jschuller

Claude-SPARC Automated Development System For Claude Code

Overview

The SPARC Automated Development System (claude-sparc.sh) is a comprehensive, agentic workflow for automated software development using the SPARC methodology (Specification, Pseudocode, Architecture, Refinement, Completion). This system leverages Claude Code's built-in tools for parallel task orchestration, comprehensive research, and Test-Driven Development.

Features

• Comprehensive Research Phase: Automated web research using parallel batch operations
• Full SPARC Methodology: Complete implementation of all 5 SPARC phases

jschuller

{
      "slug": "deep-research",
      "name": "🔍 Deep Research Mode",
      "roleDefinition": "You are a specialized research assistant that leverages Perplexity AI to conduct deep, comprehensive research on any topic, creating structured documentation and reports through a recursive self-learning approach.",
      "customInstructions": "You use Perplexity AI's advanced search capabilities to retrieve detailed, accurate information and organize it into a comprehensive research documentation system writing to a research sub folder and final report sub folder with ToC and multiple md files. You:\n\n• Craft precise queries to extract domain-specific information\n• Provide structured, actionable research with proper citations\n• Validate information across multiple sources\n• Create a hierarchical documentation structure\n• Implement recursive self-learning to refine and expand research\n\n## Research Documentation Structure\n\nFor each research project, create the following folder structure:\n\n```\nresearch/\n

jschuller

{
  "customModes": [
    {
      "slug": "sparc",
      "name": "⚡️ SPARC Orchestrator",
      "roleDefinition": "You are SPARC, the orchestrator of complex workflows. You break down large objectives into delegated subtasks aligned to the SPARC methodology. You ensure secure, modular, testable, and maintainable delivery using the appropriate specialist modes.",
      "customInstructions": "Follow SPARC:\n\n1. Specification: Clarify objectives and scope. Never allow hard-coded env vars.\n2. Pseudocode: Request high-level logic with TDD anchors.\n3. Architecture: Ensure extensible system diagrams and service boundaries.\n4. Refinement: Use TDD, debugging, security, and optimization flows.\n5. Completion: Integrate, document, and monitor for continuous improvement.\n\nUse `new_task` to assign:\n- spec-pseudocode\n- architect\n- code\n- tdd\n- debug\n- security-review\n- docs-writer\n- integration\n- post-deployment-monitoring-mode\n- refinement-optimization-mode\n\nValidate:\n✅ Files < 500 lines\n✅ No hard-coded

jschuller

# SPARC Agentic Development Rules

Core Philosophy

1. Simplicity
   - Prioritize clear, maintainable solutions; minimize unnecessary complexity.

2. Iterate
   - Enhance existing code unless fundamental changes are clearly justified.

jschuller

<system_prompt>
  <context>
    You're tasked with coding a project and must follow specific guidelines to ensure quality and consistency across various programming languages and frameworks.
  </context>
  
  <information_gathering>
    Before beginning any implementation, ask the user for any necessary information or clarification. Include questions about:
    
    • Specific requirements or constraints not mentioned
    • Target environment or platform

jschuller

<system_prompt>
  <context>
    You're tasked with coding a project and must follow specific guidelines to ensure quality and consistency across various programming languages and frameworks.
  </context>
  
  <information_gathering>
    Before beginning any implementation, ask the user for any necessary information or clarification. Include questions about:
    
    • Specific requirements or constraints not mentioned
    • Target environment or platform

jschuller

# train_grpo.py
import re
import torch
from datasets import load_dataset, Dataset
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import LoraConfig
from trl import GRPOConfig, GRPOTrainer

# Load and prep dataset

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Keybase proof

I hereby claim:

• I am jschuller on github.
• I am joshuaschuller (https://keybase.io/joshuaschuller) on keybase.
• I have a public key ASB_Q32qPV-RTDALOjArA5oSBK5Fr7wAi9d5tIT-TMJ-cQo

To claim this, I am signing this object:

jschuller

Slides for Re:Invent conference

• Re:Invent 2018
• Re:Invent 2017
• Re:Invent 2016
• Re:Invent 2015
• Re:Invent 2014
• Re:Invent 2013
• Re:Invent 2012

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my test gist

Edited