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create_work_items

Create 1 to 50 work items in one project in a single request. Validates standard enums and custom fields; a single invalid item rejects the entire batch.

Instructions

Create 1-50 work items in one project in a single bulk request.

Standard enums (type/status/severity/priority) are validated — unknown ids raise ValueError with valid options. custom_fields keys are validated against the type's schema. Atomic: one bad item rejects the whole batch; an id-count mismatch raises — re-query list_work_items before retrying.

Items are created free-floating; place into a document with move_work_item_to_document (this tool cannot). description is Markdown → sanitized HTML; later edits are raw-HTML round-trip via get_work_item(include_description_html=True) ↔ update_work_items. Markdown tables get native Polarion styling; a paragraph starting 'Table:' directly after a table becomes a numbered caption widget.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesWork items to create in one request (1-50).
dry_runNoPreview payload without writing; guards still query Polarion.
project_idYesPolarion project ID.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
createdYes
dry_runYes
work_item_idsNo
payload_previewNo
Behavior5/5

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

Goes well beyond annotations. Details validation of enums and custom_fields, atomicity, error handling (id-count mismatch), free-floating creation, and description rendering (Markdown→HTML, round-trip editing). No contradiction with annotations.

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?

Well-organized: core operation first, then validation, error handling, placement, and description details. Every sentence adds value, though slightly verbose with markdown specifics. Still concise overall.

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?

Explains error scenarios, post-creation steps, and description rendering. With an output schema present, the lack of return value details is acceptable. Covers all complex aspects of the tool.

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

Parameters4/5

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

Schema coverage is 100%, baseline 3. The description adds value by explaining enum validation (raises ValueError with options), custom_fields validation, and description Markdown behavior, which are not in the schema.

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 verb (create), resource (work items), and constraints (1-50, one project, bulk). It distinguishes from sibling tools like update_work_items and move_work_item_to_document.

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?

Provides explicit guidance: bulk creation, atomic behavior, validation rules, error handling (re-query list_work_items), and post-creation placement via move_work_item_to_document. Tells when not to use (for single items or placement).

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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