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import_tasks_csv

Import tasks from CSV into Dart AI with validation and parallel creation. Preview and fix errors using validate-only mode before actual import.

Instructions

Import tasks from CSV file with validation and parallel creation. CRITICAL: ALWAYS use validate_only=true first! Production safety: validate → fix errors → import.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
csv_dataNoCSV data as string (use this OR csv_file_path)
csv_file_pathNoPath to CSV file (use this OR csv_data)
dartboardYesDartboard dart_id or name for all imported tasks
column_mappingNoCustom column name mapping (e.g., {"Task Name": "title", "Owner": "assignee"})
validate_onlyNoPreview mode (default: TRUE for production safety). Returns validation errors and preview without creating tasks.
continue_on_errorNoContinue importing valid rows even if some fail (default: true)
concurrencyNoParallel task creation (default: 5, range: 1-20)
Behavior3/5

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

No annotations exist, so the description carries full burden. It mentions validation and parallel creation but does not disclose potential side effects (e.g., task creation confirmation, error behavior, or idempotency). Some behavioral traits are implied but not explicit.

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?

Two sentences with no wasted words. Front-loaded with purpose, followed by critical usage note. Highly efficient.

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

Completeness3/5

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

Given the tool's complexity (7 parameters, no output schema, no annotations), the description is incomplete. Missing return value hints (e.g., task IDs, success count) and error handling details beyond validation.

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?

All parameters have descriptions in the input schema (100% coverage), so the description adds little beyond reinforcement of validate_only importance. Baseline of 3 is appropriate.

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 clearly states the tool's function: importing tasks from a CSV file. It highlights validation and parallel creation, which distinguishes it from sibling tools like create_task (single import) and batch_create_tasks.

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?

Explicitly instructs to always use validate_only=true first, and outlines a safety workflow: validate → fix errors → import. This provides clear guidance on proper usage.

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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