naidx0/market-research-skill — explained in plain English
Analysis updated 2026-05-18
Generate a competitive landscape report for a company with sourced claims for every feature comparison.
Produce a visual Mermaid timeline showing where each competitor sits on a market maturity scale.
Get a structured JSON dataset of competitor research that can be reused or re-rendered.
Add competitive research capability to Claude Code as a reusable per-project or global skill.
| naidx0/market-research-skill | 0xallam/my-recipe | 0xhassaan/nn-from-scratch | |
|---|---|---|---|
| Stars | 0 | — | 0 |
| Language | Python | Python | Python |
| Last pushed | — | 2022-11-22 | — |
| Maintenance | — | Dormant | — |
| Setup difficulty | — | moderate | moderate |
| Complexity | — | 2/5 | 4/5 |
| Audience | pm founder | general | developer |
Figures from each repo's GitHub metadata at analysis time.
market-research-skill is a Claude Skill, meaning a folder of instructions that teaches Claude how to carry out a specific task well, in this case researching a company's competitors and turning that research into a finished report. A user says something like research competitors for a named company and its product category, and Claude searches the web for three to five direct competitors in the same category, records their positioning and features, and requires a source link behind every claim it writes down. Anything a source does not clearly state is marked unknown rather than guessed at. The findings are saved into a structured data file, including where each competitor sits on a four stage maturity scale from MVP up through category defining. A bundled Python script then checks that data for completeness, such as making sure every company has at least one source and every listed feature has a value, and turns it into a markdown comparison table and a Mermaid timeline diagram showing each competitor's position. The final output is a folder containing a full written report with the table and diagram embedded, plus the standalone diagram, the standalone table, and the raw structured data file behind them, rather than just a chat reply. Before finishing, Claude is instructed to walk through a checklist confirming every competitor actually came from a real search result, every filled-in table cell can be traced back to a listed source, the validation script ran successfully, and the diagram embedded in the report matches the standalone diagram file exactly. Installing it is just cloning the repository into a Claude Code skills folder, either for one project or globally for every project. It needs web search enabled in the Claude environment and Python 3.8 or later on the system path, using only Python's standard library so no extra packages need installing. The project is licensed under the MIT license.
A Claude Skill that researches a company's competitors from live web search and outputs a report plus a Mermaid roadmap.
Mainly Python. The stack also includes Python, Claude Skills, Mermaid.
Mainly pm founder.
This repo across BitVibe Labs
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