// AI Developer Tools
CLI tools for the AI engineering workflow — cost tracking, prompt ops, context analysis, memory, and agent linting.
Claude API toolkit — prompt engineering + code review + doc intelligence 311 tests
pip install promptctlai
CLAUDE.md generator + auditor + drift detector 594 tests
pip install claudemd-forge
// Flagship Projects
AI agent framework — autonomous build pipelines, dual-model routing, streaming, MCP server, identity system with guardrails
Fantasy football analytics SaaS — live at benchgoblins.com. Player dossiers, scoring engine, agent pipeline
// Case Study
Problem
AI coding agents like Claude Code rely on CLAUDE.md files for project context — coding standards, architecture, commands, anti-patterns. But these files are written by hand, go stale within days, and nobody audits them. The agent makes worse decisions every time the context drifts from reality.
Solution
Built a CLI that analyzes your codebase and generates accurate CLAUDE.md files automatically. It reads pyproject.toml, package.json, Cargo.toml, detects naming conventions by sampling source files, maps architecture trees, and extracts commands from CI configs. Then it audits existing files for accuracy and detects behavioral drift across LLM model versions using benchmark suites.
Architecture
- Generator — metadata extraction, pattern analysis, Jinja2 templates
- Auditor — 4 accuracy checkers validate claims against codebase
- Drift Detector — 6 check types, 4 model adapters, YAML benchmark suites, trend visualization
- License Server — FastAPI, SHA-256 hashed keys, rate limiting, activation tracking