> ## Documentation Index
> Fetch the complete documentation index at: https://www.opendirectory.dev/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# pricing-finder

> Tell it what your product is (URL or description). It finds 5 competitors globally, fetches their actual pricing pages, and returns a complete pricing intell...

<Info>
  **Category:** Research · **Version:** `0.0.1` · **Author:** `opendirectory` · **Compatibility:** All targets (claude, codex, opencode, gemini, anti-gravity, openclaw, hermes)
</Info>

Tell it what your product is (URL or description). It finds 5 competitors globally, fetches their actual pricing pages, and returns a complete pricing intelligence report: the dominant pricing model in your space, a benchmark price table, feature gate analysis, a competitive positioning map, and a concrete recommended pricing strategy for your product.

**Zero API keys required.** Runs entirely on free pip dependencies.

## Install

<Tabs>
  <Tab title="npx CLI (Recommended)">
    ```bash theme={null}
    npx "@opendirectory.dev/skills" install pricing-finder --target claude
    ```
  </Tab>

  <Tab title="skills.sh">
    ```bash theme={null}
    npx skills add Varnan-Tech/opendirectory --skill pricing-finder
    ```
  </Tab>

  <Tab title="Claude Code Native">
    ```bash theme={null}
    /plugin marketplace add Varnan-Tech/opendirectory
    /plugin install opendirectory-gtm-skills@opendirectory-marketplace
    ```
  </Tab>

  <Tab title="Claude Desktop">
    <video controls className="w-full aspect-video rounded-xl mb-4" src="https://github.com/user-attachments/assets/cea8b565-2002-4a87-8857-d902bfcfdc1c" />

    1. Copy `https://github.com/Varnan-Tech/opendirectory/tree/main/skills/pricing-finder` into [download-directory.github.io](https://download-directory.github.io/) to download the ZIP.
    2. Open **Claude Desktop** -> **Customize** -> **Skills** -> **+** -> **Upload a skill** and drop the folder containing `SKILL.md`.
  </Tab>

  <Tab title="Manus AI">
    <video controls className="w-full aspect-video rounded-xl mb-4" src="https://github.com/user-attachments/assets/17cbee2a-9e17-4bd4-ac46-68e0e92ffab4" />

    [**Install pricing-finder in Manus AI**](https://manus.im/import-skills?githubUrl=https%3A%2F%2Fgithub.com%2FVarnan-Tech%2Fopendirectory%2Ftree%2Fmain%2Fskills%2Fpricing-finder\&utm_source=opendirectory)
  </Tab>
</Tabs>

## Setup

```bash theme={null}
# Set up free Python dependencies (required)
pip install ddgs requests beautifulsoup4 html2text
```

No API keys needed. Optionally add keys to `.env` for better quality:

```bash theme={null}
cp .env.example .env
# Uncomment TAVILY_API_KEY or FIRECRAWL_API_KEY if you have them
```

## Usage

```
Find pricing benchmarks for my startup: https://yourstartup.com
```

Or paste a description if you don't have a live URL:

```
Find pricing benchmarks. We build [what you do] for [who]. [Stage], [geography].
```

## What It Does

1. Fetches your product page to understand what you're building
2. Analyzes your product: category, differentiators, ICP
3. Discovers 5 competitors in your space via DuckDuckGo search
4. **Asks you to confirm the competitor list** before fetching any data
5. Fetches each competitor's pricing page (3-tier fallback: direct fetch → Google cache → search snippet)
6. Extracts structured pricing data: tiers, prices, limits, feature gates
7. Analyzes patterns across all 5 competitors
8. Maps competitive positioning and identifies underserved gaps
9. Recommends a concrete pricing strategy for your product

## Output

A pricing intel report saved to `docs/pricing-intel/[product-slug]-[date].md` containing:

* **Pricing Model Analysis** -- dominant model in your space (per-seat / flat-rate / usage-based / freemium) and why
* **Price Point Benchmark Table** -- every competitor's tiers with exact prices, free tier, free trial
* **Market ranges** -- entry tier median, mid tier median, enterprise floor
* **Feature Gate Analysis** -- what's always free, what's always paid, what varies
* **Competitive Positioning Map** -- who owns cheap+simple, middle market, enterprise, and where the gap is
* **Recommended Pricing Strategy** -- model, entry price, mid price, top price, free tier decision, annual discount, what to gate behind paid

## Cost

**\$0.00.** Entirely free using pip dependencies.

Optional API upgrades:

* Tavily API (free tier: 1000 credits/month) -- better search results
* Firecrawl API (free tier: 500 credits/month) -- better JS-heavy page rendering

## Zero-Hallucination Policy

Every price in the output traces to fetched pricing page content or a search snippet. "Contact Sales" is recorded exactly -- never estimated. Fields that could not be sourced are labeled "not found in page data." Low-quality data (search snippets) is explicitly flagged so you know which competitors to verify manually.

## How Pricing Page Fetching Works

The script tries three methods per competitor, in order:

1. **Direct fetch** (`requests` + `beautifulsoup4` + `html2text`) -- works for most pricing pages since companies make them SEO-friendly and server-rendered
2. **Google cache** -- fallback for recently-changed pages or soft blocks
3. **Search snippet** -- last resort; marks data quality as "low" in the output

If you have a Firecrawl API key, it replaces step 1 with a fully JS-rendered fetch.

## Project Structure

```
pricing-finder/
├── SKILL.md                        -- 10-step workflow for Claude Code
├── README.md                       -- this file
├── .env.example                    -- optional API key template
├── requirements.txt                -- free pip dependencies
├── scripts/
│   └── research.py                 -- two-phase data collector
├── evals/
│   └── evals.json                  -- 5 test cases
└── references/
    ├── pricing-models.md           -- per-seat, flat, usage, freemium definitions + signals
    ├── extraction-guide.md         -- how to read a pricing page
    └── positioning-guide.md        -- how to map competitors and find gaps
```

## Standalone Script Usage

```bash theme={null}
# Phase 1: competitor discovery
python3 scripts/research.py \
    --phase discover \
    --product-analysis /tmp/pf-product-analysis.json \
    --output /tmp/pf-competitors-raw.json

# Phase 2: fetch pricing pages
python3 scripts/research.py \
    --phase fetch-pricing \
    --competitors /tmp/pf-competitors-confirmed.json \
    --output /tmp/pf-pricing-raw.json

# With optional API key upgrades
python3 scripts/research.py \
    --phase fetch-pricing \
    --competitors /tmp/pf-competitors-confirmed.json \
    --firecrawl-key "$FIRECRAWL_API_KEY" \
    --tavily-key "$TAVILY_API_KEY" \
    --output /tmp/pf-pricing-raw.json
```


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