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import_glossary_csv

DestructiveIdempotent

Imports CSV content into a glossary in unidirectional or multidirectional formats, returning an import job ID to poll until complete.

Instructions

Imports a CSV file into a glossary. Supports unidirectional and multidirectional formats. This is an async operation that returns an import job object containing an import_id. Poll with check_glossary_import_status using the returned import_id until the import is complete.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes	The glossary ID (format: gls_*, e.g., 'gls_xyz123')
`gzip`	No	Whether the CSV content is gzip compressed
`csv_content`	Yes	The content of the CSV file to upload
`content_type`	Yes	The format of the CSV file. 'csv/table-uni' for unidirectional, 'csv/table-multi' for multidirectional	csv/table-uni

Output Schema

TableJSON Schema

Name	Required	Description
`id`	Yes	Import job identifier
`end`	No	End offset of the import
`size`	No	Total number of entries in the import
`begin`	No	Begin offset of the import
`channel`	No	Channel identifier used by the import
`progress`	No	Import progress between 0 and 1 (1 means complete)

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv2.0.0Sep 29, 2026
- removedOutput schema / additionalProperties
```
Removed value: -{}
```

Changed1 schema field changedv1.0.4May 29, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "begin": {
+      "description": "Begin offset of the import",
+      "type": "number"
+    },
+    "channel": {
+      "description": "Channel identifier used by the import",
+      "type": "number"
+    },
+    "end": {
+      "description": "End offset of the import",
+      "type": "number"
+    },
+    "id": {
+      "description": "Import job identifier",
+      "type": "string"
+    },
+    "progress": {
+      "description": "Import progress between 0 and 1 (1 means complete)",
+      "type": "number"
+    },
+    "size": {
+      "description": "Total number of entries in the import",
+      "type": "number"
+    }
+  },
+  "required": [
+    "id"
+  ],
+  "type": "object"
+}

Addedv1.0.2May 4, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations declare destructiveHint=true and idempotentHint=true, yet the description adds genuinely non-derivable workflow context: the operation is asynchronous, returns a job object with an import_id, and must be polled to completion. It omits any warning about what the destructive import overwrites in the target glossary, which is the one notable gap.

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?

Three tight sentences: purpose, format scope, then the async/polling contract, each front-loaded with no filler. Every sentence carries distinct information.

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

Completeness5/5

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

An output schema exists, so return values need no explanation, and the description still covers the async lifecycle end-to-end including the sibling tool to poll with. For a destructive, annotated import tool, nothing needed to invoke and complete the workflow is missing.

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 id/content_type/csv_content/gzip are already fully documented in the schema. The description restates the unidirectional vs multidirectional distinction that the content_type enum already encodes, adding no new syntax or format detail.

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 and resource ('Imports a CSV file into a glossary') and names the supported formats, which distinguishes it from the sibling import_tmx (TMX vs CSV). An agent can identify the tool without opening the 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?

Explicitly tells the agent the call is async and routes the follow-up to check_glossary_import_status with the returned import_id — a clear when/how-to-continue instruction. It does not, however, compare against import_tmx or state when CSV import is preferred over other ingestion paths.

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