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export_records

Export over 50 Gadget app records to CSV or JSON for analysis or sharing; automatic paging; returns the file path, row count, columns, and preview. Redaction settings apply.

Instructions

Export many records (beyond query_records' 50) to a CSV or JSON file on this machine for analysis or sharing. Pages through automatically. Returns the file path, row count, columns and a short preview. Redaction settings apply.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoSort value, e.g. [{ createdAt: { sortOrder: "Descending" } }]
modelYesModel name in singular camelCase, e.g. shopifyOrder
fieldsNoField selection (default: all scalar fields). Nested fields become dot-named CSV columns, e.g. "* customer { email }" → customer.email
filterNoFilter value — use introspect_filters for valid shapes
formatNoFile format (default csv)
filenameNoOptional file name (no directories); saved in the export folder (GADGET_EXPORT_DIR or ~/gadget-mcp-exports)
max_recordsNoMaximum records to export (default 10000, max 100000)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.4.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full disclosure burden and does substantial work: it reveals the side effect (writes a file to the local filesystem), that pagination is handled automatically, that redaction settings affect output, and what the result contains (path, row count, columns, preview). It omits permission requirements and overwrite/error behavior, so it is strong but not complete.

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?

Four tight sentences with the primary purpose and the sibling comparison front-loaded, then behavior, then return shape. Nothing is redundant, though 'Redaction settings apply.' is terse to the point of being slightly cryptic about what is being redacted.

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 7-parameter bulk-export tool with no output schema and no annotations, the description covers purpose, pagination, side effects and return contents, which is most of what an agent needs. Remaining gaps, such as overwrite behavior and auth requirements, are secondary but not trivial for a tool that writes files.

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 schema already documents model, fields, filter, format, filename, max_records and sort with examples. The description adds no parameter-level detail beyond the format options (already an enum) and a vague note that redaction settings apply. Baseline 3 is appropriate when the schema does the heavy lifting.

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 (export) and resource (records) plus the output form (CSV/JSON file on this machine), which is concrete and actionable. It also differentiates itself from the sibling query_records by citing the 50-record threshold, so an agent can route between them without opening a schema.

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?

Gives clear use context (bulk export for analysis or sharing) and explicitly names the alternative, query_records, with the condition that selects this tool (result sets beyond 50). It does not state any explicit when-not-to-use case (e.g. single-record lookups belong in get_record), so it falls just short of the top band.

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