Meta-Spec AI Agent Guide

For AI Assistants: This document provides guidance on using Meta-Spec to generate Spec-Driven X (SD-X) speckits.

🎯 Your Role

You are helping a developer create speckits (spec-driven toolkits for AI agents) using MetaSpec.

MetaSpec is a meta-specification framework that generates complete Spec-Driven X (SD-X) speckits:

SD-Development - Spec-driven development
SD-Design - Spec-driven design systems
SD-Testing - Spec-driven testing frameworks
SD-Documentation - Spec-driven documentation
SD-Operations - Spec-driven operations
SD-X - Spec-driven generation for any domain

Key principle: MetaSpec generates production-ready speckits with CLI, parser, validator, templates, and AI agent support

💡 Core Concept: Meta-Specification Framework

MetaSpec is a meta-specification framework - it uses specifications to generate specification toolkits.

Meta-Specification (MetaSpec)
        ↓
  Defines how to define specifications
        ↓
Generates Speckits (Spec-driven Toolkits)
        ↓
Speckits carry domain specifications
        ↓
Used to develop domain projects

Key Insights

Meta-level abstraction - MetaSpec defines how to create specification systems
Generative framework - Generates complete speckits from meta-specifications
Recursive architecture - MetaSpec uses SDD to develop itself, generates speckits that use SDD
Specification-centric - Domain specs are the source of truth, speckits are carriers

Example Flow:

MetaSpec (meta-spec)
    ↓ generates
MCP-Spec-Kit (carries MCP specification spec)
    ↓ used by
Developer (validates MCP servers against spec)

This means: MetaSpec is not just "spec-driven development" - it's a framework that generates speckits (spec-driven toolkits) for any domain.

See Recommended Practice: SDS + SDD Separation in MetaSpec Commands section for how speckits separate domain specifications from toolkit implementation.

📋 CLI Commands

MetaSpec provides these commands:

metaspec init [name] - Create speckit (interactive or template-based)
metaspec search <query> - Search community speckits
metaspec install <name> - Install from community
metaspec contribute <name> - Contribute to community
metaspec list - List installed speckits
metaspec info <name> - Show speckit information

Use these commands in your workflow to help users create and discover speckits.

🔒 Constitutional Principles

ALWAYS follow memory/constitution.md which defines:

Core principles for meta-spec definitions
Quality standards for generated systems
Prohibited patterns
Required patterns

Constitution Structure

The constitution is organized into three parts:

memory/constitution.md
├── Part I: Project Core Values (Managed by: /speckit.constitution)
│   - AI-First Design
│   - Progressive Enhancement
│   - Minimal Viable Abstraction
│   - Domain Specificity
│
├── Part II: Specification Design Principles (Managed by: /metaspec.sds.constitution)
│   - Entity Clarity
│   - Validation Completeness
│   - Operation Semantics
│   - Implementation Neutrality
│   - Extensibility Design
│   - Domain Fidelity
│   - Workflow Completeness ⭐ NEW
│
└── Part III: Toolkit Implementation Principles (Managed by: /metaspec.sdd.constitution)
    - Entity-First Design
    - Validator Extensibility
    - Spec-First Development
    - AI-Agent Friendly
    - Progressive Enhancement
    - Automated Quality

Key principles:

Minimal Viable Abstraction (Part I): Don't over-abstract
AI-First Design (Part I): Generated systems must be AI-friendly
Progressive Enhancement (Part I): Start with MVP, add features incrementally
Domain Specificity (Part I): Respect domain constraints
Workflow Completeness (Part II): ⭐ NEW - Define complete user workflows, not just isolated operations

🚀 Workflow-Driven Design Philosophy

CRITICAL NEW PRINCIPLE (v0.7.0+): MetaSpec now requires workflow-first design for all domain specifications.

Two Types of Workflows ⭐ UPDATED v0.8.0

IMPORTANT: There are TWO types of workflows in specifications. Understanding the distinction is critical.

Type 1: Entity State Machines (Business Execution)

What: Lifecycle of individual entities during business operations
Example: Order (pending → confirmed → shipped → delivered)
Used by: Business logic, domain operations
Defines: Status field transitions, business rules

Order Entity:
  status: [pending, confirmed, shipped, delivered]
  transitions:
    - pending → confirmed (when: payment verified)
    - confirmed → shipped (when: items packed)
    - shipped → delivered (when: customer receives)

Type 2: Specification Usage Workflow (Specification Creation) ⭐ NEW

What: End-to-end process of creating and using the specification itself
Example: SDS Workflow (Constitution → Specify → Clarify → ... → Implement)
Used by: Users creating specifications, AI agents
Defines: Action steps, slash commands, quality gates

SDS Workflow:
  Step 1: Constitution → /metaspec.sds.constitution
  Step 2: Specify → /metaspec.sds.specify
  Step 3: Clarify → /metaspec.sds.clarify
  ...
  Step 8: Implement → /metaspec.sds.implement

Key Distinction:

Type 1: How entities change during business execution (WHAT happens)
Type 2: How to create/use/validate the specification (HOW to use speckit)

Most speckits need BOTH:

Type 1: Define entity lifecycles (if domain has stateful entities)
Type 2: Required for all Speckits - Define specification creation workflow

Why Workflow Matters

❌ Don't build: "Toolbox" (collection of isolated operations)
✅ Do build: "Workflow Systems" (integrated end-to-end user journeys)

The Problem We Solved

Before v0.7.0: Developers could create speckits that passed all quality checks but lacked clear user workflows. Users received "13 commands" without knowing which to use first, or how they relate.

After v0.7.0: All domain specifications MUST define:

Workflow Phases - Distinct stages in the user journey (Type 2)
Phase Purposes - Why each phase exists
Operation Mapping - Which operations belong to which phase
Sequencing - Entry/exit criteria, dependencies, ordering
End-to-End Examples - Complete workflow demonstrations
Entity State Machines - If domain has stateful entities (Type 1)

MetaSpec as Example

MetaSpec itself demonstrates perfect workflow design:

SDS Workflow:
  Phase 1: Constitution → /metaspec.sds.constitution
  Phase 2: Specification → /metaspec.sds.specify
  Phase 3: Quality Gates → /metaspec.sds.clarify, /metaspec.sds.checklist
  Phase 4: Implementation → /metaspec.sds.plan, /metaspec.sds.tasks, /metaspec.sds.implement
  Phase 5: Validation → /metaspec.sds.analyze

SDD Workflow:
  Phase 1: Constitution → /metaspec.sdd.constitution
  Phase 2: Specification → /metaspec.sdd.specify, /metaspec.sdd.clarify
  Phase 3: Architecture → /metaspec.sdd.plan, /metaspec.sdd.checklist
  Phase 4: Implementation → /metaspec.sdd.tasks, /metaspec.sdd.analyze, /metaspec.sdd.implement

Your mission: Ensure all speckits you help create follow this same pattern.

Required Workflow Elements

When defining domain specifications, ALWAYS include:

Phase Definitions

Phase 1: [Name]
  Purpose: [Why this phase exists]
  Entry: [When user enters]
  Operations: [Which operations]
  Outputs: [What is produced]
  Exit: [When complete]

Operation-to-Phase Mapping
- Every operation MUST belong to at least one workflow phase
- No "orphan" operations without clear usage context
Workflow Examples
- Show complete end-to-end usage
- Demonstrate phase transitions
- Include success indicators
Decision Points
- Document when users choose between paths
- Explain branching logic
- Provide decision criteria

Enforcement

The new Part II Principle 7: Workflow Completeness ensures:

/metaspec.sds.constitution includes workflow requirements
/metaspec.sds.specify generates Workflow Specification sections
/metaspec.sds.checklist (future) validates workflow completeness
/metaspec.sds.analyze (future) scores workflow quality

Examples

Good Workflow-Driven Design (Type 2: Specification Usage Workflow):

MetaSpec SDS Workflow:
  Phase 1: Foundation
    - Operations: /metaspec.sds.constitution
    - Output: Specification design principles
  
  Phase 2: Specification
    - Operations: /metaspec.sds.specify, /metaspec.sds.clarify
    - Output: Domain specification document
  
  Phase 3: Quality Gates
    - Operations: /metaspec.sds.checklist, /metaspec.sds.analyze
    - Output: Quality validation reports
  
  Phase 4: Implementation (if complex)
    - Operations: /metaspec.sds.plan, /metaspec.sds.tasks, /metaspec.sds.implement
    - Output: Sub-specifications

Good Entity State Machine (Type 1: Business Execution):

Specification Entity (MetaSpec itself):
  States: draft → review → approved → deprecated
  Transitions:
    - draft → review (when: ready for feedback)
    - review → approved (when: quality checks pass)
    - approved → deprecated (when: replaced by new version)

Bad (Pre-v0.7.0) Design:

Specification Operations (no workflow):
  - /spec.create (what's this for?)
  - /spec.validate (when to use?)
  - /spec.analyze (how does this relate to create?)
  ❌ Users confused about sequence and relationships

Your Checklist

When helping users create speckits, verify:

Type 2: Specification Usage Workflow (Required for all speckits):

Domain specification includes "Specification Usage Workflow" section
Workflow has 8-12 action steps (Constitution → Specify → ... → Implement)
Each step maps 1:1 to a slash command
Each step has clear goal, inputs, outputs, quality criteria
End-to-end workflow examples provided

Type 1: Entity State Machines (If domain has stateful entities):

Domain specification includes "Entity State Machines" section
Each stateful entity has defined states and transitions
Forbidden transitions are documented
Validation rules for state changes defined

Constitution:

Constitution Part II includes Workflow Completeness principle

🤝 Spec-Driven Development for Speckits

Generated speckits (spec-driven toolkits) include MetaSpec commands in .metaspec/commands/ to assist AI in understanding and generating the speckit.

Speckits are specialized toolkits generated by MetaSpec that:

Carry domain specifications as core assets
Include built-in MetaSpec commands for development
Follow spec-driven architecture patterns

These commands provide a complete workflow from specification definition to controlled evolution (19 commands total: 8 SDS + 8 SDD + 3 Evolution).

See MetaSpec Commands section for the complete command reference.

🎯 MetaSpec Commands: Specification Lifecycle Management

When you generate a speckit, it includes MetaSpec (Spec-Driven X) commands in the .metaspec/commands/ directory. These commands manage the specification lifecycle.

Command Groups

MetaSpec uses a three-layer architecture to separate concerns:

SDS (Spec-Driven Specification) - 8 Commands

For defining domain specifications:

/metaspec.sds.constitution - Update Part II of constitution (Specification Design Principles)
/metaspec.sds.specify - Define specification entities, operations, validation rules
/metaspec.sds.clarify - Clarify underspecified areas (recommended BEFORE plan; input quality gate)
/metaspec.sds.plan - Plan specification architecture and sub-specifications
/metaspec.sds.tasks - Break down specification work
/metaspec.sds.analyze - Cross-artifact consistency check (run AFTER tasks, BEFORE implement; checkpoint)
/metaspec.sds.implement - Write specification documents (creates sub-spec files, NOT code)
/metaspec.sds.checklist - Generate quality checklist (like "unit tests for specifications"; output quality gate)

Location: Works with specs/domain/ directory (stores domain specifications) Constitution: Updates Part II in /memory/constitution.md

🌳 Recursive Tree Structure (NEW)

SDS supports recursive specification hierarchy:

IMPORTANT: Physical structure is FLAT, logical structure is TREE.

Physical Structure (flat directory layout):

specs/domain/
├── 001-order-specification/     # All at same level
├── 002-order-creation/
├── 003-payment-processing/
├── 013-credit-card-payment/     # Same level, not nested
├── 014-digital-wallet-payment/
└── 015-bank-transfer-payment/

Logical Structure (tree via frontmatter):

001-order-specification (root)
  ├── 002-order-creation (leaf)
  ├── 003-payment-processing (parent)
  │   ├── 013-credit-card-payment (leaf)
  │   ├── 014-digital-wallet-payment (leaf)
  │   └── 015-bank-transfer-payment (leaf)
  └── 004-fulfillment (leaf)

Why flat physical structure?

✅ Simple paths: specs/domain/013-credit-card-payment/
✅ FEATURE independence: Each specification is a standalone FEATURE
✅ Flexible numbering: 003's children can be 013-015 (skip 004-012)
✅ Git branch friendly: Branch name = directory name
✅ Easy reorganization: Change parent in frontmatter, no file moves

Key features:

Any specification can be a parent: If complex, run plan → tasks → implement to create sub-specifications
Unlimited depth: Sub-specifications can have their own sub-specifications
Context tracking: Via YAML frontmatter (spec_id, parent, root, type)
Unified commands: Same commands work at all levels

How relationships are maintained:

Physical: All specifications are sibling directories under specs/domain/

Logical: Parent-child relationships declared in YAML frontmatter

---
spec_id: 013-credit-card-payment
parent: 003-payment-processing    # ← Declares logical parent
root: 001-order-specification
type: leaf
---

Parent → Child: Parent's spec.md lists sub-specifications in "Sub-Specifications" table
Child → Parent: Child's spec.md shows "Parent chain" breadcrumb navigation
Benefit: Change relationships by editing frontmatter, no directory restructuring needed

Example workflow (Level 2 splitting):

# At root (001)
/metaspec.sds.specify → 001-order-specification/spec.md
/metaspec.sds.plan → Decides to split
/metaspec.sds.implement → Creates 002-008

# At level 2 (003 is also complex)
cd specs/domain/003-payment-processing/
/metaspec.sds.plan → Decides to split again
/metaspec.sds.implement → Creates 013-015

Numbering strategy:

Root specification starts at 001
First-level children: 002-009 (reserve 001 for root)
Second-level children: 010-099 (e.g., 003's children are 013-015)
Third-level children: 100-999
Benefits: Clear hierarchy, flexible expansion, easy identification

See Recommended Practice: SDS + SDD Separation for specification + toolkit separation.

⚠️ CRITICAL PRINCIPLE: Specification First, Toolkit Second

Every speckit MUST have a domain specification before toolkit development.

Why this matters:

Specification = WHAT (domain specification, core asset)
Toolkit = HOW (implementation, supporting tool)
Without specification, MetaSpec becomes a generic code generator
Spec-Driven means specifications drive development

Workflow:

✅ First: Define specification with /metaspec.sds.specify
✅ Then: Develop toolkit with /metaspec.sdd.specify
❌ Never: Skip specification and go straight to toolkit

Enforcement:

/metaspec.sdd.specify will ERROR if no specification exists
/metaspec.sdd.analyze marks missing specification as CRITICAL
Toolkit specs MUST have Dependencies section referencing specification

🎯 How Toolkit Value is Realized

Toolkit value ≠ Fixed code templates
Toolkit value = Spec-driven code generation

MetaSpec generates working toolkits through a three-stage process:

Stage 1: Define Specification (SDS)

/metaspec.sds.specify
  ↓
specs/domain/001-{domain}-specification/spec.md
  - Entity definitions
  - Validation rules
  - Operations
  - Error handling

Stage 2: Define Toolkit (SDD)

/metaspec.sdd.specify
  ↓
AI guides you to define:
  - Implementation Language: Python / TypeScript / Go / Rust / Other
  - Required Components: Parser / Validator / CLI / Generator / SDK
  - Architecture: Monolithic / Modular / Plugin-based
  ↓
specs/toolkit/001-{name}/spec.md
  - Language choice + rationale
  - Component selection
  - Architecture direction
  - Dependencies on specification

Stage 3: Generate Code (SDD)

/metaspec.sdd.plan
  ↓
AI designs architecture based on:
  - Chosen language (Python/TS/Go/Rust)
  - Required components
  - Specification entities
  ↓
specs/toolkit/001-{name}/plan.md
  - Tech stack for chosen language
  - File structure
  - Component interfaces
  
/metaspec.sdd.implement
  ↓
AI generates code based on:
  - Specification (entity definitions)
  - Toolkit spec (language, components)
  - Plan (architecture, structure)
  ↓
src/{package_name}/
  - models.py/ts/go (from specification entities)
  - parser.py/ts/go (from toolkit spec)
  - validator.py/ts/go (enforces specification rules)
  - cli.py/ts/go (toolkit commands)

Key advantages:

✅ Language-agnostic: Supports Python, TypeScript, Go, Rust
✅ Component-flexible: Generate only what's needed
✅ Architecture-adaptive: Monolithic, modular, or plugin-based
✅ Spec-driven: Code generated from specifications, not templates
✅ Specification-compliant: Generated code enforces specification rules

Example outcome:

$ cd my-speckit
$ /metaspec.sds.specify  # Define domain specification
$ /metaspec.sdd.specify  # Choose Python, Parser+Validator+CLI
$ /metaspec.sdd.plan     # Design Python architecture
$ /metaspec.sdd.implement # Generate code
$ pip install -e .
$ my-speckit --help      # ✅ Working CLI!
$ my-speckit validate spec.yaml  # ✅ Validates against specification!

This is how MetaSpec realizes Toolkit value: not by providing fixed templates, but by generating spec-driven, language-appropriate, working code.

SDD (Spec-Driven Development) - 8 Commands

For developing speckits (spec-driven toolkits):

/metaspec.sdd.constitution - Update Part III of constitution (Toolkit Implementation Principles)
/metaspec.sdd.specify - Define toolkit specifications
/metaspec.sdd.clarify - Clarify technical decisions (recommended BEFORE plan; input quality gate)
/metaspec.sdd.plan - Plan toolkit implementation architecture
/metaspec.sdd.checklist - Validate requirements completeness (recommended AFTER plan; quality gate)
/metaspec.sdd.tasks - Break down implementation work
/metaspec.sdd.analyze - Check architecture consistency (recommended AFTER tasks, BEFORE implement; checkpoint)
/metaspec.sdd.implement - Build toolkit code (write actual implementation)

Workflow: Follows spec-kit pattern completely (toolkit development always needs full process)

constitution → specify → [clarify] → plan → [checklist] → tasks → [analyze] → implement

Location: Works with specs/toolkit/ directory Constitution: Updates Part III in /memory/constitution.md

Evolution - 3 Shared Commands

For controlled specification evolution (both SDS and SDD):

/metaspec.proposal - Propose changes with --type sds|sdd parameter
/metaspec.apply - Apply approved changes
/metaspec.archive - Archive completed changes

Location: Works with changes/ directory (independent from specs/)

The Relationship

MetaSpec commands (19 total):
  - SDS (8 commands)     → Define domain specifications (specs/domain/)
                         → Update constitution Part II
  - SDD (8 commands)     → Develop toolkits (specs/toolkit/)
                         → Update constitution Part III
  - Evolution (3 shared) → Manage changes (changes/)
                              ↓
                    Project structure:
                    ├── memory/
                    │   └── constitution.md  ← Unified constitution (3 parts)
                    ├── specs/
                    │   ├── domain/   ← SDS manages (domain specifications)
                    │   └── toolkit/  ← SDD manages (toolkit implementation)
                    └── changes/      ← Evolution manages (independent)

Key principle:

One unified constitution with three parts
SDS and SDD each manage their respective sections
Clear separation between domain specification and toolkit development

When to Use Which

Use SDS commands (/metaspec.sds.*):

Defining domain specifications from scratch
Specifying specification entities, operations, validation rules
Creating domain specifications independent of implementation
Focus on WHAT the domain specification is

Use SDD commands (/metaspec.sdd.*):

Developing spec-driven toolkits (always uses complete workflow like spec-kit)
Planning and implementing parsers, validators, CLI
Building tools to support a specification
Focus on HOW to implement the toolkit
Unlike SDS, toolkit development always needs full process (no "Simple Path")

Use Evolution commands (/metaspec.*):

Specification is stable and in use (domain specification or toolkit)
Changes need review or approval
Want to track change history
Controlled evolution for both SDS and SDD specs
Use --type sds for specification changes, --type sdd for toolkit changes

Typical workflow:

SDS: Define domain specification
- Simple: /metaspec.sds.specify → /metaspec.sds.checklist
- Complex: /metaspec.sds.specify → /metaspec.sds.plan → /metaspec.sds.tasks → /metaspec.sds.implement
SDD: Develop toolkit (always complete workflow, like spec-kit)
- /metaspec.sdd.specify → /metaspec.sdd.clarify → /metaspec.sdd.plan → /metaspec.sdd.checklist → /metaspec.sdd.tasks → /metaspec.sdd.analyze → /metaspec.sdd.implement
Evolution: Manage changes to either specification or toolkit
- /metaspec.proposal --type sds|sdd

Recommended Practice: SDS + SDD Separation

When using MetaSpec to develop a speckit, follow this two-phase approach:

Phase 1: Domain Specification (SDS)

Purpose: Define the domain specification, rules, and standards

Location: specs/domain/001-{domain}-specification/

What to include:

Domain entities and schemas
Validation rules and constraints
Operations and interfaces
Error handling specifications

Example:

# specs/domain/001-mcp-core-specification/spec.md

## MCP Specification

### Server Interface
- initialize: Server startup handshake
- tools/list: Enumerate available tools
- tools/call: Execute a specific tool

### Validation Rules
- Tool name must be unique
- inputSchema must be valid JSON Schema

Key principle: This is pure domain knowledge, independent of any speckit implementation.

Phase 2: Toolkit Specification (SDD)

Purpose: Define how to build tools to parse, validate, and enforce the specification

Location: specs/toolkit/001-{name}/

What to include:

Explicit dependency on domain specifications
User Journey Analysis (🆕 From Step 2.5)
- Primary users (AI Agents vs Human Developers distribution)
- Key usage scenarios (3-5 scenarios with User/Context/Goal/Pain Point)
- Feature derivation from scenarios (P0/P1/P2 priority matrix)
- Command design rationale (why each command exists)
- Scenario coverage matrix
Parser design (input formats)
Validator logic (references specification rules)
CLI commands (init, validate, generate)
Slash Commands (for AI agents)
Templates & Examples (🆕 From Component 6)
- Templates directory structure (organized by specification system source)
- Template mapping (library specs → directories)
- Entity templates (specification entities → template files)
- Examples directory (basic/advanced/use-cases)
- Implementation checklist
Success criteria

Example:

# specs/toolkit/001-mcp-parser/spec.md

## Dependencies
- Depends on: domain/001-mcp-core-spec

## User Journey Analysis
### Primary Users
- 80% AI Agents (Claude in Cursor)
- 20% Human Developers

### Key Scenarios
**Scenario 1**: AI Agent generates MCP server from natural language
- User: AI Agent
- Goal: Generate valid server definition
- Required Features: show-spec command, get-template command, validate CLI

**Scenario 2**: Developer validates server definition manually
- User: Human Developer
- Goal: Verify server compliance
- Required Features: init, validate, docs

### Derived Features (P0)
- Specification reference system: AI needs rules before generating (Scenarios: 1)
- Template system: Users need starting points (Scenarios: 1, 2)
- Validation CLI: Critical for both AI and developers (All scenarios)

### Command Design Rationale
- show-spec: AI needs rules before generating → Scenario 1
- validate: Critical for both AI and developers → All scenarios
- init: Developer quick setup → Scenario 2

## Components
1. Parser: Parse MCP server definitions
2. Validator: Verify compliance with specification
3. CLI: mcp-spec-kit init|validate|generate

## Templates & Examples
### Templates Directory Structure
templates/
├── generic/               # From library/generic
│   ├── commands/
│   └── templates/
├── spec-kit/              # From library/sdd/spec-kit
│   ├── commands/
│   └── templates/
└── mcp/                   # Custom (from domain/001-mcp-spec)
    ├── commands/
    │   ├── show-spec.md
    │   ├── get-template.md
    │   └── validate-server.md
    └── templates/
        ├── basic-server.yaml
        └── advanced-server.yaml

### Examples Directory
examples/
├── basic/
│   ├── simple-server.yaml
│   └── README.md
└── advanced/
    ├── full-featured-server.yaml
    └── README.md

Key principle: Toolkit specs explicitly depend on domain specifications, derive features from user scenarios, and define HOW to implement the toolkit.

MetaSpec Workflow for SDS + SDD

SDS has two workflow paths (like GitHub spec-kit):

Path 1: Simple Specification (Recommended starting point)

Use when: Single specification document, no need to split

# Core Flow (Required)
/metaspec.sds.constitution  # 1. Define specification design principles
/metaspec.sds.specify       # 2. Create specs/domain/001-{domain}-specification/spec.md

# Quality Gates (Recommended)
/metaspec.sds.clarify       # 3. Clarify ambiguities (input quality gate)
/metaspec.sds.checklist     # 4. Final quality validation (output quality gate)

Path 2: Complex Specification (Needs splitting)

Use when: Large specification requiring multiple sub-specifications

# Core Flow (Required)
/metaspec.sds.constitution  # 1. Define specification design principles
/metaspec.sds.specify       # 2. Create root specification

# Quality Gates (Recommended)
/metaspec.sds.clarify       # 3. Clarify ambiguities (BEFORE plan, input quality gate)

# Core Flow (Required) - Continued
/metaspec.sds.plan          # 4. Plan sub-specification architecture ⭐

# Quality Gates (Recommended)
/metaspec.sds.checklist     # 5. Validate requirements (AFTER plan, quality gate)

# Core Flow (Required) - Continued
/metaspec.sds.tasks         # 6. Break down specification tasks ⭐

# Quality Gates (Recommended)
/metaspec.sds.analyze       # 7. Check task consistency (AFTER tasks, checkpoint)

# Core Flow (Required) - Continued
/metaspec.sds.implement     # 8. Write sub-specification documents (NOT code) ⭐

📌 How to choose: Start with Path 1. If /metaspec.sds.specify output shows complexity, run /metaspec.sds.plan to decide if splitting is needed. If yes, switch to Path 2.

Phase 2: Toolkit Specification (SDD)

/metaspec.sdd.constitution # Define toolkit principles /metaspec.sdd.specify # Create specs/toolkit/001-parser/spec.md # Must reference: domain/001-{domain}-spec /metaspec.sdd.plan # Plan toolkit architecture /metaspec.sdd.tasks # Break down implementation /metaspec.sdd.implement # Build src/ code based on toolkit spec /metaspec.sdd.checklist # Validate quality /metaspec.sdd.analyze # Verify toolkit references specification correctly

Evolution: Manage Changes

/metaspec.proposal "Add GraphQL" --type sds # Propose specification change /metaspec.apply add-graphql # Apply approved change /metaspec.archive add-graphql # Archive completed change


#### Why Separate?

1. **Clear separation of concerns**
   - Specification experts define WHAT (SDS)
   - Toolkit experts define HOW (SDD)

2. **Reusable specifications**
   - Domain specifications can be published independently
   - Other tools can reference the same specification

3. **Clean dependencies**
   - Toolkit explicitly depends on specification
   - `/metaspec.sdd.analyze` can verify consistency

4. **Embodies MetaSpec philosophy**
   - Domain specification is the source of truth
   - Toolkit is the carrier

#### When to Use

**Use SDS + SDD Separation** (Recommended):
- Domain has well-defined specifications (MCP, OpenAPI, GraphQL)
- Domain specification can be useful independently
- Multiple toolkit implementations might exist

**Merge SDS and SDD** (Acceptable for simple cases):
- Very simple domain without formal specifications
- Toolkit is the only implementation
- No need for standalone domain specification

### Practical Examples

**Example 1: Starting a new speckit (Simple Specification)**
```bash
cd my-speckit
# Phase 1: Define specification (Simple Path)
/metaspec.sds.constitution  # Define specification design principles
/metaspec.sds.specify "Define domain specification"  # Create specification
/metaspec.sds.clarify  # Clarify ambiguities (recommended)
/metaspec.sds.checklist  # Quality check (recommended)

# Phase 2: Develop toolkit (complete workflow)
/metaspec.sdd.constitution  # Define toolkit principles
/metaspec.sdd.specify "Define parser and validator"  # Toolkit spec
/metaspec.sdd.clarify  # Clarify technical decisions (recommended)
/metaspec.sdd.plan  # Plan architecture
/metaspec.sdd.checklist  # Validate requirements (recommended)
/metaspec.sdd.tasks  # Break down implementation
/metaspec.sdd.analyze  # Check architecture consistency (recommended)
/metaspec.sdd.implement  # Write code

Example 1b: Complex Specification (Needs Splitting)

cd my-speckit
# Phase 1: Define specification (Complex Path)
/metaspec.sds.constitution  # Define specification design principles
/metaspec.sds.specify "Define MCP specification"  # Create root specification
/metaspec.sds.clarify  # Clarify ambiguities (BEFORE plan)
/metaspec.sds.plan  # Plan sub-specification architecture
/metaspec.sds.checklist  # Validate requirements (AFTER plan)
/metaspec.sds.tasks  # Break down specification tasks
/metaspec.sds.analyze  # Check task consistency (BEFORE implement)
/metaspec.sds.implement  # Write sub-specification documents (NOT code)

# Phase 2: Develop toolkit (complete workflow, same as Example 1)
/metaspec.sdd.constitution
/metaspec.sdd.specify "Define parser and validator"
/metaspec.sdd.clarify
/metaspec.sdd.plan
/metaspec.sdd.checklist
/metaspec.sdd.tasks
/metaspec.sdd.analyze
/metaspec.sdd.implement

Example 2: Iterating on specification

# Make changes to specs/domain/001-*/spec.md
/metaspec.sds.clarify  # Resolve ambiguities
/metaspec.sds.checklist  # Validate specification quality
/metaspec.sds.analyze  # Check consistency

Example 3: Implementing toolkit

/metaspec.sdd.tasks  # Break down work
/metaspec.sdd.implement  # Execute tasks
/metaspec.sdd.checklist  # Validate quality

Example 4: Controlled evolution

# For stable specification or toolkit
/metaspec.proposal "Add GraphQL support" --type sds  # Specification change
# Review and approve
/metaspec.apply <proposal-id>
/metaspec.archive <proposal-id>

🧭 Token Optimization: Precision-Guided Navigation

NEW in v0.5.4+: Major MetaSpec commands now include precision-guided navigation with exact line numbers, enabling massive token savings (84-99%).

What is Precision-Guided Navigation?

Instead of reading entire command files (1000-2300+ lines), AI can now jump directly to specific sections using read_file with offset and limit parameters.

Example:

# ❌ Before: Read entire file
read_file("src/metaspec/templates/meta/sdd/commands/specify.md.j2")
# Result: 2378 lines (~8000 tokens)

# ✅ After: Read only CLI design section
read_file("src/metaspec/templates/meta/sdd/commands/specify.md.j2", offset=390, limit=273)
# Result: 273 lines (~900 tokens)
# Token savings: 88.3% 🎉

Commands with Navigation

Enhanced commands (6 total, 8615 lines coverage):

Command	Lines	Navigation Sections	Best Savings
SDD/specify	2378	7 main + 7 subsections	70-94%
SDS/implement	1271	6 main + 9 templates	87-95%
SDS/specify	1060	6 main + 8 templates	70-90%
SDS/tasks	1054	7 main + 5 templates + 4 phases	84-99%
SDD/implement	998	7 main + 4 languages + 5 phases	84-97%
SDD/plan	854	7 main + 4 languages + 4 components	90-98%

How to Use Navigation

Each enhanced command starts with a 📖 Navigation Guide table showing:

Line ranges for each section
read_file usage with exact offset/limit
Typical usage patterns with concrete examples
Token savings calculation

Example from SDD/specify:

📖 Navigation Guide (Quick Reference with Line Numbers)

Core Flow:
| Step | Lines | Size | read_file Usage |
|------|-------|------|-----------------|
| 1. Setup | 55-111 | 56 lines | read_file(target_file, offset=55, limit=56) |
| 3. CLI Design | 390-663 | 273 lines | read_file(target_file, offset=390, limit=273) |

💡 Typical Usage Patterns:
# Minimal: Read only Steps 1-2 (135 lines)
read_file(target_file, offset=55, limit=135)

# CLI Design: Read Component 3 (273 lines)
read_file(target_file, offset=390, limit=273)

Language-Specific Navigation (SDD)

Special feature for toolkit development: Jump directly to language-specific context.

# Python toolkit development
read_file("implement.md.j2", offset=210, limit=25)  # 97% savings! 🏆

# TypeScript toolkit development
read_file("implement.md.j2", offset=236, limit=25)  # 97% savings! 🏆

# Go toolkit development
read_file("plan.md.j2", offset=132, limit=15)  # 98% savings! 🏆

# Rust toolkit development
read_file("plan.md.j2", offset=148, limit=16)  # 98% savings! 🏆

Best Practices

When to use navigation:

✅ You need specific guidance (e.g., CLI design, templates)
✅ You're familiar with the command structure
✅ You want to minimize token usage

When to read full file:

⚠️ First time using the command (learn structure)
⚠️ Need comprehensive understanding
⚠️ Unclear which section you need

Quick Reference Strategy:

# Step 1: Read navigation guide only (first 100 lines)
read_file(target_file, offset=1, limit=100)

# Step 2: Based on navigation, read specific section
read_file(target_file, offset=390, limit=273)

# Result: ~370 lines vs 2378 lines = 84% savings

Token Savings by Scenario

Real-world examples:

Scenario	Before	After	Savings
Quick start	2378 lines	135 lines	94.2%
CLI design	2378 lines	273 lines	88.3%
Template reference	1054 lines	11 lines	99.0% 🏆
Language context	854 lines	16 lines	98.1% 🏆
Operation template	1271 lines	45 lines	96.5%

Average token savings: 88-98% in typical usage scenarios.

🔄 Using Commands with Iteration Support

CRITICAL: Validation/analysis commands (checklist, analyze, clarify) support iteration modes to preserve history and track progress.

Understanding Iteration Modes

When you run a validation command and output already exists, you should ask the user which mode to use:

Mode	Action	When to Use
update (default)	Update scores/status, add Iteration N section	User says "re-run", "verify improvement", "check again"
new	Create new output (backup existing)	User says "start fresh", "regenerate"
append	Add supplementary output for different focus	User says "add another", "different aspect"

Default Interpretation Rules

When user says:

✅ "re-run checklist" → update mode
✅ "re-run analyze" → update mode
✅ "verify improvement" → update mode
✅ "check quality again" → update mode
⚠️ "start fresh" → new mode
⚠️ "regenerate checklist" → new mode
🔵 "add another checklist" → append mode

Key principle: Default to update mode unless user explicitly requests new/regenerate.

Iteration Workflow Example

Scenario: User improves specification based on checklist feedback

# Step 1: Initial validation
User: "Run checklist to validate specification quality"
AI: /metaspec.sds.checklist

Output:
✅ Checklist generated: comprehensive-quality.md

📋 Summary:
- CHK001: ❌ Missing field types
- CHK002: ❌ No validation rules
- CHK003: ⚠️ Incomplete examples
Score: 33% (1/3 passing)

# Step 2: User fixes issues
User edits specs/domain/001-mcp/spec.md
- Adds field types
- Adds validation rules

# Step 3: Re-validate (CRITICAL MOMENT)
User: "Re-run checklist to verify improvements"

AI recognizes:
- ✅ Checklist file exists
- ✅ User says "re-run... verify improvements"
- ✅ This means: update mode (not regenerate)

AI: /metaspec.sds.checklist (update mode)

Output:
✅ Checklist updated: comprehensive-quality.md

📊 Iteration 2 Summary:
- Items updated: 3/3
- Improved: 2 items (CHK001: ❌ → ✅, CHK002: ❌ → ✅)
- Still partial: 1 item (CHK003: ⚠️)

📈 Progress:
- Previous: 33% (1/3 passing)
- Current: 67% (2/3 passing)
- Improvement: +34%

🎯 Key improvements:
- CHK001: ❌ → ✅ (field types now defined)
- CHK002: ❌ → ✅ (validation rules added)

⚠️ Still needs work:
- CHK003: Examples incomplete (2/5 entities)

What Gets Preserved in Update Mode

Preserved:

✅ All previous iteration records (Iteration 1, 2, 3...)
✅ Original checklist item IDs (CHK001, CHK002...)
✅ Evidence and detailed findings
✅ Category structure
✅ Progress history

Updated:

✅ Pass/Partial/Missing status (❌ → ⚠️ → ✅)
✅ Evidence with new findings
✅ Overall scores and percentages

Added:

✅ New Iteration N section with date
✅ Progress comparison (before/after)
✅ List of improvements

Best Practices for AI Agents

Always check if output exists

Before running validation command:
- Check: Does checklists/comprehensive-quality.md exist?
- If YES: Ask user for mode (or infer from keywords)
- If NO: Generate new

Default to update mode

Unless user explicitly says "start fresh" or "regenerate":
→ Always choose update mode
→ This preserves valuable history

Highlight improvements

In update mode, emphasize:
- What improved: CHK001: ❌ → ✅
- What's still needed: CHK003: ⚠️
- Overall progress: +34%

Never silently overwrite

❌ WRONG: Detect existing file → Silently regenerate
✅ RIGHT: Detect existing file → Ask mode → Update with history

When NOT to Use Iteration Modes

Creation commands (specify, implement, constitution):

❌ These create initial specs/code
❌ After creation, users edit directly
❌ No iteration tracking needed

Execution commands (tasks):

❌ These execute and mark complete
❌ Not validation-oriented
❌ Use Evolution for changes

Evolution Layer vs Command Layer

Command Layer (checklist, analyze, clarify):

Purpose: Validate specification quality (read-only)
Output: checklists/quality.md, analysis/report.md
Never modifies: spec.md
Iteration: update/new/append modes

Evolution Layer (proposal, apply, archive):

Purpose: Modify specifications (formal process)
Output: changes/[id]/proposal.md, spec-delta.md
Modifies: spec.md (after approval)
When: Released toolkit OR breaking/major changes

See Decision Guide for when to use which.

📝 Complete Workflow: Generating a Speckit

This section describes how to generate a speckit using metaspec init.

Note: This is different from developing a speckit (which uses MetaSpec commands and SDS + SDD Separation practice).

Two Workflows

Workflow	Purpose	Commands
Generate Speckit	Create initial speckit structure	`metaspec init` (this section)
Develop Speckit	Define specs and implement features	MetaSpec commands `/metaspec.*`

Creating a speckit is more complex than building an application. Follow these steps carefully.

STEP 1: Understand Domain Requirements

Goal: Research domain before designing.

Key actions:

Ask clarifying questions (domain, use case, users, existing tools)
Use web_search for standards and best practices
Identify key entities and relationships

Checklist:

Domain thoroughly researched
Key entities identified (1-3 core entities)
Existing solutions studied
Not assuming domain behavior

STEP 2: Design Entity Model

Goal: Define core entities with minimal fields.

Key principles:

Start minimal: 1-3 entities, 3-5 fields each
Field types: string, number, boolean, array, object
Only essential fields as required: true
Every field needs a description

Checklist:

Entities match domain research
Field names clear and consistent
Only essential fields required
No over-engineering

STEP 3: Use Template or Interactive Mode

Recommended: Use metaspec init with templates or interactive mode.

metaspec init                        # Interactive wizard
metaspec init my-toolkit             # Quick start (uses 'default')
metaspec init my-toolkit default     # Explicit (same as above)

Required fields (if manual):

name, version, domain, lifecycle, description
Entity definition (from STEP 2)
Commands (init, validate, generate)
Dependencies (pydantic, typer, yaml parser)

Checklist:

All required fields filled
Entity matches STEP 2 design
Commands aligned with domain
Dependencies specified

STEP 3.5: Understand init Command Standards ⭐ NEW

Goal: Ensure your speckit's init command follows MetaSpec standards.

Why this matters: When you later use /metaspec.sdd.specify to define your toolkit, the init command specification must align with MetaSpec conventions. This prevents common mistakes like creating single files instead of project structures.

init Command Standard for Generator/Scaffolder Toolkits

If your toolkit type is "Generator/Scaffolder", the init command MUST:

Argument Format:
```
{toolkit-name} init <project-directory> [OPTIONS]
```
- ✅ Argument is a directory name (not a filename)
- ❌ WRONG: {toolkit-name} init spec.yaml
- ✅ RIGHT: {toolkit-name} init my-project

Output Structure (Must create):

<project-directory>/
├── .{toolkit-name}/       # Configuration directory
│   ├── commands/          # (Optional) Custom slash commands
│   └── templates/         # (Optional) Output templates
├── memory/
│   └── constitution.md    # Project principles (pre-filled)
├── specs/
│   └── {initial-spec}     # Initial specification file
└── README.md              # Project documentation

constitution.md Requirements:
- ✅ Must be pre-filled with template content
- ✅ Must include domain-specific guidance
- ❌ NOT empty or placeholder
Initial Specification File:
- ✅ Created from template with example data
- ✅ Must pass validation immediately

Reference Examples

✅ Correct (MetaSpec itself):

metaspec init my-speckit
# Creates: my-speckit/ with full structure
# - All required directories
# - Pre-filled constitution.md
# - Example spec files

❌ Wrong:

my-toolkit init spec.yaml
# Creates: Single spec.yaml file only
# Missing: directories, constitution, README

Why These Standards?

Consistency: All MetaSpec-generated toolkits follow the same pattern
AI-Friendly: AI agents know what to expect
Complete Projects: Users get a full project structure, not just a file
Best Practices: Follows industry standards (like create-react-app, cargo new)

When NOT to Follow

If your toolkit is NOT a "Generator/Scaffolder" (e.g., pure validator, query tool), init may have different behavior or not exist at all. The standards above apply specifically to toolkits that create projects or scaffolding.

STEP 4: Preview with Dry-Run

Goal: Test before generating.

metaspec init my-toolkit --dry-run

Checklist:

File structure looks correct
Entity names verified
Dependencies confirmed
No validation errors

STEP 5: Generate Speckit

Goal: Generate the complete speckit.

metaspec init my-speckit -o ./my-speckit

Post-generation:

Verify files created successfully
Run init script if exists: ./scripts/init.sh
Read generated README.md and AGENTS.md

Checklist:

Generation completed without errors
All expected files present
README and AGENTS.md generated

STEP 6: Test the Speckit

Goal: Verify speckit works.

cd my-speckit
pip install -e .
my-speckit --help
my-speckit init sample.yaml
my-speckit validate sample.yaml

Checklist:

CLI commands work
Help messages clear
Sample spec validates
Error messages helpful

⚠️ Common Pitfalls

Avoid these mistakes:

Over-Engineering - Start with 1-3 entities, 3-5 fields each (not 20+ fields)
Skipping Research - Always use web_search to study domain standards
No Dry-Run - Always preview with --dry-run before generating
Not Testing - Test CLI commands after generation
Ignoring Constitution - Follow Minimal Viable Abstraction, AI-First Design, Progressive Enhancement

🎯 Success Criteria

A successful speckit generation should:

Solves a real domain problem - Not just a generic tool
Has clear entity model - Entities match domain research
Follows minimal abstraction - No over-engineering
Generates cleanly - No errors during metaspec init
CLI works - All commands functional
Has good docs - README and AGENTS.md are clear
Includes constitution - memory/constitution.md exists
Is testable - Can create sample specs
Follows patterns - Matches existing spec-driven tools

📚 Additional Resources

Template: templates/meta-spec-template.yaml
Examples: examples/ directory
Constitution: memory/constitution.md
Docs: docs/ directory

FilesExpand file tree

AGENTS.md

Latest commit

History

AGENTS.md

File metadata and controls

Meta-Spec AI Agent Guide

🎯 Your Role

💡 Core Concept: Meta-Specification Framework

Key Insights

📋 CLI Commands

🔒 Constitutional Principles

Constitution Structure

🚀 Workflow-Driven Design Philosophy

Two Types of Workflows ⭐ UPDATED v0.8.0

Type 1: Entity State Machines (Business Execution)

Type 2: Specification Usage Workflow (Specification Creation) ⭐ NEW

Why Workflow Matters

The Problem We Solved

MetaSpec as Example

Required Workflow Elements

Enforcement

Examples

Your Checklist

🤝 Spec-Driven Development for Speckits

🎯 MetaSpec Commands: Specification Lifecycle Management

Command Groups

SDS (Spec-Driven Specification) - 8 Commands

🌳 Recursive Tree Structure (NEW)

⚠️ CRITICAL PRINCIPLE: Specification First, Toolkit Second

🎯 How Toolkit Value is Realized

Stage 1: Define Specification (SDS)

Stage 2: Define Toolkit (SDD)

Stage 3: Generate Code (SDD)

SDD (Spec-Driven Development) - 8 Commands

Evolution - 3 Shared Commands

The Relationship

When to Use Which

Recommended Practice: SDS + SDD Separation

Phase 1: Domain Specification (SDS)

Phase 2: Toolkit Specification (SDD)

MetaSpec Workflow for SDS + SDD

Phase 2: Toolkit Specification (SDD)

Evolution: Manage Changes

🧭 Token Optimization: Precision-Guided Navigation

What is Precision-Guided Navigation?

Commands with Navigation

How to Use Navigation

Language-Specific Navigation (SDD)

Best Practices

Token Savings by Scenario

🔄 Using Commands with Iteration Support

Understanding Iteration Modes

Default Interpretation Rules

Iteration Workflow Example

What Gets Preserved in Update Mode

Best Practices for AI Agents

When NOT to Use Iteration Modes

Evolution Layer vs Command Layer

📝 Complete Workflow: Generating a Speckit

Two Workflows

STEP 1: Understand Domain Requirements

STEP 2: Design Entity Model

STEP 3: Use Template or Interactive Mode

STEP 3.5: Understand init Command Standards ⭐ NEW

init Command Standard for Generator/Scaffolder Toolkits

Reference Examples

Why These Standards?

When NOT to Follow

STEP 4: Preview with Dry-Run

STEP 5: Generate Speckit

STEP 6: Test the Speckit

⚠️ Common Pitfalls

🎯 Success Criteria

📚 Additional Resources