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bulk_create_tasks

Create multiple tasks for a project in one atomic request, preserving order and validating every entry so invalid batches fail without creating any tasks.

Instructions

Create several tasks in one project, in one request. Needs the v2 API.

Vikunja creates the batch atomically: if one entry is invalid then none are created, and the error names the entry that failed. The tasks also keep the order they were given. A loop of create_task calls races: a numbered plan can come back shuffled, and a failure halfway through leaves the rest uncreated.

Each entry is an object taking the same fields as create_task. title is required; description, priority, due_date, start_date, end_date, percent_done, is_favorite, repeat_after, and repeat_mode are optional and mean what they do there, including an empty string to clear a date. Anything else is refused. A dropped key would read as a task created with a date or a priority it never got. Vikunja caps a batch at 100.

Returns a summary per created task, in creation order. Call get_task for the full detail of one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tasksYes
project_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.2.0

TDQS

A5/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden, and it excels: it discloses atomicity, the error naming the failed entry, ordering guarantees, the 100-task cap, strict validation that refuses unknown fields, the empty-string date-clearing convention, and the summary-only return format. This goes well beyond what the sparse schema provides.

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?

The description is front-loaded with the core purpose and then provides dense, non-redundant behavioral and parameter details. Each paragraph earns its place: atomicity, ordering, comparison to create_task, field semantics, limits, and return-value guidance. Nothing is filler.

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?

Given the tool's moderate complexity and zero annotation coverage, the description is complete: it covers the API requirement, atomic behavior, ordering, validation, batch limit, field semantics, and return type. The output schema likely covers the exact summary shape, so the description's high-level mention of 'summary per created task' is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the schema only declares project_id and tasks as generic types, so the description must compensate. It does so thoroughly by listing required and optional fields, explaining that entries mirror create_task fields, and warning that unknown keys are refused and dropped keys can silently produce unintended dates or priorities.

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 opens with 'Create several tasks in one project, in one request,' giving a specific verb and resource while clearly distinguishing it from the single-task create_task sibling. It also states the v2 API requirement and the atomic/ordered batch behavior, so an agent can identify exactly what this tool is for.

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?

The description explicitly contrasts this tool with a loop of create_task calls, explaining that the loop races and can leave partially-created tasks, while bulk_create_tasks is atomic and preserves order. It also directs the agent to get_task when full detail of an individual task is needed, providing clear when-to-use and when-not-to-use guidance.

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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