kappaemme-git/codex-startup-pricing-lab — explained in plain English
Analysis updated 2026-05-18
Compare subscription, lifetime, usage based, and other pricing models for a new product.
Check whether a lifetime deal is financially safe given ongoing product costs.
Audit an existing pricing page and get a safer pricing experiment roadmap.
Generate a 14 day plan for testing price hypotheses with real buyers.
| kappaemme-git/codex-startup-pricing-lab | 1ncendium/aibuster | aaronmayeux/ha-hurricane-tracker | |
|---|---|---|---|
| Stars | 5 | 5 | 5 |
| Language | Python | Python | Python |
| Setup difficulty | easy | moderate | easy |
| Complexity | 2/5 | 3/5 | 2/5 |
| Audience | pm founder | ops devops | general |
Figures from each repo's GitHub metadata at analysis time.
Codex Startup Pricing Lab is a skill for the Codex AI assistant focused specifically on pricing. Instead of guessing a single price, it researches how a product delivers value, who buys it, which costs continue after a sale, and how current competitors charge, then compares a range of monetization models before making a recommendation. Given a startup URL, repository, pricing page, or description, the skill researches official competitor pricing pages and compares subscription, annual, one time, lifetime, per seat, usage based, credit, freemium, and hybrid models. It scores plausible models from 0 to 100 using deterministic rules and will reject unsafe uncapped lifetime deals when the product has ongoing costs or support obligations. It then picks a primary monetization model plus a testable alternative, and recommends specific plan tiers, target segments, value metrics, upgrade triggers, trial structures, annual discounts, and price hypotheses to test. The skill separates what it treats as product facts, current competitor pricing, cost evidence, real demand evidence, and plain assumptions or unknowns. Competitor prices are used only as market reference points, not as proof that customers will pay a given amount, and every recommended number is labeled as a hypothesis until it has been tested with real buyers. Running the skill produces a scored JSON file, a markdown pricing report that opens in Codex and renders on GitHub, and a CSV roadmap laying out a fourteen day pricing validation plan with a metric and decision rule for each day. It can also audit an existing pricing page and suggest a safer testing plan. The skill only uses public information and user supplied input: it does not touch private billing data, change Stripe products, update live prices, or contact customers on its own. It installs via npx or manual copy into the Codex skills folder and is released under the MIT license.
A Codex skill that researches competitor pricing and recommends evidence backed pricing models, plans, and a 14 day testing roadmap.
Mainly Python. The stack also includes Python, Codex.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly pm founder.
This repo across BitVibe Labs
double-check against the repo, no cap.