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validate_chart

Validates chart query parameters by executing the chart's query context and returns render status with actionable errors for missing metrics, columns, or other issues.

Instructions

Run chart query validation and return render status.

This validates the saved chart params against chart-data execution, returning actionable errors for missing metrics/columns/etc.

Notes:

  • This does not take a screenshot; it executes the same query context used for chart rendering.

  • dashboard_id speeds lookup of chart form_data. If omitted, all dashboards are scanned.

Args: chart_id: Chart ID to validate dashboard_id: Optional dashboard context for form_data lookup row_limit: Query row limit used for validation force: Whether to force recomputation (if supported by backend) response_mode: 'compact' (small summary), 'standard' (default), or 'full' (raw payload + metadata)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chart_idYes
dashboard_idNo
row_limitNo
forceNo
response_modeNostandard

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, but description discloses key behaviors: does not take a screenshot, executes same query context, dashboard_id speeds lookup. Covers the main behavioral aspects.

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?

Front-loaded with purpose, efficient use of bullet points and notes. No wasted words. Could be slightly more concise but overall well-structured.

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 output schema exists, description doesn't need to explain return values. Covers validation concept, parameter meanings, and special notes. Adequate for the tool's complexity, though missing some details on error handling.

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 description coverage is 0%, so description must compensate. It provides brief explanations for all 5 parameters, including enum values for response_mode. Adds meaning beyond the schema, though could be more detailed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it validates chart query and returns render status, with specific verb and resource. Does not explicitly differentiate from sibling tools like validate_chart_render, but the purpose is clear.

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?

Provides context on when to use (validate chart params) and notes about dashboard_id, but lacks explicit guidance on when not to use or alternatives among siblings.

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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