| name | description |
|---|---|
orchestrating-swarms |
Master multi-agent orchestration using Claude Code's TeammateTool and Task system. Use when coordinating multiple agents, running parallel code reviews, creating pipeline workflows with dependencies, building self-organizing task queues, or any task benefiting from divide-and-conquer patterns. |
Master multi-agent orchestration using Claude Code's TeammateTool and Task system.
This is not a proposal. This documents existing but hidden functionality found in Claude Code v2.1.19 binary, plus speculation on how it could be used.
TeammateTool already exists in Claude Code. We extracted this from the compiled binary at ~/.local/share/claude/versions/2.1.19 using strings analysis. The feature is fully implemented but gated behind feature flags (I9() && qFB()).
| #!/usr/bin/env bash | |
| set -euo pipefail | |
| source_dirs=( | |
| "/Users/someone/code/some-skills" | |
| "/Users/someone/code/sentry_skills" | |
| "/Users/someone/code/my-skills" | |
| ) | |
| codex_dest="$HOME/.codex/skills/public" |
| // | |
| // ContentView.swift | |
| // Airdrop Demo | |
| // | |
| // Created by Daniel Kuntz on 7/30/23. | |
| // | |
| import SwiftUI | |
| struct ContentView: View { |
Your org's brain that AI can use
This document describes the conceptual architecture of the Inferal Workspace - a text-based, version-controlled knowledge and operations hub designed to replace tools like Notion and Webflow while being natively accessible to AI assistants.
As an engineering-driven organization, we found ourselves fighting our tools instead of using them. Notion couldn't keep up with how we actually work - context scattered across pages, no version control, and AI that could read but not act. Webflow meant our website lived in a silo, disconnected from our codebase and deployment pipelines. Every tool was another tab, another context switch, another place where knowledge went to die.
Production-Ready Framework for Continuous Agent Learning
A complete implementation of reward-free reinforcement learning through world modeling, exploration, and self-reflection, with full ACE (Adaptive Context Engineering) integration for knowledge curation and semantic deduplication.
| # API Stress Test | |
| Create a Bash-based stress testing suite that simulates real user interactions with | |
| your API and measures system performance under load. | |
| ## Core Script (`api_stress_test.sh`) | |
| - Simulate realistic user flows with sequential API calls (GET, POST, PUT, DELETE) | |
| - DELETE requests should be executed last to clean up test data | |
| - Support bearer token authentication and custom headers | |
| - Base URL should be configurable |
| #ifndef MarchingCubesParams_h | |
| #define MarchingCubesParams_h | |
| #include <simd/simd.h> | |
| struct MarchingCubesParams { | |
| simd_uint3 cells; | |
| simd_float3 origin; | |
| simd_float3 cellSize; | |
| float isoLevel; | |
| simd_float3 centerA; |
| # export OPENAI_API_KEY=sk_proj-... | |
| # uv run gpt-5-voice-agent.py | |
| # /// script | |
| # dependencies = [ | |
| # "numba==0.61.2", | |
| # "openai==1.99.1", | |
| # "python-dotenv", | |
| # "fastapi[all]", | |
| # "uvicorn", |