max rows to return (default 50, capped at 500). target: Unused (undo state is host-local); accepted for CLI uniformity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
targetNo
Behavior5/5

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

Discloses the read-only nature via [READ] tag, explains the truncated measurement method (fetching one extra row), details effectVerified semantics and implications, and notes that target is unused. Comprehensive coverage beyond minimal requirements.

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?

Well-structured with clear sections: purpose, output format, behavioral notes, and parameter details. Every sentence adds value without redundancy. Front-loaded with the main purpose and key usage hint.

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?

Given no output schema, the description fully defines the return structure and edge cases (truncated, effectVerified). References sibling tool undo_apply and provides actionable guidance. No gaps identified.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates: explains limit default of 50 and cap of 500, and clarifies that target is unused but accepted for CLI uniformity. No ambiguity remains.

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 lists recorded, not-yet-applied undo tokens in reverse chronological order. It distinguishes itself from sibling tools like undo_apply by specifying it is a read operation for inspecting available undo actions.

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 mentions using the undoId with undo_apply, advises re-running with higher limit when truncated, and cautions about effectVerified. Lacks explicit when-not-to-use guidance, but provides sufficient context for correct usage.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AIops-tools/AI-Guardian'

If you have feedback or need assistance with the MCP directory API, please join our Discord server