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sample-specship
SpecShip is an autonomous engineering workflow that orchestrates AI agents through a recon→plan→build→validate→ship pipeline with TDD, parallel execution, adversarial validation, and spec-driven quality gates.
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2026-07-13
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FR-AI / ANALYSISWhy it is worth attention
It introduces a structured, contract-first approach to AI-driven software development with built-in testing, validation, and self-healing, aiming to produce more reliable and complete code than typical AI agents.
Who it is for
- AI-assisted software developers
- Engineering teams exploring autonomous development
- Developers working on brownfield projects
- Quality-focused teams wanting rigorous validation
Use cases
- Rapidly building prototypes with TDD and validation
- Reverse engineering and extending existing codebases
- Automating full feature development from requirements to PR
- Enforcing quality gates in AI-generated code
Strengths
- Test-Driven Development enforced at every milestone
- Parallel execution of independent tasks and validators for speed
- Adversarial validation where different agents judge the code
- Brownfield reverse engineering before planning for existing repos
Considerations
- Requires Kiro agent infrastructure (superpowers + gstack)
- Experimental and has not undergone external security review
- Generated code requires AppSec review before production use
- Dependency on Playwright MCP for browser validation
README quick start
SpecShip
A Kiro Power autonomous engineering workflow that orchestrates AI agents through a complete recon → plan → build → validate → ship pipeline — with brownfield reverse engineering, TDD, parallel execution, adversarial validation, and spec-driven quality gates.
Architecture
Editable source: docs/architecture-diagram.svg
The 4 Phases (+ Brownfield Recon)
| Phase | What happens | Output |
|---|---|---|
| RECON (brownfield only) | Reverse engineer existing code before planning: repo map, technology stack, components, APIs, data models, business flows, baseline tests, preserved behavior, and change impact. | .specship/.../artifacts/reverse-engineering/ |
| PLAN | Brainstorm → market research (real web search, minimum 5 queries) → sprint contract → pre-generate test cases → implementation plan. Each step feeds the next. | requirements.md + design.md + tasks.md + artifacts |
| BUILD | Execute tasks.md milestone-by-milestone. Parallel batches for independent tasks. Every behavior follows Test-Driven Development (write failing test → watch it fail → implement → pass → commit). Hard gate blocks each milestone until typecheck + tests + build pass. | Tested, committed code per milestone |
| VALIDATE | Up to 7 adversarial validators run in parallel as independent subagents, each delegating to its gstack specialist skill (code→review, security→cso, browser→qa-only). Code, Security, Integration, Browser, Design, Alignment (always) + Load (if performance NFR exists). Each produces a typed verdict with evidence. Aggregate decides: merge / recover / escalate. | Typed verdicts → merge or recover |
| SHIP | PR + changelog + archive. Ship report with timing, bugs caught, milestone breakdown. If no git remote, prepares locally with push instructions. | PR ready to merge |
Why SpecShip?
AI agents build fast but shallow — working skeleton in 7 minutes, 60% of features missing, no tests, no error handling. SpecShip fixes this:
| Principle | What it means |
|---|---|
| Test-Driven Development | No production code without a failing test first. The build gate blocks every milestone until typecheck + tests + build all pass. Catches bugs within minutes, not hours. |
| Parallel execution | Independent tasks run simultaneously. A |
Description
Spec-driven autonomous engineering workflow for AI coding agents: recon → plan → build → validate → ship — with TDD, adversarial validation, and anti-slop quality gates. Packaged as a Kiro Power.
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