How do I install the Team Ops skill?

Run npx skillmds@latest add infometa/team-ops in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Team Ops safe to use?

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Which AI agents work with Team Ops?

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Is Team Ops free to use?

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Who published Team Ops?

infometa (@infometa) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Team Ops by infometa — Agent Skill

Name: Team Ops
Rating: 4.2 (5 reviews)
Author: infometa

Team Ops

Audit team performance using the Elon Algorithm (identify A/B/C players) and extract action items from meeting transcripts. Use when asked to "audit team performance", "review my team", "extract meeting actions", "meeting notes to tasks", "team efficiency audit", or "identify underperformers".

infometa Updated Aug 19, 2026 228 repo stars

File contents

AI Team Ops

Preamble (runs on skill start)

# Version check (silent if up to date)
python3 telemetry/version_check.py 2>/dev/null || true

# Telemetry opt-in (first run only, then remembers your choice)
python3 telemetry/telemetry_init.py 2>/dev/null || true

Privacy: This skill logs usage locally to ~/.ai-marketing-skills/analytics/. Remote telemetry is opt-in only. No code, file paths, or repo content is ever collected. See telemetry/README.md.

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)

---name: team-opsdescription: Audit team performance using the Elon Algorithm (identify A/B/C players) and extract action items from meeting transcripts. Use when asked to "audit team performance", "review my team", "extract meeting actions", "meeting notes to tasks", "team efficiency audit", or "identify underperformers".---# AI Team Ops## Preamble (runs on skill start)```bash# Version check (silent if up to date)python3 telemetry/version_check.py 2>/dev/null || true# Telemetry opt-in (first run only, then remembers your choice)python3 telemetry/telemetry_init.py 2>/dev/null || true```> **Privacy:** This skill logs usage locally to `~/.ai-marketing-skills/analytics/`. Remote telemetry is opt-in only. No code, file paths, or repo content is ever collected. See `telemetry/README.md`.---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 UseUse 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` |## ConfigurationAll 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 RecommendationsMeeting 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)

Frequently asked questions