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.
git clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practicesWrote 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.
[](https://agentmods.dev/plugins/stevegjones/ai-first-sdlc-practices/sdlc-team-ai)<a href="https://agentmods.dev/plugins/stevegjones/ai-first-sdlc-practices/sdlc-team-ai"><img src="https://agentmods.dev/badge/plugins/stevegjones/ai-first-sdlc-practices/sdlc-team-ai/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.
<a href="https://agentmods.dev/plugins/stevegjones/ai-first-sdlc-practices/sdlc-team-ai"><img src="https://agentmods.dev/badge/plugins/stevegjones/ai-first-sdlc-practices/sdlc-team-ai.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
sdlc-team-ai scanned grade A with 0 findings 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 1mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
{
"name": "sdlc-team-ai",
"version": "1.0.0",
"description": "AI/ML specialist agents — architects, prompt engineers, RAG designers",
"author": { "name": "SteveGJones" },
"keywords": ["sdlc", "ai", "ml", "agents"]
}
What it installs
The manifest is a name and a version. 14 agents travel with it, and installing the plugin installs all of them — 644 tokens a session between them. Each is measured on its own page, and each can be installed alone.
- Agent ai-team-transformer A 39 tokens
- Agent mcp-test-agent A 36 tokens
- Agent orchestration-architect A 49 tokens
- Agent a2a-architect A 49 tokens
- Agent ai-devops-engineer A 48 tokens
- Agent ai-test-engineer A 51 tokens
- Agent context-engineer A 45 tokens
- Agent langchain-architect A 51 tokens
- Agent mcp-server-architect A 42 tokens
- Agent rag-system-designer A 40 tokens
- Agent mcp-quality-assurance A 35 tokens
- Agent agent-developer B 52 tokens
- Agent prompt-engineer B 52 tokens
- Agent ai-solution-architect C 55 tokens
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.
- 1mo ago First seen · 8 lines scan A f978c721456f
sdlc-team-ai is a plugin published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 19d ago), licensed MIT. Its token cost is not measured: this kind of file is read by the harness, not the model. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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