digitaldemocracy2030/kouchou-ai/kouchou-ai-architecture

Claude Code and agent skill by digitaldemocracy2030/kouchou-ai

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Project architecture, core services, key directories, data flow, and tech stack for the kouchou-ai repository. Use when you need an overview of components, pipeline structure, or where code lives.

Install

npx vskill@latest install digitaldemocracy2030/kouchou-ai/kouchou-ai-architecture

SKILL.md

Kouchou-AI Architecture

Overview

Use this skill to orient yourself in the repo and explain how the system fits together. Remember that Kouchou-AI is a broadlistening system for the Digital Democracy 2030 project, adapted from Talk to the City for Japanese municipal use cases.

Core services and ports

  • Locate the API (FastAPI) in apps/api/ and expect it on port 8000.
  • Locate the public viewer (Next.js) in apps/public-viewer/ and expect it on port 3000.
  • Locate the admin app (Next.js) in apps/admin/ and expect it on port 4000.
  • Locate the static site builder in apps/static-site-builder/ and expect it on port 3200.
  • Expect the optional Ollama service on port 11434 for local LLM usage.
  • Expect Ollama to use the ELYZA-JP model by default.

Key directories

  • Use packages/analysis-core/src/analysis_core/ for analysis steps, orchestration, services, and workflows.
  • Use apps/api/broadlistening/pipeline/ for runtime configs, inputs, and outputs managed by the API.
  • Use apps/public-viewer/components/charts/ and apps/public-viewer/components/report/ for report UI and charts.
  • Use apps/admin/app/create/ and apps/admin/app/create/hooks/ for report creation UI.
  • Use apps/api/src/routers/, apps/api/src/services/, apps/api/src/schemas/, and apps/api/src/repositories/ for API layers.

Pipeline architecture and report flow

  • Follow the flow: CSV upload -> API validation -> pipeline run -> hierarchical output -> public viewer.
  • Start API-side orchestration at apps/api/src/services/report_launcher.py.
  • Start CLI-side orchestration at packages/analysis-core/src/analysis_core/__main__.py and packages/analysis-core/src/analysis_core/orchestrator.py.
  • Expect API-managed outputs under apps/api/broadlistening/pipeline/outputs/{report_id}/.

Technology stack

  • Treat the backend as FastAPI + OpenAI GPT models + sentence-transformers + pandas/numpy/scipy.
  • Treat the frontend as Next.js 15 + TypeScript + Chakra UI + Plotly.js.
  • Use pytest, Jest, and Playwright for testing.
  • Use Biome (frontend) and Ruff (backend) for linting and formatting.
  • Expect Azure Blob Storage support for storage needs.
  • Use Lefthook for Git hooks (pre-push) as configured in lefthook.yml.

Configuration pointers

  • Check biome.json, apps/api/pyproject.toml, lefthook.yml, and .env.example for core config.

Operational notes

  • Require an OpenAI API key or local LLM for full pipeline runs.
  • Validate LLM output for bias before acting on results.
  • Back up report data before upgrading or applying breaking changes.
  • Expect breaking changes between versions.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
162
Repository forks
60
7-day trend score
25

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 20 Mar 2026, 7 months ago.

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