project

Create research projects via agent-driven gap analysis or interactive scaffolding.

46|5|Updated Mar 7, 2026
One-click install
npx skills add https://github.com/victoriacity/openakari --skill project-victoriacity
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: project
Source: https://github.com/victoriacity/openakari/tree/main/.claude/skills/project
Command: npx skills add https://github.com/victoriacity/openakari --skill project-victoriacity

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill streamlines the creation of new research projects, whether initiated by an agent identifying a gap or by a human requesting a new project scaffold.

Core Features & Use Cases

  • Agent-Initiated Proposals: Agents can scan the repository for research gaps, assess their project-worthiness, and write formal proposals for PI review.
  • Human-Initiated Scaffolding: The Skill interactively guides humans to define project objectives, success criteria, and scope, then sets up the necessary directory structure and initial files.
  • Use Case: An agent identifies a gap in understanding user behavior from past experiments and automatically proposes a new project to investigate it. Alternatively, a researcher can use the skill to quickly set up a new project directory for tracking experiments on a new topic.

Quick Start

Use the project skill to propose a new research project on the topic of optimizing LLM inference latency.

Frequently Asked Questions about project

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

FAQPage Schema
How do I scaffold a new research project directory structure and define success criteria?

To scaffold a new research project, this Skill interactively guides you to define project objectives, success criteria, and scope, then automatically sets up the necessary directory structure and initial files for tracking experiments.

How does agent-driven gap analysis work for automatic research proposal generation?

Agent-driven gap analysis works by having agents scan your repository to identify research gaps, assess their project-worthiness, and automatically write formal proposals for principal investigator review before project initiation.

Can I use project scaffolding to assess feasibility and align with existing knowledge architecture?

Yes, you can use project scaffolding to assess feasibility and ensure alignment with existing knowledge and system architecture, as it supports lifecycle initiation by formally defining research questions and scope constraints.

What is the best way to initiate a research project on optimizing LLM inference latency?

The best way to initiate a research project on optimizing LLM inference latency is to request a proposal generation, which triggers gap analysis, defines the research questions, and scaffolds the initial project files.

Does the research initiation workflow integrate with existing repository conventions for file generation?

Yes, the research initiation workflow integrates directly with your existing repository conventions to ensure proper proposal and project file generation during the scaffolding process.

When should I not use automated proposal generation for research initiation?

You should avoid automated proposal generation when human-driven interactive scaffolding is required to manually define nuanced project objectives, success criteria, and scope that an agent cannot autonomously infer from repository gaps.