Add/update CONTRIBUTION.md and add LICENSE (MIT)

CONTRIBUTION.md

@@ -1,76 +1,170 @@
 # Contributing to 500-AI-Agents-Projects
 
-Thank you for your interest in contributing to 500-AI-Agents-Projects! This project is a collection of AI agent projects and examples; contributions from the community are welcome. This document explains how to contribute, what we expect, and the process for submitting changes.
+Welcome — this repository collects 500 AI agent projects, templates, demos, and integrations. Thank you for helping grow a practical, reproducible, and responsible catalog of agent work. This document is tuned to the AI-agent focus of the project: reproducibility, model/data hygiene, evaluation, and safety.
 
-## Table of Contents
+Quick summary
+- Add small, runnable, well-documented agent examples and templates.
+- Prefer reproducible demos and small checkpoints or external download scripts.
+- Follow the folder schema and metadata so projects are discoverable and automatable.
+- Pay attention to license, data provenance, and ethical/safety notes.
 
-- How to contribute
-- Code style and standards
-- Branching and commits
-- Issues
-- Pull requests
-- Tests
-- Review and merge process
-- Reporting security issues
-- Code of conduct
+---
 
-## How to contribute
+## What to contribute
+- New agent projects (single- or multi-agent; code, notebooks, or demos).
+- Templates/boilerplates for agent types (reactive, planning-based, learning agents, RL, LLM-based, etc.).
+- Integrations (environments, simulators, observability / logging tools).
+- Shared tooling (evaluation harnesses, metrics, benchmark suites, dataset loaders).
+- Docs, reproducible experiments, visualization utilities, or lightweight datasets (or links to them).
 
-There are several ways to contribute:
+If your contribution is large (new category, many projects, major refactor) please open an issue first to coordinate placement and naming.
 
-- Open an issue to report bugs, request features, or propose new project ideas.
-- Submit a pull request (PR) with improvements, bug fixes, documentation updates, or new projects.
-- Help review open PRs and provide constructive feedback.
+---
 
-Before submitting substantial changes (like new project additions), please open an issue first to discuss the idea with maintainers.
+## Project folder requirements (must-have)
+Each agent project added must include the following at the top level of its folder:
 
-## Code style and standards
+- README.md — concise description, intended use-case, quick start with exact commands, expected output, and runtime (CPU/GPU/time).
+- LICENSE or a note referencing repository root LICENSE (see root LICENSE).
+- requirements.txt, pyproject.toml, or environment.yml (pin critical dependency versions).
+- One or more runnable examples (script or notebook) that reproduce the core behavior.
+  - Provide minimal example(s) that run in <10 minutes on a modest machine where possible.
+- tests/ or a smoke-test script with instructions to run them.
+- metadata.yaml or metadata.json (see example below).
+- small models / datasets should be included only if tiny. Prefer external hosting (Hugging Face, S3, Google Drive) with a download script.
 
-- Follow consistent formatting. Where appropriate, add or update linting configuration files (e.g., .prettierrc, .eslintrc) so automatic formatting is used.
-- Write clear, concise code with comments where necessary.
-- Keep project-level READMEs up to date. Each project folder should include a README.md describing purpose, setup, usage, and license.
+Example metadata schema (recommended)
+```yaml
+title: quick-chatbot-agent
+author: Your Name <you@example.com>
+language: python
+tags:
+  - llm
+  - agent
+  - rl
+license: MIT
+datasets:
+  - name: example-dialogs
+    url: https://...
+entrypoint: run_demo.py
+requirements: requirements.txt
+```
 
-## Branching and commits
+---
 
-- Fork the repository and create a feature branch off main. Name branches as feature/short-description or fix/short-description.
-- Keep changes focused and small; one logical change per PR makes review easier.
-- Use descriptive commit messages. Prefer the format:
+## Naming & layout conventions
+- Folder names: lowercase, hyphen-separated (e.g., multi-agent-pursuit).
+- Place one logical project per folder.
+- Keep demos and notebooks near the code: demo.ipynb and run_demo.py in the project root.
+- Avoid committing large binaries. Use .gitattributes or .gitignore to keep repository clean.
 
-  type: short description
+---
 
-  Where type is one of: feat, fix, docs, style, refactor, test, chore
+## Reproducibility & experiments
+- Include seed values, environment variables, and exact dependency versions.
+- Provide a minimal run command and expected output sample.
+- For stochastic experiments, include evaluation scripts and deterministic seeds or checkpoints.
+- If results require large compute or private data, include a small reproducible “toy” example that demonstrates the same pipeline on tiny inputs.
 
-Example: "feat: add sample multi-agent example"
+---
 
-## Issues
+## Models, datasets & large files policy
+- Don’t add large datasets or model checkpoints directly. Instead:
+  - Provide a download script (download.sh / download.py) that fetches artifacts from a stable host (Hugging Face, S3, Zenodo).
+  - Document the expected location/path after download.
+- Clearly state dataset licenses, attribution, and any usage restrictions.
+- When linking to external model weights provide their license and any fine-tuning provenance.
 
-- Search existing issues before opening a new one to avoid duplicates.
-- Use clear titles and provide steps to reproduce if reporting bugs. Include environment details and relevant logs or errors.
-- For feature requests, explain the motivation and suggested behavior.
+---
 
-## Pull requests
+## Code style, documentation & tests
+- Python: follow PEP 8, add a linter config (.flake8, pyproject.toml with [tool.black] or similar).
+- JS/TS: provide ESLint/Prettier configs where relevant.
+- Document complex algorithms with short docstrings and references.
+- Add unit or integration tests when possible. Include a lightweight smoke test that CI can run quickly.
 
-- Link related issues in the PR description using "Fixes #<issue-number>" when appropriate.
-- Describe what the PR does, why it is needed, and any tradeoffs.
-- Update or add tests and documentation as needed.
-- Keep PRs draft if you want feedback before finalizing.
+---
 
-## Tests
+## Evaluation & metrics
+- Include an evaluation script that produces metrics (accuracy, reward, latency).
+- State measurement conditions (hardware, seeds).
+- Where applicable, include latency and memory cost alongside performance metrics.
 
-- Where applicable, include automated tests for new features or bug fixes.
-- Describe test steps in the PR if automated tests are not available.
+---
 
-## Review and merge process
+## CI / GitHub Actions recommendations
+- If adding workflows, put them under .github/workflows and ensure expensive jobs are optional or use small inputs.
+- Recommended checks: lint, unit tests, smoke demos. Heavy training jobs should be omitted or gated/opt-in.
 
-- Maintainers will review PRs and may request changes. Address review comments and push follow-up commits.
-- Once approved, a maintainer will merge the PR. We use a non-fast-forward merge strategy to preserve PR history when appropriate.
+---
 
-## Reporting security issues
+## PR process and checklist
+Before opening a PR:
+- [ ] Fork and create a branch: feat/<short-desc> or fix/<short-desc>
+- [ ] Update README and metadata
+- [ ] Include tests or a smoke-test demonstration
+- [ ] Ensure no secrets or private data are included
+- [ ] Confirm license compatibility for added assets
 
-If you discover a security vulnerability, please do NOT open a public issue. Instead, contact the repository owner directly or use GitHub's private security advisory feature.
+PR description should include:
+- What changed and why
+- How to run the example(s) and tests
+- Links to related issues or external artifacts (datasets, model hosts)
 
-## Code of conduct
+Suggested minimal PR template (add to .github/PULL_REQUEST_TEMPLATE.md if helpful):
+```markdown
+## Summary
+Short description of change
 
-By participating in this project, you agree to follow a respectful and inclusive code of conduct. Be constructive and courteous in issues and reviews.
+## How to run
+1. pip install -r requirements.txt
+2. python run_demo.py
 
----
+## Checklist
+- [ ] README updated
+- [ ] metadata.yaml added/updated
+- [ ] smoke test included
+```
+
+---
+
+## Security, secrets & responsible disclosure
+- Never commit secrets, private keys, or API tokens.
+- If you discover a security vulnerability, do not open a public issue. Contact maintainers privately (see repository contact info) or use GitHub's private security advisory.
+
+---
+
+## Ethics, fairness & safety
+AI agents can amplify harms. When contributing:
+- Include an explicit "Ethical considerations" or "Safety notes" section in the README if the agent interacts with people, makes decisions, or processes personal data.
+- State potential biases, failure modes, and appropriate usage guidance.
+- Avoid shipping models trained on clearly disallowed data (private or scraped personal content without consent).
+- Prefer human-in-the-loop defaults for high-risk demos and clearly mark such demos as not production-ready.
+
+---
+
+## Licensing and attribution
+- Respect upstream licenses for models, code, and datasets. Include attribution and license text where required.
+- If the project uses third-party models/datasets, list their license and link to the source.
+
+---
+
+## Communication & review
+- Maintainers will review PRs and may request changes. Please reply to review comments and push updates.
+- For large or disruptive changes, maintainers may ask for staged PRs to ease review.
+
+---
+
+## Contributor support & contact
+If you need early feedback:
+- Open an issue describing your planned contribution with the following: summary, folder name, and minimal example of what you plan to add.
+- For urgent or private matters, use the contact method listed in the repository (owner profile / repo settings).
+
+---
+
+## Code of Conduct
+By contributing, you agree to the project's Code of Conduct. Be respectful, constructive, and collaborative.
+
+---
+
+Thank you for contributing to 500-AI-Agents-Projects — your examples, templates, and tools make the agent community stronger and more reproducible.