<skills_system priority="1">
When users ask to perform tasks, check if any of the available skills below can help complete the task more effectively. Skills provide specialized capabilities and domain knowledge.How to use skills:
- Invoke:
npx openskills read <skill-name>(run in your shell)- For multiple:
npx openskills read skill-one,skill-two
- For multiple:
- The skill content will load with detailed instructions on how to complete the task
- Base directory provided in output for resolving bundled resources (references/, scripts/, assets/)
Usage notes:
- Only use skills listed in <available_skills> below
- Do not invoke a skill that is already loaded in your context
- Each skill invocation is stateless
<available_skills>
prompts-writing Create, refine, and optimize high-quality YAML prompts for AI assistants. Use when working with prompt templates, system prompts, agent prompts, or any prompt engineering tasks. Provides structure guidelines, template patterns, and quality standards for YAML-based prompts. project skill-creator Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations. project</available_skills>
</skills_system>
Nexent is a zero-code platform for auto-generating AI agents. Monorepo with:
backend/- FastAPI HTTP APIsdk/nexent/- Core agent framework (pip package)frontend/- Next.js web UIdocker/&k8s/- Deployment configs
# Setup
cd backend && uv sync --extra data-process --extra test
# Install SDK for development
cd backend && uv pip install -e "../sdk[dev]"# From project root, with backend venv activated
source backend/.venv/bin/activate && python test/run_all_test.py
# Single test file
pytest test/backend/apps/test_agent_app.py -vcd frontend
npm run dev # Development server
npm run check-all # type-check + lint + format + buildcd docker
cp deploy/env/.env.example deploy/env/.env # Fill required configs
bash deploy.sh # Interactive deploymentSingle source of truth: backend/consts/const.py
- NO direct
os.getenv()/os.environ.get()outside this file - SDK (
sdk/nexent/) NEVER reads env vars - accepts config via parameters - Services read from
consts.constand pass to SDK
| Layer | Path | Responsibility |
|---|---|---|
| Apps | backend/apps/ |
HTTP boundary: parse input, call services, map exceptions to HTTP |
| Services | backend/services/ |
Business logic orchestration, raise domain exceptions |
| Consts | backend/consts/ |
Env vars (const.py), exceptions (exceptions.py), error codes |
Exception flow: Services raise domain exceptions → Apps map to HTTP status codes
Location: docker/sql/*.sql (versioned migration scripts)
Critical rule: When adding columns/tables via migration script:
- Update
docker/init.sql(Docker Compose fresh deploy) - Update
k8s/helm/nexent/charts/nexent-common/files/init.sql(K8s fresh deploy)
Version: Tracked in backend/consts/const.py as APP_VERSION
- pytest only (no unittest)
- Mock at import site with fully-qualified path:
mocker.patch("backend.services.agent_service.AgentService.run", return_value={...})
- Async tests:
@pytest.mark.asyncio - Test structure:
test/backend/andtest/sdk/
- English-only comments and docstrings (enforced by
.cursor/rules/english_comments.mdc) - Import order: stdlib → third-party → project
- Line length: 119 (sdk ruff config)
| File | Purpose |
|---|---|
backend/consts/const.py |
All env var definitions, APP_VERSION |
backend/consts/exceptions.py |
Domain exceptions (AgentRunException, LimitExceededError, etc.) |
docker/init.sql |
Database schema for Docker Compose |
k8s/helm/.../init.sql |
Database schema for Kubernetes |
test/run_all_test.py |
Test runner with coverage |
Existing instruction files with detailed rules:
CLAUDE.md- Backend architecture, env var management, app/service layer rules.cursor/rules/environment_variable.mdc- Env var centralization.cursor/rules/pytest_unit_test_rules.mdc- Testing patterns.cursor/rules/english_comments.mdc- Comment language enforcement