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undo_list

List recorded, not-yet-applied undo tokens for AIops operations. Each entry includes the original and inverse tool names, a note, and an effect verification flag indicating if the change is confirmed or probable.

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
Behavior4/5

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

Discloses read-only nature, ordering, return structure, and detailed behavior of truncated detection and effectVerified field. No annotations provided, so description carries full burden. Could mention permissions or rate limits.

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 summary, return details, truncated explanation, effectVerified note, and Args. Every sentence adds value; no wasted words.

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?

Covers return structure, truncated detection, and effectVerified. Lacks explicit description of other undo entry fields (original tool, inverse tool, note), but overall complete for a list tool.

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?

Adds meaning beyond schema: limit default and cap, target marked as unused for CLI uniformity. Schema coverage is 0%, so description compensates well.

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?

Clearly states the tool lists not-yet-applied undo tokens, using specific verb 'list' and resource 'undo tokens'. Distinguishes from sibling tools like undo_apply.

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

Usage Guidelines5/5

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

Explicitly describes when to use: to see available undo tokens before applying with undo_apply. Provides guidance on handling truncated results and interpreting effectVerified field.

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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