Manage tasks and messages for AI-driven protocol generation on the Elnora platform.
npx skills add https://github.com/Elnora-AI/elnora-plugins --skill elnora-tasks
Please help me install this Agent Skill. Skill: elnora-tasks Source: https://github.com/Elnora-AI/elnora-plugins/tree/main/elnora/skills/elnora-tasks Command: npx skills add https://github.com/Elnora-AI/elnora-plugins --skill elnora-tasks
Provides a structured, API-driven way to create, message, and manage conversation-based tasks on the Elnora platform so users can generate, iterate on, and retrieve AI-generated bioprotocols without manual orchestration across projects and files.
Create a task in the target project with an initial message describing the protocol you need and include any relevant file IDs for context.
High-intent search queries and answers about installing and using this skill.
To generate AI-driven bioprotocols, you create a project-scoped task with an initial prompt and optional file attachments as context, then send iterative messages to refine the AI-generated protocol results.
Yes, you can attach reference files to protocol generation tasks by including file IDs in your initial prompt or follow-up messages, providing the AI with necessary experimental templates and contextual data.
You manage and paginate task message histories using cursor or page-based pagination to read ordered conversations, allowing you to fetch the latest assistant response and handle long-running AI generation with explicit wait expectations.
The best way to organize AI protocol generation across multiple projects is using UUID-based identifiers to create, update, and archive conversation-based tasks within specific project and organization scopes.
Yes, the Elnora platform supports archiving completed bioprotocol conversations, allowing you to update task statuses and archive conversations tied to specific projects and organizations after protocol generation is complete.
AI protocol generation responses take long because the system handles long-running AI generation processes with explicit wait expectations, requiring time to process initial prompts and iterative refinement messages with file attachments.
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