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set_epic_status

Destructive

Update the lifecycle status of an epic in your project backlog, managing progression from draft to in-progress, done, blocked, or deferred.

Instructions

Update the lifecycle status of an epic. Use this tool to manage the epic's own status — not the status of individual stories within it (use set_story_status for that). Typical progression: draft → in-progress (when the first story starts) → done (when all stories are complete) or deferred (if the epic is postponed). Status meanings: 'draft' = epic created but no work started; 'in-progress' = actively being worked on; 'done' = all stories complete and the epic is closed; 'blocked' = progress prevented by an external dependency; 'deferred' = postponed indefinitely. Returns {epic_id, old_status, new_status}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
epic_idYesEpic ID to update, e.g. EPIC-003
statusYesNew status to assign. Must be one of: draft, in-progress, done, blocked, deferred.
Behavior4/5

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

The description adds valuable behavioral context beyond annotations by explaining status meanings and typical progression patterns. While annotations already indicate this is a destructive, non-idempotent write operation, the description provides semantic context about what status changes mean in practice. No contradiction with annotations exists.

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 efficiently structured with clear front-loading of the core purpose, followed by usage guidance, status explanations, and return format. While slightly dense, every sentence serves a distinct purpose without redundancy.

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?

For a mutation tool with good annotations but no output schema, the description provides comprehensive context including purpose, usage guidelines, parameter semantics, and explicit return format. The only minor gap is lack of explicit mention of permissions or error conditions, but overall it's quite complete.

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

Parameters4/5

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

With 100% schema description coverage, the baseline would be 3, but the description adds meaningful semantic context about status values (explaining what each status means in practice) and mentions the return format. This provides value beyond the schema's technical parameter definitions.

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 the specific action ('Update the lifecycle status of an epic') and distinguishes it from sibling tools by explicitly contrasting with set_story_status. It provides a precise verb+resource combination that leaves no ambiguity about what the tool does.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool ('manage the epic's own status') and when not to ('not the status of individual stories within it'), with a named alternative (set_story_status). It also offers context about typical progression patterns, giving practical usage scenarios.

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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