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672 Sam Framework Generator 2a8e6ae6
ASecurity**Status**: Conceptual Design **Purpose**: Generate project-specific SAM implementations through a meta-SAM workflow **Date**: 2026-01-26 ---
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- Added October 11, 2026
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[](https://www.skillsdirectory.com/skills/tools-only-672-sam-framework-generator-2a8e6ae6)# SAM Framework Generator
**Status**: Conceptual Design
**Purpose**: Generate project-specific SAM implementations through a meta-SAM workflow
**Date**: 2026-01-26
---
## Core Concept
Use **SAM to create SAM** - apply the Stateless Agent Methodology to generate project-specific SAM workflows.
Instead of manually creating commands, agents, and skills for each project type, the SAM Framework Generator uses the SAM 7-stage pipeline to discover requirements, research patterns, design the workflow, and generate all necessary artifacts.
---
## The Meta-SAM Pattern
```
┌────────────────────────────────────────────────────────────────┐
│ SAM FRAMEWORK GENERATOR (META-SAM) │
├────────────────────────────────────────────────────────────────┤
│ │
│ Input: Project type intent (e.g., "Python CLI tool") │
│ Output: Complete SAM implementation for that project type │
│ │
│ Stage 1: DISCOVERY │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ Interview user about: │ │
│ │ - What workflows does this project type need? │ │
│ │ - What are the common operations? (add feature, fix bug) │ │
│ │ - What technologies/patterns are used? │ │
│ │ - What constraints exist? (Python version, frameworks) │ │
│ │ - What verification is required? (tests, linting) │ │
│ │ - What artifacts should be generated? │ │
│ │ │ │
│ │ Output: Project Type Requirements Document │ │
│ └──────────────────────────────────────────────────────────┘ │
│ ▼ │
│ Stage 2: PLANNING (RT-ICA) │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ Verify prerequisites: │ │
│ │ - Are there existing SAM templates? │ │
│ │ - Are the workflow patterns well-defined? │ │
│ │ - Do we have reference implementations? │ │
│ │ │ │
│ │ BLOCKS if missing SAM component templates │ │
│ │ Output: SAM Generation Plan │ │
│ └──────────────────────────────────────────────────────────┘ │
│ ▼ │
│ Stage 3: CONTEXT INTEGRATION │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ Research project type patterns: │ │
│ │ - Analyze existing similar projects │ │
│ │ - Identify common file structures │ │
│ │ - Map technology stack patterns │ │
│ │ - Find existing SAM implementations to reference │ │
│ │ │ │
│ │ Output: Contextualized SAM Design │ │
│ └──────────────────────────────────────────────────────────┘ │
│ ▼ │
│ Stage 4: TASK DECOMPOSITION │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ For each workflow identified in discovery: │ │
│ │ - Design the 7-stage SAM pipeline for that workflow │ │
│ │ - Identify specialized agents needed │ │
│ │ - Define artifact templates │ │
│ │ - Specify verification gates │ │
│ │ │ │
│ │ Output: SAM Component Generation Tasks │ │
│ └──────────────────────────────────────────────────────────┘ │
│ ▼ │
│ Stage 5: EXECUTION │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ Generate artifacts: │ │
│ │ - .claude/commands/{workflow}.md (orchestrator) │ │
│ │ - .claude/agents/{role}.yaml (specialized agents) │ │
│ │ - .claude/sam-templates/{artifact}.md (templates) │ │
│ │ - .claude/sam-config.yaml (project configuration) │ │
│ │ │ │
│ │ Output: Generated SAM Implementation │ │
│ └──────────────────────────────────────────────────────────┘ │
│ ▼ │
│ Stage 6: FORENSIC REVIEW │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ Verify generated SAM implementation: │ │
│ │ - Commands follow orchestrator discipline │ │
│ │ - Agents have proper DONE/BLOCKED signaling │ │
│ │ - Artifact templates are complete │ │
│ │ - Workflow stages match SAM principles │ │
│ │ │ │
│ │ Output: Validation Report │ │
│ └──────────────────────────────────────────────────────────┘ │
│ ▼ │
│ Stage 7: FINAL VERIFICATION │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ Confirm generated SAM meets requirements: │ │
│ │ - All workflows from discovery have implementations │ │
│ │ - Agents cover all identified roles │ │
│ │ - Templates support required artifacts │ │
│ │ │ │
│ │ Output: Project-Specific SAM Ready for Use │ │
│ └──────────────────────────────────────────────────────────┘ │
│ │
└────────────────────────────────────────────────────────────────┘
```
---
## Discovery Phase Interview Structure
The Discovery Agent asks structured questions to gather complete requirements:
### Workflow Identification
**Questions:**
- What are the primary workflows for this project type? (e.g., "add feature", "fix bug", "refactor module")
- For each workflow, what triggers it? (user request, automated process)
- What is the typical complexity? (simple, moderate, complex)
- What are the success criteria for each workflow?
### Technology Stack
**Questions:**
- What programming language(s)?
- What frameworks or libraries? (e.g., Typer, Django, FastAPI, Rust clap)
- What build tools? (e.g., uv, cargo, npm)
- What testing frameworks? (pytest, jest, cargo test)
- What linting/formatting tools? (ruff, mypy, clippy, prettier)
### Domain Constraints
**Questions:**
- What architectural patterns are used? (CLI, web app, microservices)
- What are the code organization conventions? (modules, packages, directory structure)
- What data models or schemas are common?
- What external systems are integrated? (APIs, databases, SSH)
- What security considerations apply?
### Artifact Requirements
**Questions:**
- What documents should be generated during planning? (architecture specs, API docs)
- What format should task files use?
- What metadata should be tracked?
- What reports are needed for verification?
### Agent Specializations
**Questions:**
- What roles are needed? (researcher, architect, implementer, tester, reviewer)
- What domain expertise should each agent have?
- What tools should each agent have access to?
- What are the DONE/BLOCKED criteria for each agent?
### Verification Gates
**Questions:**
- What automated checks should run? (tests, linting, security scans)
- What manual review points are needed?
- What are the quality thresholds? (coverage %, linting pass rate)
- What are the acceptance criteria for complete features?
---
## Generated Artifacts
For a project type (e.g., "Python CLI Tool"), the generator produces:
### 1. Workflow Commands
`.claude/commands/add-new-feature.md`
- Orchestrates 7-stage SAM pipeline for adding features
- Delegates to specialized agents
- Uses TodoWrite for progress tracking
- Generates feature-specific artifacts
`.claude/commands/fix-bug.md`
- Orchestrates SAM pipeline for bug fixes
- Includes root cause analysis stage
- Generates bug reports and patches
`.claude/commands/refactor-module.md`
- Orchestrates SAM pipeline for refactoring
- Includes technical debt assessment
- Generates refactoring plans and verification reports
### 2. Specialized Agents
`.claude/agents/python-cli-researcher.yaml`
- Role: Discovery and requirements gathering
- Tools: Read, Grep, Glob, AskUserQuestion
- Expertise: Python CLI patterns, Typer conventions
- Output: Feature requirements document
`.claude/agents/python-cli-architect.yaml`
- Role: Architecture design
- Tools: Read, Write, Grep, Glob
- Expertise: Pydantic models, CLI design, Python 3.11+
- Output: Architecture specification
`.claude/agents/python-task-planner.yaml`
- Role: Task decomposition
- Tools: Read, Write, Grep, Glob
- Expertise: TDD patterns, dependency analysis
- Output: Task file with dependencies
`.claude/agents/python-cli-implementer.yaml`
- Role: Code implementation
- Tools: Read, Write, Edit, Bash
- Expertise: Python 3.11+, Typer, Pydantic, async patterns
- Output: Implementation + self-verification results
`.claude/agents/python-test-architect.yaml`
- Role: Test creation
- Tools: Read, Write, Edit, Bash
- Expertise: pytest, pytest-mock, hypothesis, coverage
- Output: Test suite + coverage report
`.claude/agents/python-forensic-reviewer.yaml`
- Role: Independent verification
- Tools: Read, Bash, Grep
- Expertise: Code review, quality assessment
- Output: Review report with COMPLETE/NEEDS_WORK verdict
### 3. Artifact Templates
`.claude/sam-templates/feature-requirements.md`
```markdown
# Feature Requirements: {feature-name}
## Who
{target users}
## When
{trigger conditions}
## Where
{integration point}
## Inputs
{parameters, files, env vars}
## Outputs
{results, exit codes, side effects}
## Guardrails
{validation, safety checks}
## Conditionals
{edge cases, error handling}
## Naming
{CLI command/option names}
## Acceptance Criteria
- [ ] Criterion 1
- [ ] Criterion 2
- [ ] Criterion 3
```
`.claude/sam-templates/architecture-spec.md`
```markdown
# Architecture Specification: {feature-name}
## Overview
{high-level design}
## CLI Interface
{Typer command structure}
## Component Changes
{modules affected}
## Data Models
{Pydantic models}
## Error Handling
{exception strategy}
## Security Considerations
{security analysis}
## Testing Strategy
{test approach}
```
`.claude/sam-templates/task-file.md`
```markdown
# Implementation Tasks: {feature-name}
## Task 1: {name}
**Status**: pending
**Dependencies**: []
**Priority**: high
**Complexity**: moderate
**Agent**: python-cli-implementer
**Acceptance Criteria**:
- [ ] Criterion 1
- [ ] Criterion 2
**Verification Steps**:
- [ ] Step 1
- [ ] Step 2
**Context Manifest**: {will be added by context-gathering agent}
```
### 4. Project Configuration
`.claude/sam-config.yaml`
```yaml
# SAM Configuration for Python CLI Tool Projects
project_type: python-cli-tool
framework_version: "1.0.0"
# Technology Stack
languages:
- python: "3.11+"
frameworks:
- typer: "CLI framework"
- pydantic: "v2 - Data validation"
- rich: "Terminal UI"
build_tools:
- uv: "Package management and script runner"
testing:
- pytest: "Test framework"
- pytest-mock: "Mocking"
- pytest-asyncio: "Async tests"
- hypothesis: "Property-based testing"
- coverage: "Code coverage (80% minimum)"
quality:
- ruff: "Linting and formatting"
- mypy: "Type checking (strict mode)"
# SAM Workflow Configuration
workflows:
add-feature:
command: /add-new-feature
stages: 7
agents:
- python-cli-researcher
- python-cli-architect
- python-task-planner
- python-cli-implementer
- python-test-architect
- python-forensic-reviewer
artifacts:
- feature-requirements.md
- architecture-spec.md
- task-file.md
- implementation-results.md
- review-report.md
fix-bug:
command: /fix-bug
stages: 7
agents:
- bug-investigator
- root-cause-analyzer
- python-cli-implementer
- python-test-architect
- python-forensic-reviewer
artifacts:
- bug-report.md
- root-cause-analysis.md
- fix-plan.md
- implementation-results.md
- review-report.md
# Verification Gates
verification:
tests:
required: true
min_coverage: 80
frameworks: [pytest]
linting:
required: true
tools: [ruff, mypy]
strict_mode: true
security:
required: false
tools: []
# Domain Constraints
constraints:
python_version: "3.11+"
type_hints: required
async_patterns: preferred
cli_framework: typer
data_validation: pydantic-v2
```
---
## SAM Component Templates
These templates are used by the generator to create project-specific agents and commands.
### Agent Template
`.claude/sam-templates/agent-template.yaml`
```yaml
# SAM Agent Template
# Variables: {ROLE_NAME}, {EXPERTISE}, {TOOLS}, {OUTPUT_ARTIFACT}
name: {ROLE_NAME}
description: |
SAM {STAGE_NAME} stage agent for {PROJECT_TYPE}.
{ROLE_DESCRIPTION}
model: claude-sonnet-4.5
tools:
{TOOLS_LIST}
prompt: |
You are a {ROLE_NAME} agent in a Stateless Agent Methodology (SAM) workflow.
Your ROLE_TYPE is sub-agent.
## Your Responsibilities
{RESPONSIBILITIES}
## Domain Expertise
{EXPERTISE}
## Input Artifacts
{INPUT_ARTIFACTS}
## Output Requirements
You MUST produce: {OUTPUT_ARTIFACT}
The artifact MUST include:
{OUTPUT_REQUIREMENTS}
## Completion Signaling
Return STATUS: DONE when:
- {DONE_CRITERIA}
Return STATUS: BLOCKED when:
- {BLOCKED_CRITERIA}
## Verification Protocol
Before signaling DONE:
1. {VERIFICATION_STEP_1}
2. {VERIFICATION_STEP_2}
3. {VERIFICATION_STEP_3}
```
### Command Template
`.claude/sam-templates/command-template.md`
```markdown
---
description: {WORKFLOW_DESCRIPTION}
argument-hint: {ARGUMENT_HINT}
---
# {WORKFLOW_NAME}
Execute the {WORKFLOW_NAME} workflow using the Stateless Agent Methodology (SAM).
<workflow_request>
$ARGUMENTS
</workflow_request>
---
## Orchestrator Discipline
**CRITICAL**: You are an orchestrator. You coordinate work across specialized agents. You do NOT perform discovery work directly.
- **NEVER** use Read tool to gather information for decision-making
- **NEVER** use Glob tool to search the codebase
- **NEVER** use Grep tool to find patterns
- **ALWAYS** delegate discovery and analysis to specialized agents
- **ALWAYS** use TodoWrite for progress tracking (your state management tool)
- **CAN** read files ONLY for state management (checking task status, not for discovery)
Your role: Route context between user and agents. Define success criteria. Track progress. Trust agent expertise.
---
## Mission
Orchestrate the execution of all {STAGE_COUNT} SAM stages sequentially. Each stage depends on the previous stage's output. After each stage completes, RECEIVE the agent's structured STATUS response before proceeding to the next stage.
---
## Completion Tracking (MANDATORY)
**IMMEDIATELY** after reading this command, you MUST create todos using TodoWrite with this exact checklist:
```
TodoWrite(todos=[
{STAGE_TODOS}
])
```
**RULES**:
1. Create ALL todos BEFORE starting Stage 1
2. Mark each todo `in_progress` BEFORE launching the agent
3. Mark each todo `completed` AFTER agent returns STATUS: DONE
4. If agent returns STATUS: BLOCKED, keep todo as `in_progress` and address the blocker
5. DO NOT display final summary until ALL todos are `completed`
---
{STAGE_DEFINITIONS}
---
## Final Summary
**BEFORE displaying the final summary, YOU MUST:**
1. **VERIFY ALL TODOS COMPLETE**: All todos from Completion Tracking should be `completed`
2. If ANY todo is still `pending` or `in_progress`, DO NOT display the final summary - complete the missing work first
3. Mark "Final: Display completion summary" as `in_progress`
4. DISPLAY this summary structure:
```
================================================================================
{WORKFLOW_NAME} COMPLETE
================================================================================
Request: $ARGUMENTS
## DELIVERABLES
{DELIVERABLES_LIST}
## PHASE SUMMARIES
{PHASE_SUMMARIES}
## NEXT STEPS (for user)
{NEXT_STEPS}
## FILES TO REVIEW
{FILES_TO_REVIEW}
```
5. Mark "Final: Display completion summary" as `completed`
**WORKFLOW COMPLETE**
```
### Stage Template
`.claude/sam-templates/stage-template.md`
```markdown
## Stage {N}: {STAGE_NAME}
**Agent**: `{AGENT_NAME}`
**Purpose**: {STAGE_PURPOSE}
### Delegation
```
Task(
subagent_type="{AGENT_NAME}",
description="{STAGE_DESCRIPTION}",
prompt="""
Your ROLE_TYPE is sub-agent.
OBSERVATIONS:
{OBSERVATIONS}
DEFINITION OF SUCCESS:
{SUCCESS_CRITERIA}
CONTEXT:
{CONTEXT}
YOUR TASK:
{TASK_STEPS}
AVAILABLE RESOURCES:
{RESOURCES}
"""
)
```
### Handle Result
IF STATUS: DONE → {DONE_ACTION}
IF STATUS: BLOCKED → {BLOCKED_ACTION}
```
---
## Implementation Phases
### Phase 1: Core Infrastructure
**Deliverables:**
- SAM generator command: `/sam:generate`
- Discovery agent for requirements gathering
- Project type registry (initial types: python-cli, django-web, rust-binary)
- Template storage in `.claude/sam-templates/`
### Phase 2: Template System
**Deliverables:**
- Agent template system
- Command template system
- Artifact template system
- Variable substitution engine
### Phase 3: Project Type Library
**Deliverables:**
- Python CLI tool templates
- Django web app templates
- Rust binary templates
- React/Next.js frontend templates
### Phase 4: Customization
**Deliverables:**
- Project-specific overrides
- Custom agent injection
- Workflow composition
- Template inheritance
### Phase 5: Validation & Testing
**Deliverables:**
- Generated artifact validation
- SAM principle compliance checks
- Integration testing harness
- Example generated projects
---
## Example Usage
### Generate SAM for Python CLI Project
```bash
# User invokes generator
/sam:generate python-cli-tool
# Discovery agent interviews user
Agent: "What workflows does this CLI tool need?"
User: "Add commands, fix bugs, refactor modules"
Agent: "What CLI framework do you use?"
User: "Typer with Rich for UI"
Agent: "What testing approach?"
User: "pytest with 80% coverage minimum"
# ... more questions ...
# Generator produces artifacts
✓ Generated: .claude/commands/add-new-feature.md
✓ Generated: .claude/commands/fix-bug.md
✓ Generated: .claude/commands/refactor-module.md
✓ Generated: .claude/agents/python-cli-researcher.yaml
✓ Generated: .claude/agents/python-cli-architect.yaml
✓ Generated: .claude/agents/python-task-planner.yaml
✓ Generated: .claude/sam-templates/feature-requirements.md
✓ Generated: .claude/sam-config.yaml
SAM framework ready for: Python CLI Tool
Available workflows: /add-new-feature, /fix-bug, /refactor-module
```
### Use Generated Workflow
```bash
# User invokes generated workflow
/add-new-feature Add a command that lists all out-of-date packages on remote managed hosts over SSH, with search and filtering, and options for selecting what to install or installing all updates. With a toggle for a post-update reboot, or to schedule a reboot for its maintenance window.
# Orchestrator follows SAM 7-stage pipeline
Stage 1: Discovery → python-cli-researcher agent
Stage 2: Planning → validates prerequisites
Stage 3: Context Integration → maps to existing code
Stage 4: Task Decomposition → generates task file
Stage 5: Execution → python-cli-implementer agent
Stage 6: Forensic Review → python-forensic-reviewer agent
Stage 7: Final Verification → confirms feature complete
# Complete with all artifacts generated
✓ Feature requirements documented
✓ Architecture spec created
✓ Task file with dependencies
✓ Implementation verified
✓ Tests passing at 85% coverage
```
---
## Integration with Existing SAM Concepts
### Convergence with OctoCode RDD
The generator can produce workflows that use OctoCode's adversarial validation:
```yaml
# In .claude/sam-config.yaml
verification_style: adversarial
# Generates agents with Generator/Discriminator pattern
agents:
- python-cli-generator # Produces code
- python-cli-verifier # Finds flaws (adversarial)
```
### Convergence with Get Shit Done (GSD)
The generator can produce workflows that use GSD's wave execution:
```yaml
# In .claude/sam-config.yaml
execution_style: wave-based
# Generates task files with parallelization metadata
task_format: gsd-compatible
```
---
## Naming Considerations
Following the pop culture naming exploration, project types could have themed names:
| Project Type | SAM Nickname | Rationale |
| -------------- | ---------------------- | ---------------------------------------- |
| Python CLI | "The Ford Line" | Assembly line metaphor for CLI pipelines |
| Django Web | "The Groundhog Loop" | Iteration cycles for web development |
| Rust Binary | "The Apollo Pattern" | Systems rigor and verification |
| React Frontend | "The Portal Framework" | Component portals and state management |
| Data Pipeline | "The Deming Cycle" | PDCA quality methodology |
| Microservices | "The Memento Pattern" | Stateless services with external memory |
These names appear in:
- Generated command descriptions
- Agent role definitions
- Artifact templates
- Project documentation
---
## Success Metrics
| Metric | Target | Measurement |
| ------------------------------ | ------ | ----------------------------------------------- |
| **Generation time** | <5 min | Time from `/sam:generate` to complete artifacts |
| **Workflow completeness** | 100% | All identified workflows have implementations |
| **Agent specialization** | 5-7 | Agents per workflow for proper separation |
| **Artifact template coverage** | 100% | Templates for all required documents |
| **SAM principle compliance** | 100% | Generated artifacts follow SAM structure |
| **User customization** | <10min | Time to customize generated workflow |
---
## Future Enhancements
### Community Template Registry
Allow sharing of project type templates:
```bash
/sam:install community/nestjs-backend
/sam:install community/svelte-frontend
```
### Cross-Project Learning
Generator learns from successful implementations:
```bash
# After successful feature implementation
/sam:learn-pattern add-new-feature
# Incorporates pattern into future generations
```
### Template Composition
Combine multiple project types:
```bash
/sam:generate python-cli + fastapi-backend
# Generates workflows for both CLI and API development
```
---
## Conclusion
The SAM Framework Generator is a **meta-SAM** that uses the Stateless Agent Methodology to create project-specific SAM implementations.
**Core Insight**: Instead of manually creating SAM workflows for each project type, use SAM's own principles to discover, design, and generate those workflows.
**Key Benefits**:
1. **Consistency**: All generated workflows follow SAM principles
2. **Customization**: Tailored to project-specific technologies and constraints
3. **Evolution**: Easy to update templates and regenerate
4. **Reusability**: Templates can be shared and versioned
5. **Learning**: Captures best practices in template form
**The Recursion**: SAM generates SAM, which generates working software through SAM.
**Next Steps**:
1. Implement Phase 1 (Core Infrastructure)
2. Create initial templates for Python CLI tools
3. Validate with real-world project generation
4. Expand to additional project types
5. Build community template registry
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