● Open Source CLI Tool

Map the funnel.
Inspect the proof.

Explore a brand’s public touchpoints, offer sequence, and open questions in one sourced report.

See Demo Report (AG1) ↗ View on GitHub Quick Start ↓

Inspect the touchpoints

Conceptual journey. Open the AG1 report for sourced observations.

This report’s seven journey labels

Unaware

Problem Aware

Solution Aware

Product Aware

Most Aware

Customer

Advocate

The report groups observations by journey stage. Missing evidence remains an open question.

What you get

Read what the sources support.

One command, one report, full breakdown.

📡

Awareness Coverage Map

See exactly which Schwartz stages the brand is hitting — and which gaps they're leaving open for competitors.

⟶

Full Funnel Diagram

Mermaid.js flowchart of the complete stranger-to-advocate journey with color-coded awareness stages.

✓ / ⚡

Bustamante-Style Analysis

What's Working and What's Missing for every single funnel step. Specific, actionable, not generic.

💰

Offer Stack

All identified offers with price, type, awareness target, and connection to the funnel step that presents them.

❓

Epistemic Honesty

Open questions distinguish what the public sources show from what remains unknown.

💾

Step Cache & Resume

Each agent's output is cached to .tmp/. Re-run just Agent 3 without repeating the web search.

How it works

3 agents, 1 report.

Sequential pipeline with shared Pydantic state.

Brand Resolver

gpt-4o-mini

Web search → identifies brand, website, founder, ICP, confidence level

Touchpoint Mapper

gpt-4o-mini

Web search + homepage scraping → maps all public channels by awareness level

Journey Mapper

claude-sonnet-4-6

Deep reasoning → full funnel map with steps, offers, working/missing, open questions

↓

HTML Report

pure Python

Deterministic renderer → dark-mode report with Mermaid.js diagrams

Quick start

Run your first report.

Requires Python 3.9+, an OpenAI key, and an Anthropic key.

Clone and install

Clone the repo and install Python dependencies.

git clone https://github.com/siddchauhan77/funnel-teardown

cd funnel-teardown

pip3 install -r requirements.txt

Add your API keys

Copy the env template and add your OpenAI + Anthropic keys.

cp .env.example .env

# Then edit .env:

OPENAI_API_KEY=sk-...

ANTHROPIC_API_KEY=sk-ant-...

Run your first teardown

Pass any brand name. Optionally add hints to disambiguate.

# Basic usage

python3 teardown.py "Athletic Greens"

# With disambiguation hints

python3 teardown.py "Justin Welsh" --url justinwelsh.me

# Re-run only the journey mapper (uses cached brand + touchpoints)

python3 teardown.py "Justin Welsh" --from-cache --agent 3

Output lands in output/{brand}_{timestamp}/teardown_report.html. Open it in any browser.

All CLI flags

python3 teardown.py "Brand Name"
  --founder "Founder Name"   # disambiguation hint
  --url "website.com"         # website hint
  --from-cache                 # load .tmp/ cache instead of re-running Agent 1+2
  --agent 3                    # start from this agent (1, 2, or 3)
    

Map the funnel.Inspect the proof.

Read what the sources support.

3 agents, 1 report.

Run your first report.

Map the funnel.
Inspect the proof.