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Build AI coding assistant configs from a shared prompt library

Project description

prompticorn

A unified, tool-agnostic prompt architecture for managing AI coding-assistant configurations across 5 assistants.

Version: the published version is dynamic. pyproject.toml declares dynamic = ["version"] sourced from prompticorn/__about__.py, and CI/CD injects the real MAJOR.MINOR.PATCH at build time. Local and editable installs report 0.0.0.dev0. Check your installed version with pip show prompticorn.

Define your project's agents, conventions, and personas once, then generate the right config for whichever assistant your team uses:

  • Kilo Code — IDE (.kilo/agents/) and CLI (.opencode/rules/)
  • Cline.clinerules
  • Claude.claude/ directory plus CLAUDE.md
  • Cursor.cursor/rules/ plus .cursorrules
  • GitHub Copilot.github/copilot-instructions.md

What's in the library

  • 25 primary agents (architect, backend, frontend, code, test, debug, security, devops, and more)
  • ~100 workflows in minimal and verbose variants
  • ~95 specialized skills
  • 29 languages with first-class conventions (prompticorn/agents/core/conventions-*.md)

Install

pip install prompticorn
# or
uv add prompticorn

This installs the prompticorn CLI command.

Quick Start

cd your-project
prompticorn init

init is interactive: it asks which assistant to configure, your repository type, prompt variant, personas, language-specific settings, and a set of project questions (database, ORM, error-handling pattern, commit style, PR-size limit, deploy target, and source-tree layout). It then writes .prompticorn/.prompticorn.yaml and generates the assistant's config files.

See docs/QUICKSTART.md for the full walkthrough.

Key Features

  • Unified IR system — define agents once, generate for every supported tool.
  • 5 production builders — Kilo, Cline, Claude, Cursor, Copilot.
  • Minimal / verbose variants — trade tokens for detail at build time.
  • Persona-based filtering — pick your team's roles and only relevant agents are generated.
  • Spec-driven conventions — your language, runtime, package manager, test framework, linter, formatter, coverage targets, and project settings are baked into the generated conventions.
  • Per-language source layouts — the core convention renders each language's standard source tree; flat is the default and src is selectable.
  • Auto-discovery registry — agents are discovered from the bundled agents/ tree; no manual registration.

Commands

Command Description
prompticorn init Interactive setup: pick a tool, answer language and project questions, generate configs.
prompticorn list List discovered agents, their subagents, and prompt variants (live agent discovery).
prompticorn validate Check the agents/ structure: every agent and subagent has the expected prompt files and loads cleanly.
prompticorn switch [tool] Switch to a different assistant, removing old artifacts and regenerating from the saved config.
prompticorn swap Change active personas and regenerate configs with the new agent set.
prompticorn update Update saved configuration options interactively.

Documentation

Development

git clone https://github.com/snoodleboot-io/prompticorn.git
cd prompticorn

# Install in editable mode (reports version 0.0.0.dev0)
uv pip install -e .

# Run tests with coverage (target ~85%)
uv run pytest

# Mutation testing
uv run mutmut run

# Lint, format, and type-check
uv run ruff check .
uv run ruff format .
uv run pyright

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