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1luvc0d3
by 1luvc0d3

execute_card

Read-onlyIdempotent

Execute a saved Metabase card by ID and retrieve its query results, with optional parameters, pagination, column selection, and response format.

Instructions

Execute an existing question/card and get results

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
card_idYesCard ID to execute
parametersNoOptional parameters for parameterized queries
fieldsNoColumn names to include in results (default: all)
formatNoResponse format (default: compact). Use "default" for pretty-printed output
limitNoMax rows to return (default: server maxRows setting)
offsetNoRow offset for pagination

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.3.0
    • addedInput schema / properties / fields
      Added value: +{
      +  "description": "Column names to include in results (default: all)",
      +  "items": {
      +    "type": "string"
      +  },
      +  "type": "array"
      +}
    • addedInput schema / properties / format
      Added value: +{
      +  "description": "Response format (default: compact). Use \"default\" for pretty-printed output",
      +  "enum": [
      +    "default",
      +    "compact"
      +  ],
      +  "type": "string"
      +}
    • addedInput schema / properties / limit
      Added value: +{
      +  "description": "Max rows to return (default: server maxRows setting)",
      +  "maximum": 10000,
      +  "minimum": 1,
      +  "type": "number"
      +}
    • addedInput schema / properties / offset
      Added value: +{
      +  "description": "Row offset for pagination",
      +  "minimum": 0,
      +  "type": "number"
      +}
  2. First observedv1.1.1

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and idempotentHint, aligning with the description. The description adds no further behavioral context (e.g., caching, performance implications), but does not contradict the annotations.

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?

The description is concise and front-loaded, but could be slightly improved by including the tool's main function without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (6 parameters, no output schema), the description lacks crucial context such as return format, pagination behavior, or support for parameterized queries.

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%, so the baseline is 3. The description adds no extra parameter meaning beyond what the schema already provides.

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?

The description clearly states the tool executes an existing card and returns results, but does not differentiate from sibling tools like batch_execute or execute_query.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as execute_query or batch_execute. This forces the agent to infer usage patterns.

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