SPECLAN — Your Specification Is Your Prompt

The missing middle layer between business intent and AI coding agents. Write structured specifications inside VS Code. Hand them to your AI assistant. Ship.

AI coding agents have become remarkably capable — the bottleneck is no longer the agent, it's the input. The better the specification, the better the code. SPECLAN turns loose ideas into structured, traceable specification trees that both humans can read and AI agents can act on. Everything lives as plain Markdown files in your project folder — no database, no server, no lock-in.

Key Capabilities

Three Workflows That Matter

1. From Idea to Spec Tree in Minutes

Describe what you want to build. The AI Generation Wizard decomposes your idea into a full specification hierarchy — requirements, scenarios, acceptance criteria, tests — each as a separate, traceable entity. Skip the blank-page problem. Structure enables AI.

2. Business Writes, Developer Reads — Same File

The WYSIWYG editor makes specification authoring feel like a modern document editor. Bold, italic, tables, task lists — through a familiar toolbar. The Markdown and YAML frontmatter are hidden entirely. A product manager never sees a # or a ---. They just write. The output is clean, standards-compliant Markdown — ready for Git, ready for AI, ready for developers.

3. Tree Views for the Full Picture

Navigate your entire specification hierarchy through dedicated tree views — goals, features, requirements, templates. Drag to reorder. Right-click for context menus. See lifecycle status at a glance with color-coded icons. Git status integration shows what's changed since the last commit.

Two On-Ramps — Start Anywhere

New project? Import a requirements doc. The HLRD Import Assistant takes unstructured stakeholder input and generates a structured specification tree — vision, mission, goals, features, requirements — in minutes.

Existing codebase? Infer specs from code. The Codebase Inference Assistant reads your source and generates draft specifications that describe what the code already does. Finally, your legacy project has proper specs — without anyone writing them from scratch.

Either way, you have structured, AI-ready specifications in minutes — not months.

Three AI Providers. Your Choice.

SPECLAN supports Claude (recommended), Google Gemini, and OpenAI. Choose the model that fits your workflow, your budget, or your organization's policies — and switch between them at any time.

Claude (recommended): If you have a Claude subscription — Max, Pro, or Team — open a terminal in VS Code, run claude login, and every AI feature lights up. No API key. No separate billing. No token budgets. One command and you're done.

# Fastest path to AI-powered specs.
claude login

Google Gemini or OpenAI: Enter your API key in SPECLAN's settings panel, select your preferred model, and every AI feature works the same way — spec generation, requirement decomposition, codebase inference, HLRD import. The specification workflow is provider-agnostic; only the underlying model changes.

No Lock-In. No Paperwork. No Excuses.

Every specification lives as a plain Markdown file with YAML frontmatter in your project's speclan/ directory — right next to src/. The folder structure is the data model.

your-project/
├── src/
└── speclan/
    ├── goals/           G-###-slug.md
    ├── features/        F-####-slug/F-####-slug.md
    │   └── requirements/  R-####-slug/R-####-slug.md
    └── templates/

Stop using SPECLAN tomorrow and your specs remain perfectly readable. No export step. No migration script. No proprietary format. Version them with Git, review them in pull requests, read them on GitHub. Your specifications belong to you.

Quick Start

1. Install SPECLAN from the VS Code Marketplace
2. Set up your AI provider:
   • Claude (recommended): Run claude login in your terminal — done
   • Gemini / OpenAI: Open SPECLAN Settings and enter your API key
3. Open any project folder — SPECLAN detects the speclan/ directory automatically
4. New project: Use the HLRD Import command to generate specs from a requirements document
5. Existing project: Use Codebase Inference to reverse-engineer specs from your source code
6. From scratch: Right-click in the Features tree and create your first feature

Your specification is your prompt. Let's build.

Requirements

• VS Code ^1.80.0
• For AI features, one of:
  • Claude Code CLI with a Claude subscription (Max, Pro, or Team) — recommended, zero-config
  • Google Gemini API key
  • OpenAI API key
• AI features are optional — specification management works without them

Frequently Asked Questions

Do I need an AI subscription to use SPECLAN? No. All specification management features — the domain model, WYSIWYG editor, tree views, lifecycle tracking, templates, Git integration — work without any AI subscription. AI features (generation wizard, HLRD import, codebase inference, implementation assistant) require one of: a Claude subscription, a Google Gemini API key, or an OpenAI API key.

Which AI providers are supported? Three providers: Claude (recommended), Google Gemini, and OpenAI. Claude is the fastest path — run claude login and you're done. For Gemini or OpenAI, enter your API key in SPECLAN's settings panel. All AI features work identically regardless of provider.

Why is Claude the recommended provider? Zero-friction setup. If you have a Claude subscription (Max, Pro, or Team), one terminal command — claude login — activates every AI feature. No API key, no separate billing, no token budgets. But Gemini and OpenAI work just as well if that's what your team uses.

Where are my specifications stored? Everything lives as plain Markdown files with YAML frontmatter in a speclan/ directory inside your project. No database, no server, no proprietary format. You can read, edit, and version them with any tool — Git, GitHub, your favorite text editor.

What happens if I stop using SPECLAN? Nothing. Your specs remain as readable Markdown files. No export step, no migration script. The folder structure is the data model. You keep everything.

Can I use SPECLAN with an existing codebase? Yes. The Codebase Inference Assistant analyzes your source code and generates draft specifications that describe what the code already does. Point it at your project and get structured specs in minutes.

How does SPECLAN work with Git? Specifications are plain files, so they work with Git natively. SPECLAN adds status decorations in tree views, conflict detection on merge, and a sync panel with AI-generated commit messages. Branch, merge, and review specs just like code.

What is the specification hierarchy? Goal → Feature → Requirement → Scenario → Acceptance Criterion → Test. Goals capture business outcomes. Features break down into requirements. Requirements decompose into testable scenarios. Every entity is traceable to its parent.

Can multiple people work on specs at the same time? Yes. Since specs are Git-tracked Markdown files, your team branches, merges, and reviews specifications through the same workflow you use for code. SPECLAN detects merge conflicts and helps resolve them.

What does the 7-status lifecycle do? Every specification moves through: draft → review → approved → in-development → under-test → released → deprecated. This tracks where each requirement stands. Released specs are locked — changes go through a formal change request process to prevent silent spec drift.

Resources

• Documentation & Help — Getting started guides, tutorials, and reference
• speclan.net — Product website
• Report an Issue — Bug reports and feature requests
• Support — support@speclan.net
• Changelog — What's new in each release

License

SPECLAN Proprietary License

SPECLAN — structure your ideas, feed your AI, ship your code.