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cnvs.app

by app.cnvs

Create Column

create_column

Add a kanban column (swimlane) to a 'todo' board. Generates and returns a stable column id. sort is a float ordering key (ascending); omit to default to 0. lane is an integer row index for multi-row layouts (defaults to 0). color is an optional title color ('red' / 'blue' / 'green', or 'auto' / omit for default). To rename, reorder, recolor or move between lanes later use update_column.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
laneNoRow index for multi-row layouts. Defaults to 0.
sortNoFloat ordering key (ascending). Defaults to 0.
colorNoTitle color: 'red', 'blue', 'green', or 'auto' (default).
titleYes
authorNoAuthor tag, defaults to ai:claude.
board_idYes
access_keyNo8-character lowercase alphanumeric board access key when the board is locked (legacy 6-character lowercase alphanumeric keys are also accepted). Equivalent to setting the `X-Board-Key` HTTP header on the JSON-RPC POST. Omit for unlocked boards. Obtain via POST /api/boards/<id>/lock.

TDQS

A4.3/5.0
Behavior3/5

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

Annotations indicate non-readonly and open-world, but description adds little beyond the basic action; doesn't disclose side effects or error behavior.

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?

Single sentence packed with necessary info, efficient and well-structured.

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?

Sufficient for a simple create operation, mentions return ID and alternative use case.

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?

Schema covers many parameters with descriptions, but the tool description doesn't add additional parameter context; some parameters lack descriptions.

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 it adds a kanban column to a board, distinguishing from other create operations.

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 recommends using update_column for later modifications, providing clear guidance on when to use this tool.

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

All cnvs.app toolsInspect
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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: canvas items (text, image, stroke, link), kanban elements (tasks, columns, lanes), and board-level operations (create, open, preview). Even the two move tools are clearly separated: move for board items and move_task for kanban cards. Descriptions explicitly disambiguate potential overlaps (e.g., add_link vs add_text).

Naming Consistency4/5

Tool names overwhelmingly follow a verb_noun snake_case pattern (add_image, create_column, delete_task, update_task). Minor deviations: 'erase' and 'move' are single-word verbs lacking an explicit object, and 'move' could be confused with 'move_task' without descriptions. Overall the pattern is highly predictable.

Tool Count4/5

25 tools is at the high end but justified by the dual-mode scope (freeform whiteboard and kanban board). Each cluster has a coherent set covering create, read, update, delete, and specialized operations (bulk creation, export, querying, waiting for updates). Slightly heavy but well-scoped.

Completeness4/5

Core workflows for both whiteboard and kanban are covered: CRUD for text, images, tasks, columns, plus preview, export, bulk creation, and filtering. Minor gaps exist: no board rename/delete, no image resize after creation, and no bulk erase, but these can be worked around.

Resources