cookiy

Automate upstream AI workflow imports into Omni Skills with provenance and audit packets.

108|27|Updated Mar 26, 2026

Search Tags:#mcp #provenance #recruitment #workflows #ai-interview #cookiy #study-management

Ready to run

npx skills add https://github.com/diegosouzapw/omni-skills --skill cookiy

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

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.

Core Features & Use Cases

Upstream provenance preservation: packages upstream references, playbooks, and source manifests for auditable handoffs.
End-to-end interview workflow: supports AI interviews, recruitment previews, study creation, and reporting via MCP tools.
Reviewer-focused packaging: includes a router note, rubric, and operator packet to guide review before handoff.

Quick Start

Load the upstream workflow into the native Omni Skills shape and begin an AI interview sequence with full provenance.

Frequently Asked Questions about cookiy

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I preserve provenance when importing upstream AI workflows?▼

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.

What is an AI interview workflow with study lifecycle management?▼

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.

How do I set up MCP tools for AI interview automation and health checks?▼

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.

Can I generate auditable review packets for recruitment and guide editing?▼

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.

Does manifest-driven packaging work for upstream source preservation in AI interviews?▼

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.

What are the limitations of importing upstream AI workflows without provenance?▼

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.