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Batch Get Changelogs

jira_batch_get_changelogs
Read-only

Batch retrieve changelogs for multiple Jira issues. Optionally filter by fields and limit results per issue.

Instructions

Get changelogs for multiple Jira issues (Cloud only).

Args: ctx: The FastMCP context. issue_ids_or_keys: List of issue IDs or keys. fields: List of fields to filter changelogs by. None for all fields. limit: Maximum changelogs per issue (-1 for all).

Returns: JSON string representing a list of issues with their changelogs.

Raises: NotImplementedError: If run on Jira Server/Data Center. ValueError: If Jira client is unavailable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issue_ids_or_keysYesComma-separated list of Jira issue IDs or keys (e.g. 'PROJ-123,PROJ-124')
fieldsNo(Optional) Comma-separated list of fields to filter changelogs by (e.g. 'status,assignee'). Default to None for all fields.
limitNoMaximum number of changelogs to return in result for each issue. Default to -1 for all changelogs. Notice that it only limits the results in the response, the function will still fetch all the data.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already provide readOnlyHint: true. The description adds valuable behavioral details: it raises NotImplementedError for on-prem, and the limit parameter only limits response data but still fetches all data. This goes beyond annotations.

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 Args, Returns, and Raises sections. It is concise and front-loaded, with every sentence providing necessary information without redundancy.

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 batch nature, readOnly annotations, and presence of output schema, the description covers purpose, parameters, return type, and error conditions completely. No gaps identified.

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?

Input schema has 100% coverage with descriptions. The description's Args section re-describes parameters but adds minimal new meaning beyond the schema. Given high schema coverage, a baseline score 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 gets changelogs for multiple Jira issues, specifying 'Cloud only'. The verb 'Get' and resource 'changelogs for multiple Jira issues' distinguishes it from sibling tools like jira_get_issue, which retrieves single issue details.

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

Usage Guidelines3/5

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

The description mentions 'Cloud only' and raises NotImplementedError for Server/Data Center, providing a clear context. However, it does not explicitly state when to use this tool versus alternatives (e.g., jira_get_issue for individual changelogs), nor when not to use it.

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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