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/olehsvyrydov/AI-development-teamWrote 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/commands/olehsvyrydov/ai-development-team/ai)<a href="https://agentmods.dev/commands/olehsvyrydov/ai-development-team/ai"><img src="https://agentmods.dev/badge/commands/olehsvyrydov/ai-development-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/commands/olehsvyrydov/ai-development-team/ai"><img src="https://agentmods.dev/badge/commands/olehsvyrydov/ai-development-team/ai.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00029 | $0.00120 |
| Opus 5.5 | $0.00012 | $0.00048 |
| Sonnet 5.5 | $0.00006 | $0.00024 |
| Haiku 4.5 | $0.00003 | $0.00012 |
Grade A, and why
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
/ai — AI/LLM Application Engineer
Invoke the ai-engineer skill (claude/skills/development/ai/ai-engineer/SKILL.md).
Builds LLM-powered product features with an eval-first discipline. Consult the workflow-engine; security review is almost always triggered (prompt injection, PII, keys). Hand off to mlops-engineer for training/serving infra.
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 · 10 lines · 29 tokens per session scan A 2dddeaade773
ai is a command published in the GitHub repository olehsvyrydov/AI-development-team (17 stars, last pushed 2d ago), licensed MIT. It adds 29 tokens to every session and 120 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
Other commands, from other repositories
t00-ai-dev
A set of instructions for building applications that use artificial intelligence, such as chatbots, document search, or text-generation tools. It covers Claude, retrieval-augmented generation (RAG), embeddings, and vector databases, which help find relevant documents for an AI answer.
boot
Start a new PromptKit prompt assembly session (alias for /bootstrap).
change-models
Set, change, or audit model preferences for pipeline agents — interactive 6-mode workflow (global/workspace prefs, per-agent overrides, first-run wizard, catalog refresh).
atlas
Architect the intelligence layer — RAG pipelines, model selection, embeddings, and evaluation for agentic systems.
sam-skills
Invoke Sam Altman — AI Strategy & Fundraising. Use for AI roadmaps, investor storytelling, platform architecture, and ecosystem strategy.
reprompt-orator
Optimize a prompt using Anthropic best practices.