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 subhansh-dev/agent-maxxing --skill readmegit clone --depth 1 https://github.com/subhansh-dev/agent-maxxingWrote 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/subhansh-dev/agent-maxxing/readme)<a href="https://agentmods.dev/skills/subhansh-dev/agent-maxxing/readme"><img src="https://agentmods.dev/badge/skills/subhansh-dev/agent-maxxing/readme/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/subhansh-dev/agent-maxxing/readme"><img src="https://agentmods.dev/badge/skills/subhansh-dev/agent-maxxing/readme.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 | $0.00000 | $0.06442 |
| Opus 5.5 | $0.00000 | $0.02577 |
| Sonnet 5.5 | $0.00000 | $0.01288 |
| Haiku 4.5 | $0.00000 | $0.00644 |
Grade A, and why
README 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.
How it starts
The opening of the file, as written. The whole thing — 593 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Maxxing
95+ production-ready skills, 19 UI components, and 7 system prompts extracted from the world's best AI agents. Drop them into any agent — Claude Code, Codex, Cursor, OpenCode — and it instantly becomes elite.
Think of it as: Giving your AI agent a brain transplant — it inherits the engineering judgment of GPT-5.5, the reasoning of Claude Fable 5, the frontend taste of Claude Design, and the tool orchestration of Gemini CLI.
⚡ Quick Start
Step 1: Clone the repo
git clone https://github.com/subhansh-dev/agent-maxxing.git
Step 2: Install for your agent
Claude Code (user-wide):
cp -r agent-maxxing ~/.claude/skills/agent-maxxing
Claude Code (project-scoped):
cp -r agent-maxxing .claude/skills/agent-maxxing
Codex CLI (user-wide):
cp -r agent-maxxing ~/.codex/skills/agent-maxxing
OpenCode (user-wide):
cp -r agent-maxxing ~/.opencode/skills/agent-maxxing
Cursor (project-scoped):
cp -r agent-maxxing .cursor/skills/agent-maxxing
Continue (project-scoped):
cp -r agent-maxxing .continue/skills/agent-maxxing
Kilo Code (project-scoped):
cp -r agent-maxxing .kilocode/skills/agent-maxxing
Step 3: Restart your agent
The agent auto-discovers all .md files with YAML frontmatter on next session.
Step 4: Use the skills
Just describe what you want. The agent picks the right skill automatically:
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 · 593 lines · 0 tokens per session scan A 0b2391d8c994
README is a skill published in the GitHub repository subhansh-dev/agent-maxxing (2 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 6,442 tokens. 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 2026-08-31.
Other skills, from other repositories
gh-find-prs
Survey open Codewhale PRs and triage each for mergeability and disposition against the real landing branch.
review
Diff-scoped correctness review that reads the codebase around the change — callers, contracts, and invariants — and returns line-anchored findings ranked by severity with confidence, then a merge-risk verdict. Use for reviewing a PR, diff, or named change set. Not for style review, approvals-as-rubber-stamp, or…
simplify
Review recent code changes for reuse, code quality, and efficiency, then directly apply straightforward cleanup improvements. Use when the user wants a post-implementation cleanup pass, pre-PR polish, or asks to simplify/refine recent changes. Invoke with /simplify or /simplify .
find-simplifications
Use for a periodic repo-wide sweep of qwen-code for accumulated excess surface — dead components and files, orphaned locale keys, exports nothing consumes, added-then-removed scaffolding — filing candidates on a tracking issue and landing only what a maintainer has said yes to. Repo-wide and evidence-first; every…
review-this-branch
Run the nohuman review gate (fresh-session adversarial reviewer + tamper guard) over the current branch or a GitHub pull request, with no server, no database, and no onboarding, and relay the pass/fail checklist.
fabric-spec
Starts a persistent Pi Fabric spec supervisor that audits the main session against a feature design spec and steers only when a requirement lacks verified evidence. Use for strict, unblocked spec compliance while the main agent keeps full freedom to orchestrate.