Google Compute Engine

list_reservations

Read-onlyIdempotent

Lists Compute Engine reservations. Details for each reservation include name, ID, creation timestamp, zone, status, specific reservation required, commitment, and linked commitments. Requires project and zone as input.

Input Schema

TableJSON Schema

Name	Required	Description
`zone`	Yes	Required. The zone of the reservations.
`project`	Yes	Required. Project ID for this request.
`pageSize`	No	Optional. The maximum number of reservations to return.
`pageToken`	No	Optional. A page token received from a previous call to list reservations.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`reservations`	No	The list of reservations.
`nextPageToken`	No	A token that can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.

TDQS

A3.5/5.0

Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, covering the safety profile. The description adds the required inputs and the fields returned, but does not disclose additional behavioral traits like pagination, rate limits, or permissions. It does not contradict annotations.

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 brief and front-loaded with the main action. The final sentence about requiring project and zone is redundant with the schema, but the overall structure is clean and efficient.

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?

For a read-only list operation with a rich output schema, the description adequately explains what the tool does and the scope. It could better distinguish itself from sibling tools like get_reservation_details, but the core functionality is sufficiently covered.

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?

The input schema provides full descriptions for all four parameters, including required project and zone. The description only repeats that project and zone are required, adding no new semantic meaning. Baseline of 3 is appropriate given 100% schema coverage.

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 'Lists Compute Engine reservations' with a specific verb and resource. It further enumerates the details included, distinguishing it from a generic list operation. This is unambiguous and differentiates from sibling tools like get_reservation_basic_info.

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?

The description implies usage when you need to list reservations in a given project and zone, but it does not mention alternatives or when to prefer other tools such as get_reservation_basic_info or list_commitment_reservations. No explicit exclusions or conditions are provided.

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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TDQS

A3.6/5.0

Disambiguation5/5

Each tool targets a distinct resource-action combination. For resources with both basic and detailed getters (reservations, templates), the suffixes clearly differentiate them, and list vs get distinctions are unambiguous. No two tools appear to do the same thing.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case (e.g., create_instance, list_disks, get_zone_operation). Getters consistently use descriptive suffixes like basic_info, details, or properties. No mixed naming conventions or vague verbs.

Tool Count4/5

29 tools is slightly above the ideal range but justified given the breadth of Google Compute Engine resources covered (instances, disks, templates, reservations, commitments, MIGs, snapshots, images, machine types, accelerator types). Each tool serves a specific purpose and contributes to the overall scope.

Completeness2/5

The toolset is heavily read-oriented. While instances have full lifecycle coverage (create, delete, start, stop, reset, set machine type), most other resources lack write operations: disks, templates, reservations, commitments, snapshots, and MIGs only have get/list tools. This creates dead ends for agents needing to create or modify these resources, which is a significant gap for a GCE management server.

Resources

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