This file documents environment variables visible in the checked-in source of this repository snapshot. It is not guaranteed to be exhaustive for the full product, because many imported files are not present here.
For each variable, this document gives:
| The best skills for AI jobs in India range from technical mastery of languages like Python and SQL to essential soft skills like critical thinking and AI ethics. As of 2026, the Indian AI market is rapidly expanding, particularly in Global Capability Centres (GCCs) and sectors like BFSI (Banking, Financial Services, and Insurance) and healthcare, where AI-skilled professionals can see salary premiums of up to 56%. [1, 2, 3, 4] | |
| ## Essential Technical Skills | |
| Technical expertise is the foundation for roles like Machine Learning Engineer, NLP Engineer, and Data Scientist. [5, 6] | |
| * Programming Languages: Python remains the top choice due to its extensive library ecosystem (NumPy, Pandas, Scikit-learn, PyTorch, and TensorFlow). Other valuable languages include SQL for data handling, R for statistical analysis, and Java or C++ for high-performance enterprise applications. | |
| * Mathematics & Statistics: A strong foundation in linear algebra, calculus, probability, and statistics is critical for building, fine-tuning, |
As a Technology Leader and CAIO, I have observed that the evolution of Agentic AI has shifted the focus from "prompt engineering" to "context engineering." The emergence of files like AGENTS.md, CLAUDE.md, and SKILLS.md represents a move toward standardized, repository-level governance for AI agents. The following table provides a structured comparison of these "Context Manifest" files used in modern AI-augmented development environments. Comparative Analysis: AI Context Manifest Files
| Sl. No. | File Name | Primary Purpose | Best Suited For | Key Components |
|---|---|---|---|---|
| 1 | CLAUDE.md | Environment & Task Governance | Cursor / Claude Code users | Build commands, test patterns, and style guide enforcement. |
| 2 | AGENTS.md | Cross-Agent Protocol | Multi-agent swarms (e.g., ProjectCodeX) | High-level architectural intent, "Anti-patterns," and tribal knowledge. |
| 3 | SKILLS.md | Tooling & Capability Mapping | MCP (Model Context Protocol) | Definitions of external tools, API schemas, and executio |
| Job Title: SAP Solution Architect | |
| Location: EY (Ernst & Young) Business Consulting | |
| Location: Bangalore, India | |
| Experience Required: 10-12 years | |
| Job Description:- | |
| We are seeking a seasoned SAP Solution Architect with a robust understanding of the SAP ecosystem. This individual will be a key player in creating and executing strategic plans related to SAP implementation, maintenance, and enhancement. They will also be responsible for designing, developing, and implementing SAP modules to enhance business functionality and overall performance while maintaining a high degree of customer satisfaction. | |
| Required Skills: | |
| 1. 10-12 years of experience in SAP architecture design and development. |
| import spacy | |
| # Load a pre-trained NLP model from spaCy | |
| nlp = spacy.load("en_core_web_sm") | |
| # Define a function to handle user input and generate a response | |
| def respond(input): | |
| # Parse the user input using the NLP model | |
| doc = nlp(input) |
| $ irb | |
| >> 1.class | |
| => Fixnum | |
| >> 1.respond_to?(:dup) | |
| => true | |
| >> 1.dup | |
| TypeError: can't dup Fixnum | |
| from (irb):3:in `dup' | |
| from (irb):3 |
| # To parse a tweet from twitter to get teh '@' , '#' and the text seperated | |
| parsed_text = tweet.text.gsub(/ ?(@\w+)| ?(#\w+)/) { |a| ((a.include?('#')) ? tags : replies) << a.strip.gsub(/#|@/,''); '' } |
| # A nice way to format the default rails date magic field to human readable format | |
| @foo.created_at.strftime("%b %d %Y") |
| # Working and strong RegEx for email validation in Ruby | |
| /\A([\w\.%\-\+]+)@((?:[-a-z0-9]+\.)+[a-z]{2,})\z/i |
| page.select('#DOM_element_id').each do |foo| | |
| foo.value = bar | |
| end |