Add AI agent configs, contributing guide, and issue templates

- CLAUDE.md, AGENTS.md, .github/copilot-instructions.md for AI agent support
- CONTRIBUTING.md with AI-first workflow explanation and code example guidance
- Issue templates for feature requests and bug reports

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: 2 people

.github/ISSUE_TEMPLATE/bug_report.md

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+---
+name: Bug Report
+about: Report a bug or unexpected behaviour
+title: 'fix: '
+labels: bug
+assignees: ''
+---
+
+## Description
+
+<!-- Clear description of the bug -->
+
+## Steps to Reproduce
+
+1. 
+2. 
+3. 
+
+## Expected Behaviour
+
+<!-- What should happen -->
+
+## Actual Behaviour
+
+<!-- What actually happens -->
+
+## Environment
+
+- OS: 
+- Python version: 
+- Package version: 
+
+## Original Prompt
+
+<details>
+<summary>Click to expand starting prompt</summary>
+
+<!-- If this issue was created from an AI prompt, paste the original prompt here -->
+
+</details>

.github/ISSUE_TEMPLATE/feature_request.md

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+---
+name: Feature / Task Request
+about: Propose a new feature, improvement, or task
+title: ''
+labels: enhancement
+assignees: ''
+---
+
+## Overview
+
+<!-- 2-4 sentence summary of what this task is and why it matters -->
+
+## Plan
+
+<!-- High-level bullet-point plan, human readable, no code -->
+
+<details>
+<summary>Detailed implementation plan</summary>
+
+### Affected Repositories
+<!-- List repos this touches, mark primary -->
+
+### Implementation Steps
+<!-- Step-by-step with file paths and specifics -->
+
+### Key Files
+<!-- List files that will be modified -->
+
+</details>
+
+## Example Code
+
+<!-- If your feature involves a specific calculation, algorithm, or small piece of functionality,
+     include example code here. Even a rough script, a working prototype, or a snippet showing
+     the existing behaviour you want changed helps enormously.
+
+     Code gives AI agents and human contributors concrete context and dramatically reduces
+     misunderstandings. Delete this section if not applicable. -->
+
+```python
+# Paste your example code here
+```
+
+## Original Prompt
+
+<details>
+<summary>Click to expand starting prompt</summary>
+
+<!-- If this issue was created from an AI prompt, paste the original prompt here -->
+
+</details>

.github/copilot-instructions.md

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+# Copilot Coding Agent Instructions
+
+You are working on **PyAutoConf**, the configuration management library for the PyAuto ecosystem.
+
+## Key Rules
+
+- Run tests after every change: `python -m pytest test_autoconf/`
+- All files must use Unix line endings (LF, `\n`)
+- If changing public API (function signatures, class names, import paths), clearly document what changed in your PR description — all downstream PyAuto packages depend on this
+
+## Architecture
+
+- `autoconf/conf.py` — Core configuration system
+- `autoconf/dictable.py` — Dictionary/serialization support
+- `autoconf/fitsable.py` — FITS file handling
+- `autoconf/json_prior/` — JSON-based configuration priors
+- `autoconf/tools/` — Utility decorators and helpers
+- `test_autoconf/` — Test suite
+
+## Sandboxed runs
+
+```bash
+NUMBA_CACHE_DIR=/tmp/numba_cache MPLCONFIGDIR=/tmp/matplotlib python -m pytest test_autoconf/
+```

AGENTS.md

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+# PyAutoConf — Agent Instructions
+
+**PyAutoConf** is the configuration management library for the PyAuto ecosystem. It handles object serialization/deserialization, JSON-based priors, and configuration generation.
+
+## Setup
+
+```bash
+pip install -e ".[dev]"
+```
+
+## Running Tests
+
+```bash
+python -m pytest test_autoconf/
+```
+
+### Sandboxed / Codex runs
+
+```bash
+NUMBA_CACHE_DIR=/tmp/numba_cache MPLCONFIGDIR=/tmp/matplotlib python -m pytest test_autoconf/
+```
+
+## Key Architecture
+
+- `autoconf/conf.py` — Core configuration system
+- `autoconf/dictable.py` — Dictionary/serialization support for YAML
+- `autoconf/fitsable.py` — FITS file handling
+- `autoconf/json_prior/` — JSON-based configuration priors
+- `autoconf/tools/` — Utility decorators and helpers
+- `autoconf/mock/` — Mock objects for testing
+
+## Key Rules
+
+- All files must use Unix line endings (LF)
+- If changing public API, note it in your PR description — all downstream PyAuto packages depend on this
+
+## Working on Issues
+
+1. Read the issue description and any linked plan.
+2. Identify affected files and write your changes.
+3. Run the full test suite: `python -m pytest test_autoconf/`
+4. Ensure all tests pass before opening a PR.
+5. If changing public API, clearly document what changed — PyAutoFit, PyAutoArray, PyAutoGalaxy, and PyAutoLens all depend on this package.

CLAUDE.md

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+# PyAutoConf
+
+**PyAutoConf** is the configuration management library for the PyAuto ecosystem. It handles object serialization/deserialization via YAML, JSON-based priors and configuration generation, and provides utility tools for scientific Python applications.
+
+- Package name: `autoconf`
+- Requires Python >= 3.9
+
+## Repository Structure
+
+- `autoconf/` — Main package
+  - `conf.py` — Core configuration system
+  - `dictable.py` — Dictionary/serialization support
+  - `fitsable.py` — FITS file handling
+  - `json_prior/` — JSON-based configuration priors
+  - `tools/` — Utility decorators and helpers
+  - `mock/` — Mock objects for testing
+- `test_autoconf/` — Test suite (pytest)
+
+## Commands
+
+### Install
+```bash
+pip install -e ".[dev]"
+```
+
+### Run Tests
+```bash
+python -m pytest test_autoconf/
+python -m pytest test_autoconf/ -s
+```
+
+### Codex / sandboxed runs
+
+When running Python from Codex or any restricted environment, set writable cache directories:
+
+```bash
+NUMBA_CACHE_DIR=/tmp/numba_cache MPLCONFIGDIR=/tmp/matplotlib python -m pytest test_autoconf/
+```
+
+## Line Endings — Always Unix (LF)
+
+All files **must use Unix line endings (LF, `\n`)**. Never write `\r\n` line endings.

CONTRIBUTING.md

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+# AI-Assisted Development
+
+This project uses an AI-first development workflow. Most features, bug fixes, and improvements are implemented through AI coding agents (Claude Code, GitHub Copilot, OpenAI Codex) working from structured issue descriptions.
+
+## How It Works
+
+1. **Issues are the starting point** — Every task begins as a GitHub issue with a structured format: an overview, a human-readable plan, a detailed implementation plan (in a collapsible block), and optionally the original prompt that generated the issue.
+
+2. **AI agents pick up issues** — Issues can be assigned to AI coding agents (e.g. GitHub Copilot) which read the issue description, `AGENTS.md`, and `CLAUDE.md` for context, then implement the changes autonomously.
+
+3. **Human review** — All AI-generated pull requests are reviewed by maintainers before merging.
+
+## Creating an Issue
+
+When opening an issue, please use the provided issue templates. The **Feature / Task Request** template follows our standard format:
+
+- **Overview** — What and why, in 2-4 sentences
+- **Plan** — High-level bullet points (human-readable)
+- **Detailed implementation plan** — File paths, steps, key files (in a collapsible block)
+- **Original Prompt** — If you used an AI to help draft the issue, include the original prompt
+
+If your feature involves a specific calculation, algorithm, or small piece of functionality — **include example code**. Even a rough script, a working prototype, or a snippet showing the existing behaviour you want to change makes a huge difference. Code examples give AI agents and human contributors concrete context to work from, and dramatically reduce misunderstandings about what you're asking for.
+
+This structure ensures that both human contributors and AI agents can understand and act on the issue effectively.
+
+## Contributing Without AI
+
+Traditional contributions are equally welcome! If you prefer to work without AI tools, simply follow the development setup and pull request guidelines below. The issue templates are helpful for any contributor, AI or human.
+
+---
+
+# Contributing
+
+Contributions are welcome and greatly appreciated!
+
+## Getting Started
+
+1. Install from source:
+    ```
+    pip install -e ".[dev]"
+    ```
+
+2. Create a feature branch:
+    ```
+    git checkout -b feature/name-of-your-branch
+    ```
+
+3. Make your changes and run tests:
+    ```
+    python -m pytest test_autoconf/
+    ```
+
+4. Commit, push, and submit a pull request.
+
+### Pull Request Guidelines
+
+1. The pull request should include tests for new functionality.
+2. If the pull request adds functionality, update docs accordingly.
+3. If changing public API, clearly document what changed — downstream packages depend on this.