AI Team Operations

AI Team Ops

by ericosiu · MIT license · ★ 3,615 on GitHub

python3 telemetry/versioncheck.py 2>/dev/null || true

# 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.

Overview

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.

Manual install (npx, ZIP)

Claude Codenpx skills add ericosiu/ai-marketing-skills --skill team-ops -g -a claude-code

Claude Code (degit)npx degit ericosiu/ai-marketing-skills/team-ops#main ~/.claude/skills/team-ops

Claude.ai / desktopZip the folder and upload it under Settings → Capabilities → Skills.

Codex, Cursor, other agentsPoint them at SKILL.md. The other files are plain text.

Connects with Agent Alley MCP · agentalley.io/mcp

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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.

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)

1	# AI Team Ops
2
3	## Preamble (runs on skill start)
4
5	```bash
6	# Version check (silent if up to date)
7	python3 telemetry/version_check.py 2>/dev/null \|\| true
8
9	# Telemetry opt-in (first run only, then remembers your choice)
10	python3 telemetry/telemetry_init.py 2>/dev/null \|\| true
11	```
12
13	> 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`.
14
15	---
16
17	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.
18
19	## When to Use
20
21	Use this skill when:
22	- Evaluating team performance against OKRs/KPIs with a structured framework
23	- Stack ranking team members to identify A/B/C players
24	- Finding redundant roles, bottlenecks, and automation opportunities in your org
25	- Extracting action items and decisions from meeting transcripts
26	- Processing batch meeting notes into structured follow-up lists
27	- Pushing meeting action items to CRM (HubSpot) as tasks
28
29	## Tools
30
31	### Team Performance
32
33	\| Script \| Purpose \| Key Command \|
34	\|--------\|---------\|-------------\|
35	\| `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` \|
36
37	### Meeting Intelligence
38
39	\| Script \| Purpose \| Key Command \|
40	\|--------\|---------\|-------------\|
41	\| `meeting_action_extractor.py` \| Extract decisions, actions, follow-ups from transcripts \| `python3 meeting_action_extractor.py --transcript meeting.txt --format markdown` \|
42
43	## Configuration
44
45	All scripts use environment variables for LLM API access. Copy `.env.example` to `.env` and fill in your values.
46
47	### Required Environment Variables
48
49	- `ANTHROPIC_API_KEY` — Anthropic API key (Claude for analysis)
50	- `OPENAI_API_KEY` — OpenAI API key (alternative LLM provider)
51
52	### Optional Environment Variables
53
54	- `HUBSPOT_API_KEY` — HubSpot private app token (for pushing meeting action items as tasks)
55	- `LLM_PROVIDER` — `anthropic` (default) or `openai`
56	- `LLM_MODEL` — Model name override (default: `claude-sonnet-4-20250514` or `gpt-4o`)
57
58	## Data Flow
59
60	```
61	Role Descriptions + OKRs + Output Data (CSV/JSON)
62	│
63	▼
64	┌──────────────────────────────────┐
65	│ team_performance_audit.py │
66	│ 5-Step Elon Algorithm: │
67	│ 1. Question requirements │
68	│ 2. Delete redundancies │
69	│ 3. Simplify workflows │
70	│ 4. Accelerate bottlenecks │
71	│ 5. Automate what's possible │
72	│ │
73	│ + Score: velocity, quality, │
74	│ independence, initiative │
75	│ + Stack rank: A/B/C players │
76	│ + Actions: promote/coach/exit │
77	└──────────────────────────────────┘
78	│
79	▼
80	Executive Summary + Individual Scorecards + Org Recommendations
81
82
83	Meeting Transcripts (text files or stdin)
84	│
85	▼
86	┌──────────────────────────────────┐
87	│ meeting_action_extractor.py │
88	│ Extract: │
89	│ • Decisions (who + context) │
90	│ • Action items (owner + │
91	│ deadline + priority) │
92	│ • Open questions │
93	│ • Key insights / quotes │
94	│ • Follow-up meetings needed │
95	│ • Implicit commitments │
96	│ + Confidence scores │
97	└──────────────────────────────────┘
98	│
99	▼
100	Structured JSON / Markdown + Optional CRM Push
101	```
102
103	## Dependencies
104
105	- Python 3.9+
106	- `anthropic` or `openai` (for LLM-powered analysis)
107	- `requests` (for optional HubSpot integration)
108