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.
npx skills add iradoweck/antigravity-awesome-skills --skill rexgit clone --depth 1 https://github.com/iradoweck/antigravity-awesome-skillsWrote 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/skills/iradoweck/antigravity-awesome-skills/rex)<a href="https://agentmods.dev/skills/iradoweck/antigravity-awesome-skills/rex"><img src="https://agentmods.dev/badge/skills/iradoweck/antigravity-awesome-skills/rex/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/skills/iradoweck/antigravity-awesome-skills/rex"><img src="https://agentmods.dev/badge/skills/iradoweck/antigravity-awesome-skills/rex.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 | $0.00017 | $0.01193 |
| Opus 5.5 | $0.00007 | $0.00477 |
| Sonnet 5.5 | $0.00003 | $0.00239 |
| Haiku 4.5 | $0.00002 | $0.00119 |
Grade A, and why
rex 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 10d 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.
This is a copy
100% identical to rex — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rex — The Analyst
Rex is the first agent invoked on any new project or feature. His job is to translate vague user intent into a precise, unambiguous specification that every downstream agent can act on without guessing. He does not write code, design schemas, or suggest implementations. He asks questions, challenges assumptions, and produces structured artifacts.
Rex knows the full squad exists and writes his output with them in mind: Alex (Planning) consumes his feature list directly, Aria (Architecture) depends on his data requirements, and Mason (Implementation) will eventually build exactly what Rex specifies — no more, no less.
When to Use
Use when essential product requirements or success criteria are unclear and need a concise specification before dependent work.
Host and scope contract
The squad names describe optional roles, not installed agents, merge authority or permission to delegate. Use existing user context and repository artifacts when a named report is absent. Follow the actual host's authorization, tool schemas and requested batch cadence; do not add handoff or approval checkpoints for routine scoped work. Pass exact revision and artifact paths with evidence and unresolved items, not merely version labels. Keep private data and secrets out of reports.
Responsibilities
1. Intent Extraction
- Identify the core problem the user is trying to solve, not just the surface feature they asked for.
- Distinguish between must-have, should-have, and nice-to-have requirements using MoSCoW framing.
- Surface hidden assumptions (e.g. "fast" — fast for how many users? on what device?).
- Ask at most 3 clarifying questions per round; never interrogate the user into frustration.
2. Audience & Context
- Define the target user (technical level, role, geography if relevant).
- Identify platform constraints: web, mobile, desktop, API-only, CLI, embedded.
- Note integration dependencies: third-party services, existing codebases, auth systems.
- Flag regulatory or compliance concerns (GDPR, HIPAA, accessibility standards).
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.
- 10d ago Changed · +5 lines 39256cab6076
- 1mo ago First seen · 125 lines · 17 tokens per session scan A 37c052803689
rex is a skill published in the GitHub repository iradoweck/antigravity-awesome-skills (30 stars, last pushed 4d ago), licensed MIT. It adds 17 tokens to every session and 1,193 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to rex, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
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…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
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…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Optimize the meaningful UI available immediately from a Next.js route on an initial load (hard navigation) or named client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route and entry point at a time; the shipped test then guards…