A-Team

Canonical validation checklist for generated team structures, executed by a fresh-context verifier

Entry point that makes this session adopt the Team Architect workflow to run the full team design process

Start the A-Team Codex coordinator workflow for designing or restructuring teams

Rewrite generated prompts to be sharper, shorter, and more executable without changing meaning

Apply Codex-native prompt patterns for agents, skills, rules, and project instructions

Validate that a generated Codex team is structurally complete and internally consistent

Provide systematic prompt optimization methodology to improve instruction quality while preserving original characteristics

Reference library of Anthropic-official prompt engineering patterns, templates, and Claude 4.6 best practices for generation agents

Capture repeated A-Team design patterns as reusable instincts for later sessions

Check whether a proposed role split is too coarse, too fine, or balanced

Apply consistent frontmatter, structure, and path references across authored markdown files

Decompose workflow responsibilities into a clean, non-overlapping role set

Create or improve a skill by using the system skill when available and the legacy local bundle as fallback

Search external sources for reusable skills before designing a new one

Extract precise team requirements through staged, single-direction questioning

Evaluate whether a proposed agent graph supports safe handoffs and useful parallel work

Instinct-based learning system that captures team design patterns via hooks and evolves them into reusable knowledge

Define universal writing standards, format specifications, and quality requirements for all .md files

Provide methodology and decision framework for decomposing team responsibilities into agent roles with appropriate granularity

Search external skill sources and evaluate candidates for reuse before creating custom skills

Provide framework for analyzing team structure rationality and evaluating collaboration topology efficiency between agents

Provide quantitative methods for evaluating whether agent decomposition granularity is appropriate

Provide in-depth interview methodology for extracting clear actionable requirements from vague descriptions