setup-team

setup-team is a skill for Claude Code from SteveGJones/ai-first-sdlc-practices. It costs 55 tokens per session (8,465 once invoked), scanned B, original, MIT.

A setup guide for forming a software-development team of agents and choosing a development method for a project.

In plain words
What is it for?
Use it to choose between solo, single-team, programme, or assured development, inspect the current setup, and install matching team plugins.
Why use it?
It first checks existing plugins, agents, and skills, helping avoid duplicate installations and making recommendations fit the project’s language, technology, and support needs.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions Claude Code.

Part of the sdlc-core plugin — 10 skills, 5 agents, 2 hooks shipped together

Good fit Use it to choose between solo, single-team, programme, or assured development, inspect the current setup, and install matching team plugins.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/stevegjones/ai-first-sdlc-practices/setup-team
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add SteveGJones/ai-first-sdlc-practices --skill setup-team
Clone the repo
git clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practices

Made for: Claude Code.

Or install sdlc-core, the plugin that ships this one along with the rest of its 10 skills, 5 agents, 2 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for setup-team

README.md
[![agentmods](https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/setup-team/github.svg)](https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/setup-team)
Your own site
<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/setup-team"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/setup-team/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for setup-team

Your own site · 80×15
<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/setup-team"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/setup-team.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,465 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00055 $0.08465
Opus 5 $0.00028 $0.04233
Sonnet 5 $0.00011 $0.01693
Haiku 4.5 $0.00006 $0.00847

Measured 9d ago against content hash 553841018a81, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade B, and why

setup-team scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

- Read `~/.claude/settings.json` → `enabledPlugins` field (global installs)
plugins/sdlc-core/skills/setup-team/SKILL.md · 565 lines

How it starts

The opening of the file, as written. The whole thing — 565 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SDLC Team Setup

Configure the right agent team for this project by selecting an SDLC method, a project type, and installing the matching team plugins.

Steps

  1. Pre-check: inventory what's already installed

    Before making any recommendations, check what plugins, agents, and skills are already available — both globally and for this project.

    0a. Check installed plugins:

    • Read ~/.claude/settings.jsonenabledPlugins field (global installs)
    • Read .claude/settings.json (project-level) → enabledPlugins field (if it exists)
    • Merge both lists. For each sdlc-*@ai-first-sdlc entry: record as installed.
    • Also check for sdlc-knowledge-base@ai-first-sdlc, sdlc-programme@ai-first-sdlc, and sdlc-assured@ai-first-sdlc specifically — these may be relevant to the SDLC method question in step 3.

    0b. Check available agents:

    • Glob .claude/agents/**/*.md (project-level agents)
    • Note which come from installed plugins vs which are project-local

    0c. Check available skills:

    • List currently registered skills (the set Claude Code can see)

    0d. Present the pre-check results to the user before any recommendations:

    Current state:
    
    Installed SDLC plugins:
      ✓ sdlc-core@ai-first-sdlc (global)
      ✓ sdlc-team-common@ai-first-sdlc (global)
      ✗ sdlc-team-fullstack@ai-first-sdlc
      ✗ sdlc-lang-python@ai-first-sdlc
      ✗ sdlc-knowledge-base@ai-first-sdlc
      ✗ sdlc-programme@ai-first-sdlc
      ✗ sdlc-assured@ai-first-sdlc
    
    Available agents: N (from installed plugins)
    Available skills: M
    
    I'll only recommend what you don't already have.
    

    0e. Record the pre-check state for use in later steps — the recommendation output (step 8) will mark already-installed plugins with ✓ (already installed) instead of install commands, and the install command list (step 9) will exclude them.

  2. Check current team configuration

Look for .sdlc/team-config.json in the project root (or .claude/team-config.json as a fallback). If it exists, display the current formation and the recorded sdlc_method (if present) and ask if the user wants to reconfigure.

Read the full file on GitHub · 565 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 565 lines · 55 tokens per session scan B 553841018a81

Subscribe to this mod's changes

setup-team is a skill published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 8,465 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens