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invokeai_boards

Manage InvokeAI image boards by listing, creating, updating, deleting, and assigning images to keep your generated artwork organized.

Instructions

Manage boards (collections of generated images).

[RATIONALE] Boards are the primary organization surface of the InvokeAI gallery; all board operations share one record store and one portmanteau.

Return Format

{"success": bool, "operation": str, "data": {...}, "message": str}

Examples

invokeai_boards(operation="list") invokeai_boards(operation="create", board_name="Concept art") invokeai_boards(operation="add_image", board_id="board-uuid", image_names=["abc123.png"])

Notes:

  • Board ids come from invokeai_boards(operation='list').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
board_idNoBoard id (required for get, update, delete, add_image, remove_image).
operationYesBoard operation to perform.
board_nameNoBoard name (required for create, update).
image_namesNoImage names to assign/remove (add_image, remove_image).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the return format and includes examples that clarify operation behavior. However, it does not warn about destructive actions (e.g., delete is permanent), permissions, or side effects. The 'shared record store' note is vague and not actionable.

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 well-structured with a brief opening, rationale, return format, examples, and a note. Each section earns its place, though the phrase 'one portmanteau' is obscure and adds little. It is not overly verbose for the complexity of a 7-operation tool.

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?

The tool has 7 operations and 4 parameters, and the description covers the return format, common examples, and a key reference detail (how to obtain IDs). It does not document every operation in depth, but the pattern is inferable, and the output schema exists to provide return details. Overall, it is sufficiently complete for invocation.

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?

Schema coverage is 100%, so the baseline is 3. The description adds value by showing concrete invocation patterns (e.g., board_id from list, image_names as a list) and pairing parameters with the operations that need them. This goes beyond the schema's field-level descriptions and helps the agent construct valid calls.

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 clear, specific verb+resource pair: 'Manage boards (collections of generated images).' It distinguishes this tool from gallery/workflow/etc. siblings by explicitly scoping it to board operations. The rationale reinforces the unique role of boards in the gallery.

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 clearly implies when to use the tool (any board management task), and provides examples for common operations (list, create, add_image). It does not explicitly mention alternatives or exclusions, but the context is sufficient for most decisions. The note about board IDs coming from list adds a practical prerequisite.

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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