# Ivx Ams Team Ops

> Ruthless team performance audits (Elon Algorithm) and meeting-to-action extraction. Use for performance audits, meeting action items, or org efficiency reviews.

- Skill: `intelli-verse-x/ivx-ams-team-ops` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds add intelli-verse-x/ivx-ams-team-ops`
- Raw SKILL.md: https://api.skillmd.com/api/skills/intelli-verse-x/ivx-ams-team-ops/raw
- Safety review: pending (external: skill-scanner FAIL, skillspector FAIL)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Productivity
- Author: intelli-verse-x (https://skillmd.com/u/intelli-verse-x)
- Updated: 2026-08-19
- Page: https://skillmd.com/skills/intelli-verse-x/ivx-ams-team-ops

---


## Cursor install notes

- Skill root: this folder (scripts + references live here).
- Vendor source: `~/.cursor/skills/_vendor/ai-marketing-skills/` (git pull to update).
- Telemetry is optional; skip `telemetry/*.py` unless you opt in.
- Run Python from this skill directory so relative paths resolve.
- Prefer `python` on Windows if `python3` is missing.

# AI Team Ops

## Working directory

```bash
cd ~/.cursor/skills/ams-team-ops
# Windows: cd $env:USERPROFILE\.cursor\skills\ams-team-ops
```

AI-powered team performance analysis and meeting intelligence: ruthless performance audits using the "Elon Algorithm" + automatic extraction of action items, decisions, and follow-ups from meeting transcripts.

## When to Use

Use this skill when:
- Evaluating team performance against OKRs/KPIs with a structured framework
- Stack ranking team members to identify A/B/C players
- Finding redundant roles, bottlenecks, and automation opportunities in your org
- Extracting action items and decisions from meeting transcripts
- Processing batch meeting notes into structured follow-up lists
- Pushing meeting action items to CRM (HubSpot) as tasks

## Tools

### Team Performance

| Script | Purpose | Key Command |
|--------|---------|-------------|
| `team_performance_audit.py` | Elon Algorithm: 5-step team audit + stack rank + scorecards | `python3 team_performance_audit.py --input team_data.json --output report.md` |

### Meeting Intelligence

| Script | Purpose | Key Command |
|--------|---------|-------------|
| `meeting_action_extractor.py` | Extract decisions, actions, follow-ups from transcripts | `python3 meeting_action_extractor.py --transcript meeting.txt --format markdown` |

## Configuration

All scripts use environment variables for LLM API access. Copy `.env.example` to `.env` and fill in your values.

### Required Environment Variables

- `ANTHROPIC_API_KEY` — Anthropic API key (Claude for analysis)
- `OPENAI_API_KEY` — OpenAI API key (alternative LLM provider)

### Optional Environment Variables

- `HUBSPOT_API_KEY` — HubSpot private app token (for pushing meeting action items as tasks)
- `LLM_PROVIDER` — `anthropic` (default) or `openai`
- `LLM_MODEL` — Model name override (default: `claude-sonnet-4-20250514` or `gpt-4o`)

## Data Flow

```
Role Descriptions + OKRs + Output Data (CSV/JSON)
        │
        ▼
┌──────────────────────────────────┐
│   team_performance_audit.py      │
│   5-Step Elon Algorithm:         │
│   1. Question requirements       │
│   2. Delete redundancies         │
│   3. Simplify workflows          │
│   4. Accelerate bottlenecks      │
│   5. Automate what's possible    │
│                                  │
│   + Score: velocity, quality,    │
│     independence, initiative     │
│   + Stack rank: A/B/C players    │
│   + Actions: promote/coach/exit  │
└──────────────────────────────────┘
        │
        ▼
Executive Summary + Individual Scorecards + Org Recommendations


Meeting Transcripts (text files or stdin)
        │
        ▼
┌──────────────────────────────────┐
│   meeting_action_extractor.py    │
│   Extract:                       │
│   • Decisions (who + context)    │
│   • Action items (owner +        │
│     deadline + priority)         │
│   • Open questions               │
│   • Key insights / quotes        │
│   • Follow-up meetings needed    │
│   • Implicit commitments         │
│   + Confidence scores            │
└──────────────────────────────────┘
        │
        ▼
Structured JSON / Markdown + Optional CRM Push
```

## Dependencies

- Python 3.9+
- `anthropic` or `openai` (for LLM-powered analysis)
- `requests` (for optional HubSpot integration)