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nulab

Backlog MCP Server

update_issue

Modify an existing issue in Backlog. Update fields such as summary, status, priority, assignee, due dates, custom fields, and attachments.

Instructions

Updates an existing issue

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issueIdNoThe numeric ID of the issue (e.g., 12345)
issueKeyNoThe key of the issue (e.g., 'PROJ-123')
summaryNoSummary of the issue
issueTypeIdNoIssue type ID
priorityIdNoPriority ID
descriptionNoUpdates an existing issue
startDateNoScheduled start date (yyyy-MM-dd)
dueDateNoScheduled due date (yyyy-MM-dd)
estimatedHoursNoEstimated work hours
actualHoursNoActual work hours
categoryIdNoCategory IDs
versionIdNoVersion IDs
milestoneIdNoMilestone IDs
statusIdNoStatus ID
resolutionIdNoResolution ID
assigneeIdNoUser ID of the assignee
notifiedUserIdNoUser IDs to notify
attachmentIdNoAttachment IDs
commentNoComment to add when updating the issue
customFieldsNoList of custom fields to set on the issue
organizationNoOptional organization name. Use list_organizations to inspect available organizations.
Behavior2/5

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

With no annotations, the description bears full responsibility for behavioral disclosure. It only states 'Updates an existing issue', omitting critical details such as whether unspecified fields remain unchanged, what permissions are required, or any side effects like notifications. This is insufficient 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.

Conciseness4/5

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

The description is a single short sentence, which is efficient and front-loaded. However, it is almost too concise, missing opportunities to add value without becoming verbose. Still, no wasted words.

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 the complexity (21 parameters, mutation tool, no output schema, no annotations), the description is too minimal. It does not explain return values, field behavior on partial updates, or practical usage context. The agent lacks sufficient information to use the tool effectively.

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% with detailed parameter descriptions in the input schema. The tool description adds no extra meaning beyond the schema, meeting the baseline expectation for high coverage.

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 'Updates an existing issue', which is a specific verb+resource combination. It effectively distinguishes from sibling tools like 'add_issue' (create) and 'delete_issue' (delete).

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?

No usage guidance is provided. The description does not indicate when to use this tool versus alternatives, nor does it specify any prerequisites or exclusions. This leaves the agent without contextual decision support.

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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