LLM OS Framework

A rough idea in. A production prompt out.

Answer five questions. Get a complete prompt package — master prompt, system prompt, agent skills, multi-agent workflow, verification plan, harness config, and cost estimate.

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LLM OS Framework

Every output is built around the LLM-as-CPU model — identity, context, tools, verification loops, and environment grounding baked in.

Smart Clarifying Wizard

A few guided questions uncover your domain, constraints, and success criteria. The AI deduces the rest so you don't have to over-explain.

Agent Skills & Context Strategy

Get a curated skills list, context injection plan, and grounding strategy so your AI always knows what it can and cannot do.

Multi-Agent Workflow

Orchestrator + specialist structure with explicit handoff protocols. Built for tasks that need parallelism or delegated specialisation.

Verification & Environment Plan

Self-check checklists, human review gates, and environment constraints. No AI output ships unverified.

Cost Optimisation

Token estimates, model tier recommendations, prompt caching strategies, and batching tips to cut your AI spend by 50%+.

One goal. Eight outputs.

Every prompt package covers all the layers your AI system needs to work reliably in production.

Master Prompt

Ready-to-paste, zero placeholders

System Prompt

Identity, constraints, persona

Agent Skills

Curated capability list

Context Strategy

What to inject and how

Multi-Agent Flow

Orchestrator + specialists

Verification Plan

Self-check + human gates

Harness Config

Claude Code settings / hooks

Cost Estimate

Tokens, tiers, caching tips