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Avicennasis

redmine-mcp-workflows

by Avicennasis

redmine_bulk_create_issues

Create multiple issues in one call with subject-based idempotency, skipping or failing on duplicates within each project.

Instructions

Bulk-create issues with subject idempotency.

Args: issues: list of issue spec dicts (≤ 100 per call). Each spec requires project, tracker, subject; optional fields match redmine_create_issue (description, priority, status, assigned_to_id, difficulty, due_date, start_date, done_ratio, custom_fields). on_duplicate: "skip" (default) pre-checks each subject within its project and reports existing matches as skipped with duplicate_of; "fail" reports duplicates as failures; "create_anyway" skips the pre-check entirely. pacing_seconds: sleep between POSTs (default 50ms — empirically the floor for not tripping Redmine's per-issue rate cap on small VMs). Set 0 to disable. stop_on_error: True to bail at first failure; remainder lands in skipped_for_stop_on_error.

Returns {"results": [{subject, status, id?, duplicate_of?, error?, hint?}], "summary": {total, created, skipped, failed}}. Honors REDMINE_MCP_READ_ONLY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issuesYes
on_duplicateNoskip
stop_on_errorNo
pacing_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Without annotations, the description covers all critical behavioral aspects: idempotency, duplicate handling strategies, pacing (sleep between POSTs), stop_on_error behavior, and honoring REDMINE_MCP_READ_ONLY. The return format is also detailed.

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 well-structured with bullet points and front-loaded purpose. Every sentence adds value; there is no redundancy or fluff.

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 complexity (4 parameters, output schema present), the description covers input format, behavior, error handling, and return values comprehensively. Agent can confidently invoke the tool.

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?

With 0% schema description coverage, the description fully compensates by explaining each parameter: issues (list of dicts with required/optional fields), on_duplicate (three options), pacing_seconds (default and rationale), stop_on_error (behavior). It adds depth beyond 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 'Bulk-create issues with subject idempotency', specifying the core action and unique feature. It distinguishes from siblings like redmine_create_issue (single create) and redmine_bulk_update_issues (update).

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?

The description implies bulk creation use case via the name and explanation of parameters. However, it does not explicitly state when not to use or compare with alternatives, though the sibling list provides context.

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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