team-builder
Interactive agent picker for composing and dispatching parallel teams
npx skills add mturac/everything-openai-codex --skill team-builder --agent codex
Same command for any agent — swap --agent for claude-code, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Team Builder Interactive menu for browsing and composing agent teams on demand. Works with flat or domain-subdirectory agent collections. ## When to Use - You have multiple agent personas (markdown files) and want to pick which ones to use for a task - You want to compose an ad-hoc team from different domains (e.g., Security + SEO + Architecture) - You want to browse what agents are available before deciding ## Prerequisites Agent files must be markdown files containing a persona prompt (identity, rules, workflow, deliverables). The first `# Heading` is used as the agent name and the first paragraph as the description. Both flat and subdirectory layouts are supported: **Subdirectory layout** — domain is inferred from the folder name: ``` agents/ ├── engineering/ │ ├── security-engineer.md │ └── software-architect.md ├── marketing/ │ └── seo-specialist.md └── sales/ └── discovery-coach.md ``` **Flat layout** — domain inferred from shared filename prefixes. A prefix counts as a domain when 2+ files share it. Files with unique prefixes go to "General". Note: the algorithm splits at the first `-`, so multi-word domains (e.g., `product-management`) should use the subdirectory layout i
- When to Use
- Prerequisites
- Configuration
- How It Works
- Step 1: Discover Available Agents
- Step 2: Present Domain Menu
- Step 3: Handle Selection
- Step 4: Spawn Agents in Parallel
- Step 5: Synthesize Results
- Rules
- Examples
What does the team-builder skill do?
Interactive agent picker for composing and dispatching parallel teams
How do I install it?
Run `npx skills add mturac/everything-openai-codex --skill team-builder --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mturac/everything-openai-codex, a repository with 84 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.