robzolkos

description	argument-hint	model
Interview me about the plan	plan	opus

Read this plan file $1 and interview me in detail using the AskUserQuestionTool about literally anything: technical implementation, UI & UX, concerns, tradeoffs, etc. but make sure the questions are not obvious.

Chizaruu

#!/usr/bin/env tsx
/* eslint-disable @typescript-eslint/no-unused-vars */
/* eslint-disable no-console */
/* eslint-disable camelcase */

/**
 * Complete Supabase Type Generator - Schema-File First with Index Support
 *
 * This script:
 * 1. Reads SQL schema files from your Supabase directory (default for --local)

ruvnet

Claude Flow treats memory as the backbone and MCP tools as the hands. You get concurrent agents that coordinate cleanly, keep context tight, and ship durable artifacts without dragging long text through prompts. It feels like an ops layer for intelligence.

The stack is simple. Claude Code as the client. Claude Flow as the MCP server. SQLite memory at .swarm/memory.db for state, events, patterns, workflow checkpoints, and consensus. Artifacts hold the big payloads. Manifests in memory link everything with ids, tags, and checksums.

Coordination is explicit. Agents write hints to a shared blackboard, gate risky steps behind consensus, and record every transition as an event. Hooks inject minimal context before tools run and persist verified outcomes after. Small bundles in, durable facts out.

Planning keeps runs stable. Use GOAP to sequence actions with clear preconditions. Use OODA to shorten loops.

Observe metrics, orient with patterns, decide through votes, act with orchestration. Topology adapts from hi

jdjkelly

import { App, } from '@slack/bolt';
import { Anthropic } from '@anthropic-ai/sdk';

const app = new App({
  signingSecret: process.env.SLACK_SIGNING_SECRET,
  token: process.env.SLACK_BOT_TOKEN,
});

const anthropic = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });