social-value

内容来源:README.md(说明文档) · 原始地址 · 查看安装指南

原始内容

Social value

Produce social value data from imported data for our social value report for Islington Council.

Architecture

Runtime Environment

This application runs within the AI coding interface:

  • Application runs via natural language interaction with AI assistant
  • AI assistant is the interface
  • No API keys or separate deployment needed
  • Skills provide capabilities
  • Simple file-based storage (JSON, CSV, etc.)

Technical Stack

  • Language: Python
  • Documentation: British English
  • Commits: Conventional Commits specification

Project Structure

project/
├── AGENTS.md            # Project conventions and session bootstrap
├── README.md            # This file
├── CLAUDE.md            # Claude Code auto-load redirect (optional)
├── skills/              # Reusable AI capabilities
│   ├── spec.md         # Creates project specifications
│   └── commit.md       # Formats commit messages
└── [project files]      # Your application code

Getting Started

Session Bootstrap

To start working with this project in any AI coding assistant:

Codex CLI: AGENTS.md loads automatically - just start working Claude Code: Say anything (if CLAUDE.md is set up), or "Read AGENTS.md" Other tools: Say "Read AGENTS.md"

Available Skills

Current skills in skills/ directory:

  • spec - Create project specifications
  • commit - Format commit messages following Conventional Commits
  • refactor - Analyse Python code for refactoring opportunities and quality issues
  • social-value-report - Generate the social value report from anonymised CSV data

Global skills in ~/.skills/ directory:

  • anonymise - Strip PII from CSVs and timestamp outputs

Configuration files

  • ~/.skills/anonymise/config.txt – column headers to remove during anonymisation (one per line, # for comments)
  • skills/social-value-report/config.json – mapping from report fields to CSV column headers (defaults prefer aim 2, fall back to aim 1)

To add more skills, create skills/skillname.md with YAML frontmatter and instructions.

Development Workflow

Spec-First Development

  1. Start with problem statement
  2. Create specification (what the system does)
  3. Define user stories (features from user perspective)
  4. Implement iteratively, one story at a time
  5. Use conventional commits for clean history

Creating Skills

Skills are markdown files with YAML frontmatter:

---
name: skill-name
description: When to use this skill. AI uses this to auto-activate.
---

# Skill instructions here

Simple skills go in skills/skillname.md. Complex skills with supporting files go in skills/skillname/SKILL.md.

Platform Agnostic

This project works with:

  • Claude Code
  • Codex CLI (OpenAI)
  • Gemini CLI (Google)
  • Cursor
  • Aider
  • GitHub Copilot CLI
  • Any future AI coding assistant

Skills and AGENTS.md are plain markdown - no vendor lock-in.

References


For detailed conventions, coding standards, and session bootstrap process, see AGENTS.md.