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SEOmatic

by ai.seomatic
OverviewDiscussionsAdmin

import_attachment_as_dataset

Promote a spreadsheet the user uploaded IN THIS CONVERSATION (CSV/Excel - its preview carries an attachmentId) into a private dataset in their library. Call it when the user wants the file used as campaign data (pages-at-scale rows, bulk targets) or asks to save it as a dataset - the returned id then goes to propose_page_scale_campaign as libraryDatasetId with rowSourceKind 'library'. Only works on files uploaded here (stash lives ~2h); nothing else is creatable this way. Cost: FREE - reads your connected/stored data, no AI credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoDataset name (defaults to the file name)
user_intentNoOptional: one short sentence describing what the user is ultimately trying to achieve with this request. Used by SEOmatic to tailor answers and improve the product; never required.
attachmentIdYesThe attachmentId shown in the uploaded file preview

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / user_intent
      Added value: +{
+  "description": "Optional: one short sentence describing what the user is ultimately trying to achieve with this request. Used by SEOmatic to tailor answers and improve the product; never required.",
+  "maxLength": 300,
+  "type": "string"
+}
  2. Added

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, idempotentHint=false, and openWorldHint=true. The description adds valuable context: the 2-hour stash lifetime, the cost ('Cost: FREE - reads your connected/stored data, no AI credits'), and the exact next-step usage (libraryDatasetId with rowSourceKind 'library'). No contradiction with annotations; it enriches them.

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 moderately long but each sentence serves a purpose: purpose, when-to-use, constraint, cost, and integration. The key information is front-loaded with the action and resource. It is not overly verbose and avoids redundancy.

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 the tool's complexity (mutation with output schema and integration), the description covers the essential usage, constraints, and next steps. It omits error scenarios (e.g., expired attachment) but the output schema and annotations fill most gaps. The description is complete enough for an agent to call it correctly.

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 coverage is 100%, so all three parameters are documented in the schema (attachmentId from preview, name defaults, user_intent). The description does not add new parameter-specific meaning; it repeats the source of attachmentId and mentions defaults, but these are already in the schema. Baseline 3 is appropriate given full schema coverage.

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?

The description states a precise action: 'Promote a spreadsheet ... into a private dataset in their library'. It identifies the specific resource (CSV/Excel uploaded in this conversation) and distinguishes it from siblings by noting 'Only works on files uploaded here; nothing else is creatable this way.' This clearly sets it apart from dataset_library and other dataset management tools.

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

Usage Guidelines5/5

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

Explicit guidance is given: 'Call it when the user wants the file used as campaign data (pages-at-scale rows, bulk targets) or asks to save it as a dataset'. It also states the exclusion ('Only works on files uploaded here') and the downstream integration ('the returned id then goes to propose_page_scale_campaign...'). No ambiguity about when to use it.

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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