AI Engineering

OMC Reference provides the OMC agent catalog, available tools, team pipeline routing, commit protocol, and skills registry for Claude Code sessions. Use it when delegating to agents, orchestrating teams, making commits, or invoking OMC skills.

Plan creates comprehensive, actionable work plans by interviewing the user for vague requests or generating directly from detailed requests, with optional consensus and review modes.

Ralph keeps working on a task until every user story in prd.json passes and is reviewer-verified. It wraps parallel execution with session persistence, automatic retry, and mandatory verification before completion.

Agent Governance provides patterns for adding safety, trust, and policy enforcement to AI agent systems. Use when building agents that call external tools, need audit trails, or require policy-based access controls.

Agent Skill Stack finds, evaluates, and assembles the smallest compatible set of AI Agent Skills for an end-to-end natural-language goal. Use it when planning multi-step workflows, auditing installed skills, checking conflicts, or building a project-specific Skill Stack.

Agentic Evaluation provides patterns and techniques for evaluating and improving AI agent outputs through iterative reflection, evaluator-optimizer loops, and rubric-based scoring. Use it when building quality-critical generation, test-driven code refinement, or LLM-as-judge systems.

AgentRC Policies help you pick, write, or apply JSON policies that change readiness scoring by disabling checks, overriding impact or level, and setting pass-rate thresholds. Use it for strict mode, AI-only scoring, org standards, or CI gating.

AI Prompt Engineering Safety Review analyzes AI prompts for safety, bias, security vulnerabilities, and effectiveness, then provides structured improvement recommendations using systematic frameworks and testing methodologies.

AI Readiness Assessment runs the AgentRC readiness scan on a repository and generates a static HTML dashboard at reports/index.html with maturity level, score, pillar breakdowns, and remediation plan. Use it when asked to audit, score, or assess the AI readiness of a codebase.

AI Ready guides users to install and review the ai-ready skill. After installation, the skill analyzes the codebase and generates AGENTS.md, copilot-instructions.md, CI workflows, and issue templates tailored to the stack.

AI Team Orchestration bootstraps and runs a lightweight multi-agent development team with producer, developer, and optional QA roles. Use it for project planning, implementation, independent testing, brainstorming, and preserving context across sessions.

Arize AI Provider Integration creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features.