Execute SkillFoundry agent pipeline

Run all PRD-driven agents across database, backend, and frontend layers until the full development lifecycle completes.

prompt
→ Claude
# SkillFoundry Framework — Agent Instructions for OpenAI Codex Version 5.22.1 | Hexa-Platform: Claude Code · Cursor · Copilot · Codex · Gemini · Grok Build | 107 Skills | 20 MCP Tool Agents --- ## What This Is SkillFoundry (Agents & Skills) is a production-ready AI development framework with 60 specialized agents covering the full software development lifecycle. This file provides always-on context for OpenAI Codex CLI. ## Philosophy - Cold-blooded logic over flattery — Honest, structured, production-ready evaluations only - ONLY REAL LOGIC — No placeholders, TODOs, mocks, or stubs. Every feature works end-to-end - Three-Layer Completeness — Every feature verified across DATABASE → BACKEND → FRONTEND - PRD-First Development — Non-trivial features start with a Product Requirements Document - Implement Test Iterate — Every feature tested before considered done ## How to Use Skills Each SkillFoundry agent is available as a Codex Skill in .agents/skills/ . Invoke explicitly or let Codex auto-select based on your prompt. Explicit invocation: $go # Execute all PRDs from genesis/ $coder
claude-code · codex · cursor

Source: samibs

More automation loops

Set and ship autonomous goals

/goalnew

Run a persistent goal autonomously until completion, routing each task to the optimal model for cost and capability.

prompt
→ Claude
/goal <objective · /loop <task | Set a persistent goal · run autonomously until complete (≤25 turns) |
automationlow risk

Schedule batch jobs with Dapr bindings

/schedulenew

Schedule recurring batch jobs and cleanup tasks using Dapr cron bindings, running on your defined cadence.

prompt
→ Claude
/Schedule | bindings.cron | Batch jobs, cleanup tasks |
automationmedium risk

Run long-horizon tasks with ralph

/ralph★ Anthropicnew

Execute autonomous multi-step work against a completion promise without human intervention until done.

prompt
→ Claude
/ralph-loop "Your task description" --completion-promise "DONE
automationlow risk