TORCH/docs/proposals/prompt-packages.md

Roadmap: Project-Type Specific Prompt Packages

Context

Torch currently provides a comprehensive set of agents for repository maintenance, but many of them are implicitly tailored to the Torch repository itself (e.g., specific folder structures like /workspace/TORCH, specific tools). As Torch aims to be a generalized tool for any project, it needs a way to provide relevant agents without forcing every project to use the same structure or stack.

Proposal

Implement Project-Type Specific Prompt Packages. During initialization (torch init), users should be able to select the type of project they are building, and Torch will install a curated set of agent prompts relevant to that project type.

Goals

1. Relevance: Only install agents that make sense for the project (e.g., don't install a React component auditor for a Python backend).
2. Reduced Noise: Avoid cluttering the src/prompts/ directory with irrelevant files.
3. Faster Onboarding: Provide immediate value by giving users agents that "understand" their stack out of the box.

Proposed Packages

We can categorize projects into "Archetypes" or "Packages":

1. The "Base" Package (Core)

• Description: Agents every project needs.
• Included Agents:
  • log-fixer-agent: Monitor task logs for failures.
  • prompt-maintenance-agent: Ensure prompts are valid.
  • todo-triage-agent: Manage TODOs.
  • changelog-agent: Generate changelogs based on commits.

2. The "Node.js Backend" Package

• Description: For server-side JavaScript/TypeScript applications.
• Included Agents:
  • deps-security-agent: Check npm audit.
  • api-schema-validator-agent: Validate OpenAPI/Swagger specs.
  • express-route-auditor-agent: Check for common Express.js pitfalls.
  • db-migration-agent: Check for pending database migrations (e.g., Knex, Prisma).

3. The "React Frontend" Package

• Description: For client-side React applications.
• Included Agents:
  • component-audit-agent: Check for large components, prop drilling.
  • accessibility-agent: Check for ARIA attributes, image alts.
  • unused-component-agent: Find components not imported anywhere.
  • bundle-size-agent: Monitor build artifacts size.

4. The "Library / Tool" Package

• Description: For NPM packages or CLI tools intended for distribution.
• Included Agents:
  • semantic-version-agent: Ensure versioning follows SemVer.
  • api-docs-agent: Generate documentation from JSDoc/TSDoc.
  • compatibility-agent: Check engines field in package.json.

5. The "Python / Django" Package (Future)

• Description: Expanding beyond Node.js.
• Included Agents:
  • pip-audit-agent: Check Python dependencies.
  • django-migration-agent: Check Django migrations.
  • flake8-agent: Python linting.

Implementation Strategy

1. Directory Structure: Organise src/prompts/ into subdirectories for packages, or use a central registry.

   src/prompts/
     ├── core/
     ├── node-backend/
     ├── react-frontend/
     └── library/
   

2. CLI Update: Update torch init to ask:

   "What type of project is this?" [ ] Generic / Custom [ ] Node.js Backend [ ] React Frontend [ ] Library / Tool

3. Configuration: Store the selected package(s) in torch-config.json.

   {
     "projectType": ["node-backend", "react-frontend"],
     "installedPackages": ["core", "node-backend"]
   }
   

4. Dynamic Roster: The roster.json could be dynamically generated based on installed packages, or simply include all installed agents.

Success Metrics

• Reduction in users deleting/ignoring irrelevant agents.
• Increase in successful agent runs (due to better alignment with project structure).
• Positive user feedback on "magic" setup experience.