a7728c6266
- Security: input validation, SQL injection, auth annotations, secrets, CVE checks - Architecture: API contract first, service boundaries, breaking change protocol - DevOps: health checks, structured logging, resource limits, rollback safety - Cost: resource tagging, auto-scaling limits, storage lifecycle - Deterministic compliance checker (.tests/check.sh) - Agent skill for context injection (Cursor, OpenSpec, Claude Code examples) - Demo with intentional violations
34 lines
1.5 KiB
Markdown
34 lines
1.5 KiB
Markdown
# AI SDLC Standards
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Cross-cutting non-functional requirements for AI-assisted software development.
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## Structure
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```
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security/ — InfoSec requirements (owned by Security team)
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architecture/ — Software architecture standards (owned by Architecture team)
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devops/ — CI/CD and deployment requirements (owned by DevOps team)
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cost/ — Cost attribution and resource tagging (owned by FinOps team)
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.tests/ — Deterministic compliance checks
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skill/ — Agent skill for context injection
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```
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## How It Works
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1. Each folder contains **testable requirements** in markdown — specific rules an AI agent (or human) must follow.
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2. The **skill** teaches your AI agent where to find these requirements and when to apply them.
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3. **Deterministic tests** in `.tests/` validate compliance at CI time — fast, free, no LLM needed.
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4. Each folder has an `OWNERS` file. That team maintains and evolves their requirements.
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## Philosophy
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- **Standardize the input, not the tool.** Use OpenSpec, BMad, Cursor rules, or anything else. These requirements feed into whatever workflow you already have.
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- **Progressive enforcement.** Start informational. Graduate to blocking as requirements mature.
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- **Concrete over aspirational.** Every requirement must be testable. If you can't write a check for it, it's not a requirement — it's a wish.
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## Getting Started
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Plug the skill into your AI agent's configuration. It will pull the right requirements at the right phase of development.
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See `skill/SKILL.md` for integration instructions.
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