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Get issue

get_issue
Read-only

Contexto completo de una issue en una sola llamada: identificador legible (TEAM-N), título, descripción markdown, contexto del agente (agentContext), estado, prioridad, asignado, fecha de vencimiento (dueDate, epoch ms), labels, milestone, cycle, sub-issues, comentarios, actividad (issue_events), adjuntos, relaciones (blocks/blocked_by/relates, cada una con el estado de la otra issue; si no puedes verla, solo su identificador y su estado) y los valores de los campos personalizados (customFields). Incluye el estado de trabajo en curso: agentWorking (nombre del agente que la tomó, null si está libre), agentWorkingBy (su userId) y agentWorkingSince. agentCloseState (stateId, name, instruction) es el estado de cierre que el dueño o un admin del workspace ha configurado para el trabajo de los agentes.

Input Schema

NameRequiredDescriptionDefault
idYesAdmite el UUID de la issue o su identificador legible (TEAM-123, el que se ve en la app), sin distinguir mayúsculas. Si ese identificador existiera en varios de tus workspaces hay que pasar el UUID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover readOnlyHint and openWorldHint, yet the description still adds real behavior: relations are truncated to identifier+state when the linked issue is not visible, and it explains the in-progress work lock (agentWorking null when free, agentWorkingBy, agentWorkingSince) plus what agentCloseState means. The notable omission is any warning about payload size or pagination for comments/activity/issue_events, which can be large.

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

Conciseness3/5

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

The core statement is front-loaded and earns its place, but the body is one very long run-on sentence that chains a dozen field names with commas and parentheticals, which is hard to scan. Since there is no output schema, the field list carries value, but it could be structured or trimmed.

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?

With no output schema, enumerating the returned fields is exactly the right compensation, and it covers the non-obvious ones (agentContext, customFields, relation states, close-state instruction). What is missing is return-size behavior — whether comments/events are capped or paginated — which matters for an all-in-one detail tool.

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 single `id` parameter is fully documented in the schema, including the UUID-vs-TEAM-123 ambiguity across workspaces. The description adds nothing about the identifier beyond noting the readable TEAM-N format appears in the returned data, so the baseline 3 applies.

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?

Opens with a specific verb+resource and scope: 'Contexto completo de una issue en una sola llamada', then enumerates the payload (description, state, relations, customFields, agentWorking, agentCloseState). An agent immediately knows this is the full-detail read, implicitly contrasted with the list/search siblings. It never names list_issues, search_issues or next_ready_issue, so the differentiation is inferential rather than explicit.

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?

'En una sola llamada' implies you come here when you need everything about one known issue, and the note about relations you cannot see implies a permission model. But there is no explicit when-to-use vs. list_issues/search_issues guidance, no prerequisites, and no statement about cost or response size. Usage is only implied.

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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