Automate upstream AI workflow imports into Omni Skills with provenance and audit packets.
npx skills add https://github.com/diegosouzapw/omni-skills --skill cookiy
Please help me install this Agent Skill. Skill: cookiy Source: https://github.com/diegosouzapw/omni-skills/tree/main/skills/cookiy Command: npx skills add https://github.com/diegosouzapw/omni-skills --skill cookiy
Importing upstream AI workflows into Omni Skills often loses provenance and auditability. This Skill preserves source context, provides a complete operator packet, and keeps reviewer notes intact for governance.
Load the upstream workflow into the native Omni Skills shape and begin an AI interview sequence with full provenance.
High-intent search queries and answers about installing and using this skill.
Preserve upstream AI workflow provenance by packaging source manifests, playbooks, and references into auditable operator packets. This ensures source context and reviewer notes remain intact for governance during handoffs.
An AI interview workflow with study lifecycle management automates recruitment previews, study creation, and reporting via MCP tools. It provides end-to-end orchestration from initial intake through final reporting.
Set up MCP tools for AI interview automation by loading the upstream workflow into the native Omni Skills context. MCP integration handles setup, health checks, and governance across the interview sequence.
Yes, you can generate auditable review packets for recruitment and guide editing. The packaging includes a router note, rubric, and operator packet to guide reviewer assessment before final handoff.
Manifest-driven packaging works for upstream source preservation by capturing references and playbooks during AI interview orchestration. This satisfies requirements for router guidance and operator-facing packets.
Importing upstream AI workflows without provenance loses source context, auditability, and reviewer notes. Without manifest-driven packaging, governance tracking across intake, editing, and reporting stages breaks down.
diegosouzapwPackage upstream PM/UX research workflows with provenance manifests and review rubrics.
issdandavisEmit JSON cross-talk packets with session IDs for auditable AI lane handoffs.
thimsluggaIdentify and leverage MCP n8n tools to build, validate, and deploy workflows.
AgentientConsolidate multi-model research outputs into provenance-enriched reports with quality metrics.
