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velesnitski

yt-mcp

by velesnitski

transition_issue

Set required fields on an issue, then transition it to a target state. Returns the exact workflow rule if the transition is blocked.

Instructions

Change an issue's State, gate-aware: set required fields first, then transition, and report the exact workflow rule if it still blocks.

YouTrack workflow scripts often gate transitions ("set Dev Estimation before To Do"). A raw update fails one opaque 400 at a time; this tool applies set_fields field-by-field first (command syntax, e.g. 'Dev Estimation 2d QA Estimation 1d'), then attempts the state change. If a gate still blocks, the blocking rule's own text is returned so the caller knows exactly what to supply — nothing is ever invented.

Args: issue_id: Issue ID or URL state: Target state name (bare, e.g. 'To Do', 'Ready for QA') set_fields: Fields to set before transitioning (command syntax; optional) instance: YouTrack instance (optional)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateYes
instanceNo
issue_idYes
set_fieldsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so the description carries full burden. It discloses that set_fields is applied first, then state change, and blocking rules are returned without inventing values. It does not cover auth, rate limits, or side effects, but key behavioral traits are transparent.

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?

Description is front-loaded with a clear summary, followed by a detailed explanation and a structured args list. Every sentence adds value without redundancy. Length is appropriate for the tool's complexity.

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

Completeness4/5

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

Given the lack of annotations and presence of an output schema, the description covers gate-aware behavior, field pre-setting, and error reporting. It does not explain return values (handled by output schema) and could hint more about when to prefer update_issue, but remains sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description adds detailed meaning: issue_id ('Issue ID or URL'), state ('Target state name (bare, e.g. 'To Do')'), set_fields ('command syntax, e.g. 'Dev Estimation 2d QA Estimation 1d''), instance ('optional'). This significantly compensates for the missing schema documentation.

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 states 'Change an issue's State, gate-aware: set required fields first, then transition, and report the exact workflow rule if it still blocks.' This clearly specifies the verb (change), the resource (issue's State), and the unique gate-aware behavior, distinguishing it from siblings like update_issue.

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

Usage Guidelines4/5

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

The description explains that raw updates fail due to gates, so this tool handles field setting before transition. It implies when to use but does not explicitly state when not to use (e.g., for simple field updates without state change). Context suggests alternatives but lacks explicit exclusions.

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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