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Yandex Tracker MCP

Create Issue

issue_create

Create a new issue in a Yandex Tracker queue by specifying queue, summary, and optional details like type, assignee, or custom fields.

Instructions

Create a new issue in a Yandex Tracker queue

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queueYesQueue key where to create the issue (e.g., 'MYQUEUE')
summaryYesIssue title/summary
typeNoIssue type id (from get_issue_types tool)
descriptionNoIssue description
assigneeNoAssignee login or UID
priorityNoPriority key (from get_priorities tool,)
fieldsNoAdditional fields to set during issue creation. IMPORTANT: Before creating an issue, you MUST call `queue_get_fields` to get available fields (it returns both global and local fields by default). Fields with schema.required=true are mandatory and must be provided. Use the field's `id` property as the key in this map (e.g., {'fieldId': 'value'}).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
createdAtNo
updatedAtNo
createdByNo
updatedByNo
versionNo
uniqueNo
keyNo
summaryNo
descriptionNo
typeNo
priorityNo
assigneeNo
statusNo
previousStatusNo
deadlineNo
componentsNo
startNo
storyPointsNo
tagsNo
votesNo
sprintNo
epicNo
parentNo
estimationNo
spentNo
Behavior2/5

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

Annotations provide readOnlyHint=false, implying a write operation, but the description adds no extra behavioral context like required permissions, side effects, or limits. Without further disclosures, an agent lacks transparency about the operation's impact.

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 sentence with no wasted words. However, it is slightly too sparse, missing helpful context that could be added without losing conciseness.

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?

Despite having an output schema and good parameter descriptions, the tool description lacks overall completeness. It fails to explain when to use, prerequisites, or any behavioral context beyond creation. The minimal description does not fully compensate for the tool's complexity.

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?

All 7 parameters have descriptions in the input schema (100% coverage), so the description does not need to add extra meaning. It adds no new semantics beyond what is already in the schema, so a baseline 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 explicitly states 'Create a new issue in a Yandex Tracker queue,' using a clear verb and resource. This distinguishes it from sibling tools like issue_update or issue_get.

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?

No explicit guidance on when to use this tool versus alternatives, such as when to use issue_update instead. The purpose is clear, but there is no when-not or contextual advice.

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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