团队效能与会议洞察 Skill

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.

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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)