Codacy
SonarQube
CodeClimate
CodeFactor.io
ESLint
Coveralls
SensioLabs Insight
codebeat
mdstill
Firecrawl
Reducto
Mindee
Parsio.io
ConvertAPI
CloudConvert
Codacy automates code reviews and monitors code quality on every commit and pull request reporting back the impact of every commit or pull request, issues concerning code style, best practices, security, and many others. It monitors changes in code coverage, code duplication and code complexity. Saving developers time in code reviews thus efficiently tackling technical debt. JavaScript, Java, Ruby, Scala, PHP, Python, CoffeeScript and CSS are currently supported. Codacy is static analysis without the hassle.
mdstill is a document-ingestion tool purpose-built for LLM and RAG workflows. Where generic converters dump messy text, mdstill outputs clean, semantic markdown that preserves tables, headings, and document structure โ the things LLMs actually need to understand context.
What you can do with it:
Prepare documents for RAG pipelines (chunk-ready, semantic boundaries preserved) Feed PDFs, Word files, or spreadsheets into ChatGPT, Claude, or Gemini without losing tables Build knowledge bases in Obsidian, Notion, or Logseq from existing document archives Extract structured context for AI agents and embeddings How it's different: Deep-conversion mode runs layout-aware parsing (tables, OCR, multi-column PDFs) โ not just text dumping. Markdown output is ~40% more token-efficient than raw text, so your LLM costs drop. REST API available for pipeline automation.
Free tier, no signup required for basic use. Competes with markitdown, Unstructured.io, and LlamaParse โ but with a zero-friction web UI.
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mdstill's answer:
mdstill is built specifically for LLM and RAG workflows, not generic file conversion. Drop any of 20+ document formats (PDF, Word, Excel, PowerPoint, EPUB, and more) and get back clean, structure-preserving Markdown that's tuned for ChatGPT, Claude, Gemini context windows and vector-database ingestion. Tables stay intact, headers become linkable anchors, output is ~40% more token-efficient than raw text extraction. Free web tool + REST API โ humans and pipelines use the same engine.
mdstill's answer:
Alternatives fall into two camps: developer libraries that require setup, or enterprise SDKs that require a sales call. mdstill fills the middle: open a browser, drop a file, get Markdown in seconds โ and when you need to scale, the same conversion runs through a REST API. 20+ formats in one tool instead of picking a different parser per format. Tables survive the trip (most tools mangle them). Files are deleted immediately after processing. Free tier, no credit card, no signup for basic use.
mdstill's answer:
Two overlapping groups. Developers building AI features โ engineers feeding documents into ChatGPT, Claude, or Gemini APIs; teams building RAG pipelines and AI agents who need reliable document ingestion. Knowledge workers and researchers โ Obsidian and Notion users importing legacy PDFs, students preparing papers for AI analysis, analysts converting spreadsheets for LLM review. Common thread: anyone who's discovered that pasting raw PDF text into an LLM loses tables and wastes tokens.
mdstill's answer:
mdstill started from a personal frustration: feeding documents into ChatGPT and Claude meant pasting messy PDF text with broken tables and lost structure, or paying for heavyweight enterprise tools just to preprocess a few files. The fix seemed obvious โ Markdown is what LLMs understand best, so the conversion should be a utility anyone can use, not a product you buy. mdstill was built to make high-quality document-to-Markdown preprocessing free and instant for everyone, with an API for teams who need to scale.
mdstill's answer:
mdstill launched publicly in April 2026 and is in the early-adopter phase. Currently used by individual developers, indie AI-tool builders, and small research teams โ customer logos will be added as early adopters opt in to share them.
mdstill's answer:
Python + FastAPI on the backend, Next.js + TypeScript on the frontend.
Based on our record, Codacy seems to be more popular. It has been mentiond 4 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I'm trying to use Codacy to review my code. One of the issues is regarding the use of the "setcookie" function. Source: over 4 years ago
Does anyone have an example on how to get this conversion done on github actions where I can convert the *.coverage file into a *.xml file for uploading to codacy.com. Source: about 5 years ago
Online analysisFinally, if you want a simple way to analyze your code without having to manually configure everything locally, you can use an online code review service such as Codacy (shameless plug here). We already integrate some of the mentioned detection tools in this article and we are working every day to improve the service. The other main benefit of using automated code review tools is to allow you to... - Source: dev.to / over 5 years ago
Because you care and because you always want to be better, automation is a great way to optimize your review workflow process. Go ahead and do a quick search on Google for automated code reviews and see who better fits your workflow. You'll find Codacy on your Google search and we hope you like what we do. - Source: dev.to / over 5 years ago
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