Jira Cloud MCP Server

update_worklog

Update a worklog entry on a Jira issue by providing the issue key and worklog ID, adjusting comments or time spent, and controlling estimate changes and notifications.

Instructions

Update worklog

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "issueIdOrKey": "<issueIdOrKey>",
      "id": "<id>",
      "body": "<body>"
    },
    "name": "update_worklog"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	The ID of the worklog.
`body`	Yes	Request body (JSON object)
`expand`	No	Use [expand](#expansion) to include additional information about worklogs in the response. This parameter accepts `prope
`newEstimate`	No	The value to set as the issue's remaining time estimate, as days (\#d), hours (\#h), or minutes (\#m or \#). For example
`notifyUsers`	No	Whether users watching the issue are notified by email.
`issueIdOrKey`	Yes	The ID or key the issue.
`adjustEstimate`	No	Defines how to update the issue's time estimate, the options are: * `new` Sets the estimate to a specific value, defi	auto
`overrideEditableFlag`	No	Whether the worklog should be added to the issue even if the issue is not editable. For example, because the issue is cl

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 30, 2026

TDQS

C2.7/5.0

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. 'Update worklog' conveys mutation but does not disclose side effects such as changing issue time estimates, notifying watchers, overwriting fields, or respecting editability flags. This is a significant transparency gap for a mutation tool.

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

Conciseness2/5

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

The description is only two words, which is concise, but this is under-specification rather than effective conciseness. It restates the tool name and contributes no additional information that would help an agent select or invoke the tool. The definition does not earn its place beyond being a label.

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?

For a complex 8-parameter mutation tool with no annotations and no output schema, the description is far too sparse. It omits what the request body should contain, how time estimate adjustment works, and what response behavior to expect. The rich schema covers parameter formats, but the overall tool context is incomplete.

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%, and the schema documents all eight parameters including the nested body object and the adjustEstimate enum. The description itself adds no parameter-level meaning, so the baseline score of 3 is appropriate because the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Update worklog'. It clearly indicates the operation is modifying an existing worklog, which distinguishes it from sibling tools like add_worklog, delete_worklog, and get_worklog. However, it provides no details about what aspects of the worklog can be updated, so it stops short of the richest possible purpose statement.

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?

The description gives no guidance on when to use this tool versus alternatives. It does not mention that it is for existing worklogs only, nor does it reference add_worklog for creating worklogs or delete_worklog for removing them. Usage context is left entirely to inference from the tool name.

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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