create-item
SolidCreates an MCP work item from conversation context. Scans existing containers to anchor the item in the right place (Bugs, Features, Tech Debt, Observations, etc.), infers type and priority, creates single items or work trees, and pre-fills required notes. Use when the conversation surfaces a bug, feature idea, tech debt item, or observation worth tracking persistently. Also use when user says: track this, log this bug, create a task for, or add this to the backlog.
Install
Quality Score: 86/100
Skill Content
Details
- Author
- jpicklyk
- Repository
- jpicklyk/task-orchestrator
- Created
- 1 years ago
- Last Updated
- 1 months ago
- Language
- Kotlin
- License
- MIT
Integrates with
Bundled in these plugins
Similar Skills
Semantically similar based on skill content — not just same category
task-new
Create a NEW work item with Baron — reach a well-specified item first (grill for the missing detail when the input is thin), infer the type role (task/bug/story), resolve the right parent, then create it. Use when the user describes new work to record ("we need...", "bug:", "add a task for..."). Starting work on it afterwards is task-start.
work-item
Drafts well-formed work items with testable acceptance criteria, then creates them in whatever tracker is connected if the user explicitly asks for that. Also applies the same standard to tighten up an existing work item. TRIGGER when: the user invokes /work-item; OR asks to draft, write up, create, or fix up a ticket, issue, task, story, bug report, or sub-task — for Jira, GitHub, Azure DevOps, Linear, or any other tracker — even when they don't name a tracker or use the word "ticket" explicitly, e.g. "log a bug for...", "file an issue about...", "write up a task for...", "can you create a story for...", "this ticket has no acceptance criteria, can you add some". Do NOT use for general prose writing, PR descriptions, or commit messages — those follow different conventions.
context-item-creation
Guides you through creating context items — instructions, skills, knowledge pointers, and memory events — that give the AI analyst persistent knowledge about your organization. Covers when to create each type, naming conventions, folder organization, and the hard boundary between context (rules and procedures) and the semantic layer (logic and calculations).