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Add Esql Table Panel

add_esql_table_panel

Add an ES|QL table panel to an existing Kibana dashboard to display query results as rows grouped by chosen columns and numeric metric columns per row.

Instructions

Add an ES|QL table panel to an existing dashboard: show a query's output columns as a table. columns are the grouping/dimension columns — one table row per distinct value (e.g. ["status"]); metric_columns are the numeric value columns shown per row (e.g. ["count"]). esql is the query. It is NOT validated server-side — a wrong query or column name yields an empty panel, so write them carefully. For field-based charts use add_panel with a VizSpec.

space targets a Kibana space by id (default: the default space).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
esqlYes
spaceNo
titleYes
columnsYes
dashboard_idYes
metric_columnsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare a non-destructive write (readOnlyHint=false, destructiveHint=false). The description adds genuinely useful context beyond them: no server-side validation, and a wrong query or column name silently produces an empty panel. It stops short of describing the response or idempotency behavior.

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-loads the core action, then the two column parameters with concrete examples, then the critical validation caveat, then the alternative tool and the space default. Dense but every clause earns its place; the parameter definitions could be tightened slightly.

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?

With an output schema present, return values needn't be explained, and annotations cover the safety profile. The description supplies the mutation caveat, all non-obvious parameter meanings, and the space default, leaving little an agent would need before invoking it.

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 the description carries the full burden and mostly delivers: columns are defined as grouping/dimension columns (one row per distinct value, with example), metric_columns as numeric value columns (example given), esql as the query, and space as the target Kibana space with its default. Only title and dashboard_id are left implicit, which are self-evident.

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?

States a specific verb (add) and resource (ES|QL table panel to an existing dashboard) and clarifies the panel's role: 'show a query's output columns as a table.' It explicitly distinguishes itself from the sibling add_panel for field-based charts, so an agent can tell it apart from the ES|QL metric/xy siblings by the table semantics.

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?

Explicitly routes field-based charts to add_panel with a VizSpec, and warns that esql is not validated server-side so wrong input yields an empty panel. It doesn't directly contrast with the closest siblings add_esql_metric_panel and add_esql_xy_panel, leaving that distinction to inference from the name.

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