102f593909
config.yaml: new repo-root config file with docs_folders list (docs, documentation, doc). apply.sh reads this list and picks the first existing folder per project instead of hardcoding docs/. Instructions: - core-principles: add No Vibe Coding and No Touching .ai/ sections - ai-root-instructions: add mandatory instructions block — rules stay active for the whole session, not just at start; AI must stop and announce if instructions were not loaded - project-context, docs: updated to list all docs folder alternatives and reference config.yaml as the source of truth FR-5.0 added to apply-requirements.md. README step 4 updated.
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Project Context
How to Load Project Context
This file does not contain project-specific information.
Each project maintains its own context document. When working in a project, search for ai-context.md in the following folders (in order):
docs/ai-context.md
documentation/ai-context.md
doc/ai-context.md
These are the standard alternatives defined in ai-superpower/config.yaml. Use whichever folder exists in the project. If multiple exist (unlikely), prefer the first in the list above.
Also look for architecture.md in the same folder:
docs/architecture.md
documentation/architecture.md
doc/architecture.md
This file contains everything you need to understand the project:
- Architecture overview
- Repository structure
- Key technical decisions
- Infrastructure and platforms
- Common debugging patterns
If ai-context.md Does Not Exist
Tell the user:
"This project does not have an
ai-context.mdfile. Would you like me to create a template?"
Place it in the project's existing documentation folder (docs/, documentation/, doc/, etc.). If no documentation folder exists, use docs/.
Template Structure for ai-context.md
When creating a new context file, use this structure:
# AI Context: [Project Name]
**Updated**: YYYY-MM-DD
## Project Overview
[Short description — what does this project do?]
## Architecture
[Key components and how they connect]
## Repository Structure
[Most important directories and files]
## Key Technical Decisions
[Things the AI must know to avoid bad suggestions]
## Common Commands
[Build, run, test, deploy]
## Debugging Patterns
[How to diagnose common issues]
## What NOT to Do
[Project-specific pitfalls]