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list_charts

Retrieve charts in the current workspace, filterable by name, visualization type, or dataset ID to locate specific charts and their identifiers.

Instructions

List charts in the current workspace.

Use this to find chart IDs and see which viz types are in use.

Args: response_mode: 'compact', 'standard', or 'full'. Default: standard. name_contains: Case-insensitive substring filter on slice_name. viz_type: Exact-match filter on viz_type (e.g. "echarts_timeseries_bar"). dataset_id: Filter to charts using this datasource_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
response_modeNostandard
name_containsNo
viz_typeNo
dataset_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries full burden. It mentions the response modes but does not disclose behaviors like pagination, ordering, permissions, or side effects. For a simple list tool, this is adequate but not thorough.

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 concise: a one-sentence purpose, a one-sentence usage hint, followed by clear bullet-style parameter descriptions. It is front-loaded and every sentence adds value.

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?

Given 0% schema coverage, the description adequately covers the parameters and purpose. It does not mention output structure, but an output schema exists (not shown). Some missing details like pagination limits are minor for a list tool; overall it is fairly complete.

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?

The input schema has 0% description coverage, so the description compensates by explaining each parameter: response_mode options, name_contains as case-insensitive substring, viz_type as exact-match, and dataset_id as datasource_id filter. This adds significant meaning beyond the schema.

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 'List charts in the current workspace,' using a specific verb and resource. It distinguishes itself from siblings like 'get_chart' (singular) and 'create_chart' by focusing on listing multiple charts.

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 provides a clear use case: 'Use this to find chart IDs and see which viz types are in use.' However, it does not explicitly exclude alternatives or provide when-not-to-use guidance, though the purpose inherently differentiates from sibling tools.

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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