cursor-rules

A project rule describing an automated software-development process. It coordinates separate agents through stages such as discovery, design, coding, testing, security, and operations.

In plain words
What is it for?
Running a full software project from initial problem discovery through production and, when needed, retirement.
Why use it?
It gives AI agents a defined order of work, shared session notes, and quality checks between stages.

Cursor rule

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add rules/bitbitcodes/autonomous-sdlc/cursor-rules
Clone the repo
git clone --depth 1 https://github.com/bitbitcodes/autonomous-sdlc
Per session 306 This file is loaded in full into every session.
When invoked 306 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00306 $0.00306
Opus 5 $0.00153 $0.00153
Sonnet 5 $0.00061 $0.00061
Haiku 4.5 $0.00031 $0.00031

Measured 2d ago against content hash 1a293c21fb03, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cursor-rules scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

templates/cursor-rules.mdc · 35 lines

What it actually says

Autonomous SDLC Framework

This project uses the Autonomous SDLC Framework for AI-driven development. 52 agents execute the full software development lifecycle autonomously.

Full instructions are in .sdlc/framework/agents/orchestrator.md. This file is the concise summary Cursor loads at startup.

Priority Reading Order

  1. AGENTS.md — Agent discovery and registry
  2. .sdlc/CONTINUITY.md — Current session state (working memory)
  3. .sdlc/state/orchestrator.json — Phase progress

How to Operate

  • Read .sdlc/framework/agents/orchestrator.md for full orchestrator instructions
  • Follow the RARV cycle: Reason → Act → Reflect → Verify
  • Read CONTINUITY.md at the start of every turn
  • Update CONTINUITY.md at the end of every turn
  • Execute phases sequentially, dispatch subagents as needed
  • Enforce quality gates before phase transitions

Agent Prompts Location

  • Orchestrator: .sdlc/framework/agents/orchestrator.md
  • Stage agents: .sdlc/framework/agents/stage/*.md
  • Subagents: .sdlc/framework/agents/sub/**/*.md
  • References: .sdlc/framework/references/*.md
  • Skills: .sdlc/framework/skills/*.md
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 35 lines · 306 tokens per session scan A 1a293c21fb03

Subscribe to this mod's changes

cursor-rules is a cursor rule published in the GitHub repository bitbitcodes/autonomous-sdlc (36 stars, last pushed 1mo ago), licensed MIT. It adds 306 tokens to every session, about $0.0015 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.