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List AI Canvas design-system templates

list_templates
Read-onlyIdempotent

List every ready-made template on AI Canvas. Use it to find full-screen dashboards, consoles, or control rooms before installing.

Instructions

Return every ready-made template on AI Canvas. A template is a complete example screen built from one design system — a dashboard, a console, a control room — installable in one CLI command. Use to discover what full screens exist before fetching one with get_template, or when the user asks for "a dashboard" / "an admin screen" rather than a single component.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
systemNoOptional design system slug to filter by, e.g. "andromeda". Omit to list templates from every system.
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering safety and mutability. The description adds contextual detail about templates being installable via CLI and being complete screens, but does not disclose further behavioral aspects like pagination, sorting, or response structure. Since annotations carry the safety profile, this adds some value but not rich behavioral context.

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?

Three sentences: state action, define key term, give usage guidance. Zero fluff, front-loaded with the core purpose, and every sentence earns its place. Highly concise while retaining all essential information.

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 simple list tool with one optional parameter, strong annotations, and no output schema, the description covers purpose, definition, and usage. It does not describe the return format, but that is not required given the lack of an output schema and the simplicity of the operation. The only minor gap is not explicitly mentioning the 'system' filter in prose, but the schema covers it, so the description is sufficiently complete.

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 description coverage is 100% for the single optional 'system' parameter, which already explains its purpose and example value. The description does not mention the parameter, but the schema fully documents it, so the baseline of 3 is appropriate.

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+resource: 'Return every ready-made template on AI Canvas' and further defines what a template is (complete example screen built from one design system). It explicitly distinguishes itself from get_template ('before fetching one with get_template') and from single-component tools, making its purpose unmistakable.

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?

The description gives explicit when-to-use guidance: 'Use to discover what full screens exist before fetching one with get_template' and 'when the user asks for "a dashboard" / "an admin screen" rather than a single component.' It also names get_template as the alternative to use after discovery, providing a clear decision path.

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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