team-ops

Name: team-ops
Availability: InStock
Author: LazyIsEfficient

Ingest role descriptions and performance data to produce structured scorecards and rankings.

15|3|Updated Apr 9, 2026

Search Tags:#audit #leadership #data-analytics #team-management #scorecards #LLM-analysis

Ready to run

npx skills add https://github.com/LazyIsEfficient/agentic-os --skill team-ops

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: team-ops
Source: https://github.com/LazyIsEfficient/agentic-os/tree/main/.claude/skills/team-ops
Command: npx skills add https://github.com/LazyIsEfficient/agentic-os --skill team-ops

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires anthropic, openai, and includes scripts (resource) and references (resource) components.

What problem does it solve?

AI-powered team performance auditing that quantifies how individuals contribute to OKRs/KPIs, surfaces redundancies and bottlenecks, and delivers concrete, actionable recommendations for improving organizational efficiency.

Core Features & Use Cases

Ingests role descriptions, OKRs/KPIs, and performance data to produce structured scorecards and stack-ranked views of the team.
Applies the Elon Algorithm (Question, Delete, Simplify, Accelerate, Automate) to identify waste, overlapping responsibilities, and automation opportunities, with qualitative analysis.
Outputs executive summaries, individual scorecards, and org-level recommendations aligned to business goals, enabling data-driven people decisions.

Quick Start

Run the team_performance_audit.py script with your team data to generate a comprehensive audit report.

Frequently Asked Questions about team-ops

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

FAQPage Schema

How do I audit team performance using OKRs and KPIs?▼

You can audit team performance by ingesting role descriptions, OKRs/KPIs, and performance data to produce structured scorecards and stack-ranked views. This identifies redundancies and bottlenecks, delivering actionable recommendations for organizational efficiency.

What is the Elon Algorithm for team management and how does it identify automation opportunities?▼

The Elon Algorithm applies Question, Delete, Simplify, Accelerate, and Automate phases to identify waste and overlapping responsibilities. It surfaces automation opportunities within team workflows through qualitative LLM analysis and quantitative local scoring.

Do I need LLM providers to generate team performance scorecards?▼

No, LLM providers are not required for quantitative team performance scorecards, as local scripts compute scores independently. Optional Anthropic or OpenAI dependencies are only required for generating qualitative insights and analysis.

How do I identify overlapping responsibilities and redundancies in a team structure?▼

You identify overlapping responsibilities and redundancies by running the team performance audit script with role descriptions and performance data. It applies the Elon Algorithm to detect waste and outputs individual scorecards and org-level recommendations.

What data do I need to prepare for a team management audit?▼

For a team management audit, prepare role descriptions, OKRs/KPIs, and performance data as inputs. Providing this data allows the script to generate executive summaries, individual scorecards, and org-level recommendations aligned to business goals.

Can I use OpenAI and Anthropic together for qualitative team analysis?▼

Yes, OpenAI and Anthropic can both be used for qualitative team analysis. Both are optional dependencies that provide qualitative insights, while quantitative scores are computed locally without requiring either provider.