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endpoint-aiops-mcp

undo_list

List pending undo tokens (most recent first) with each undo ID, original tool, inverse tool, and verification status so you can pick a token and apply its reversal.

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.

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 (1..500, default 50). target: Unused (undo state is host-local); accepted for CLI uniformity.

Returns dict: {undos[], returned, limit, truncated}. One extra row is fetched, so 'truncated' is measured rather than guessed from the returned count happening to equal the limit; re-run with a higher limit when true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
targetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden and does so thoroughly. It states this is a read operation, explains the meaning of effectVerified, warns that a false value means the reversed change is only probable, and even cautions against misreporting restore results. It also documents the extra-row fetch behavior that makes 'truncated' reliable.

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?

The description is front-loaded with the core purpose and flows logically into entry fields, safety caveats, parameters, and return values. Every sentence earns its place, and the Args/Returns structure makes it easy to scan. No filler or redundancy.

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?

There is no output schema, so the description appropriately documents the return dict shape, the meaning of truncated, and how to handle truncation. It covers the caveat about effectVerified, the parameter semantics, and the apply workflow. For a two-optional-parameter list tool, this is comprehensive.

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?

Schema description coverage is 0%, so the description must fully explain parameters. It does: limit is given a range (1..500) and default (50), and target is explicitly documented as unused but accepted for CLI uniformity. This adds meaningful semantics that the bare schema completely lacks.

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 opens with a specific verb and resource: 'List recorded, not-yet-applied undo tokens (most recent first).' It clearly distinguishes this listing tool from the apply tool (undo_apply) by explaining entries are for later application via undoId. The scope and behavior are unambiguous.

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?

The description implies when to use the tool: when you need to inspect pending undo tokens before applying them. It explicitly tells the agent to use the returned undoId with undo_apply, connecting the tool to its sibling workflow. It does not fully enumerate exclusions or alternatives, but the workflow context is strong.

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