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pascalhubacher

Jira Cloud MCP Server

create_issues

Bulk create multiple Jira issues in one API call using a list of issue updates. Save time by submitting all new issues together in a single request.

Instructions

Bulk create issue

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesRequest body (JSON object)

Schema Changelog

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

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Bulk create issue' only indicates a write operation and bulk behavior; it does not mention failure modes, partial success, limits, authentication needs, or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, but it is under-specified rather than efficiently complete. There is no structure or additional context to help an agent understand the bulk creation semantics or request format.

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

Completeness2/5

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

Given that there is no output schema, no annotations, and a nested input body, the tool needs more contextual detail. The description does not explain how issueUpdates should be formed, what constraints exist, or what the bulk operation returns.

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 description coverage is 100% for the single body parameter, so the baseline is 3 even though the description itself adds no parameter-level meaning. The schema describes body as 'Request body (JSON object)' but does not explain the issueUpdates items; however, per the rubric, high coverage keeps this at baseline.

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 'Bulk create issue' clearly states the verb (create), the resource (issue), and the bulk qualifier, which distinguishes it from the sibling tool create_issue. This is specific enough for an agent to identify the tool's core purpose.

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

Usage Guidelines2/5

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

There is no guidance about when to use this tool versus alternatives such as create_issue, submit_bulk_edit, or bulk_fetch_issues. The description does not mention any conditions, exclusions, or preferred contexts.

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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