# Sssf

Super Simple Software Factory, deploy and operate repeatable agents+code workflows...

- Repository: https://github.com/disler/super-simple-software-factory (1026 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-08-04
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add disler/super-simple-software-factory --skill sssf -g -a claude-code -y`
Codex: `npx skills add disler/super-simple-software-factory --skill sssf -g -a codex -y`
Cursor: `npx skills add disler/super-simple-software-factory --skill sssf -g -a cursor -y`
Gemini CLI: `npx skills add disler/super-simple-software-factory --skill sssf -g -a gemini-cli -y`

## Description

Super Simple Software Factory, deploy and operate repeatable agents+code workflows (ADWs) in any codebase. Use when the user says /sssf install, wants to create/run/update an ADW, manage the agent roster in sssf.config.yaml, or observe running agent workflows. Keywords - sssf, software factory, ADW, AI developer workflow, agent pipeline, install factory.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Super Simple Software Factory (SSSF)

Reusable combination of **agents plus code**: deterministic Python ADW scripts own sequencing, retries, and acceptance; coding agents (Pi in v1) work inside bounded phases; typed JSON envelopes carry context between them; everything streams into SQLite for the polled visualizer. Agent proposes, code disposes.

## Startup

Three steps. Then stop.

1. Read [cookbooks/sssf_overview.md](cookbooks/sssf_overview.md), the system map.
2. `ls adws/adw_*.py` and read each file's `Phases:` docstring line.
3. Print the ADWs as a table, name, the chain, one line on when to reach for it, and **wait for the engineer's request.**

```
| ADW | Chain | Use when |
|---|---|---|
| adw_scout | engineer → scout | read-only recon; nothing changes |
| adw_simple_sdlc | plan → build → test → review → document, 3 commits | the work is real and its shape is not obvious |
```

**Nothing else.** No trace-db queries, no reading the config or the ADW scripts' bodies, no repo inventory, no last-runs summary, no diagnosing an old failure, no "current state" dashboard. None of it was asked for, and it is not free:

- **Volunteered state is guessed state.** An orchestrator that improvised a status board queried a `runs` table and a `payload` column, neither exists (`sessions`, `payload_json`). The spec that would have said so is `references/observability.md`, one lazy read away. Probing to look prepared is how you end up confidently wrong in your first message.
- **It spends the context the real task needs**, before you know what the task is.
- **It is stale on arrival.** State printed before the request describes a system that the very next run changes.

Everything else, the db schema, the roster, the handoff contract, is lazy-loaded through the routing table below, when a request actually calls for it. Reading it early defeats the mechanism.

The rest: https://github.com/disler/super-simple-software-factory/blob/HEAD/.claude/skills/sssf/SKILL.md