Competitive Product Research

Problem

Competitive research often means chasing fragments across company websites, app stores, official PDFs, store reviews, and user feedback. Manual searching, verification, screenshots, table cleanup, and Word formatting take time and can miss market size, competitor differences, feature sets, or user pain points. This skill turns that workflow into a repeatable research task: given a company or product name, it gathers background, services, market size, competitor comparison, app/software features, user feedback, derivative manuals, and product screenshots, then assembles a structured Word report draft.

How It Works

• It starts with web_search for company background, product features, user reviews, and market signals, then uses web_fetch to pull key pages from official sites, App Store pages, or public documents.
• For official PDF manuals, it downloads files with urllib.request; if certificate issues appear, it may use ssl._create_unverified_context() as described in the source, then extracts text and renders page screenshots with PyMuPDF.
• It builds the report with python-docx, applying fixed styles for headings, body text, tables, headers, page numbers, and image paths. Screenshots go into a screenshots/ directory, and the output resembles {workspace}/{company_name}_competitive_research.docx.

Limits and Caveats

This is best for desk research, feature comparison, manual summarization, and first-draft report assembly. It is not a substitute for legal due diligence, financial modeling, precise market-share estimation, or investment decisions. Output quality depends on search and fetch reliability; sites with broken certificates, access restrictions, or changed page structures may require manual supplementation and verification of data freshness.