SkillKit is a package manager for AI coding-agent skills that installs skills from many sources and translates them between the different formats used by coding agents. It helps developers share skills across agents such as Claude Code, Cursor, Copilot, and Codex.
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 rohitg00/skillkit --skill red-green-refactorgit clone --depth 1 https://github.com/rohitg00/skillkitWrote 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/rohitg00/skillkit/red-green-refactor)<a href="https://agentmods.dev/skills/rohitg00/skillkit/red-green-refactor"><img src="https://agentmods.dev/badge/skills/rohitg00/skillkit/red-green-refactor/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/rohitg00/skillkit/red-green-refactor"><img src="https://agentmods.dev/badge/skills/rohitg00/skillkit/red-green-refactor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00090 | $0.01319 |
| Opus 5.5 | $0.00036 | $0.00528 |
| Sonnet 5.5 | $0.00018 | $0.00264 |
| Haiku 4.5 | $0.00009 | $0.00132 |
Grade A, and why
red-green-refactor 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 — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Red-Green-Refactor Methodology
You are following the RED-GREEN-REFACTOR cycle for test-driven development. Every new feature, bug fix, or behavior change starts with a failing test.
The Cycle
1. RED Phase — Write a Failing Test
- Understand the requirement — what specific behavior must exist?
- Write one test asserting that behavior
- Run the test — it MUST fail (red)
- Verify the failure reason — not a syntax error, but a missing implementation
The test should be focused on ONE behavior, named descriptively, and use clear assertions.
Executable example (Jest):
// calculateTotal.test.js
const { calculateTotal } = require('./calculateTotal');
describe('calculateTotal', () => {
it('should apply 10% discount when total exceeds 100', () => {
const items = [{ price: 60 }, { price: 60 }]; // total = 120
expect(calculateTotal(items)).toBe(108); // 120 * 0.90
});
});
Running this now produces: Cannot find module './calculateTotal' — correct RED state.
2. GREEN Phase — Make the Test Pass
Write the minimum code needed to pass the test. Don't add anything extra.
// calculateTotal.js
function calculateTotal(items) {
const total = items.reduce((sum, item) => sum + item.price, 0);
return total > 100 ? total * 0.9 : total;
}
module.exports = { calculateTotal };
Run the test — it passes. GREEN achieved. Stop here; resist adding more logic.
3. REFACTOR Phase — Improve the Code
With a passing test as your safety net, clean up the implementation. Run tests after every change.
// calculateTotal.js — refactored for clarity
const DISCOUNT_THRESHOLD = 100;
const DISCOUNT_RATE = 0.9;
function calculateTotal(items) {
const subtotal = items.reduce((sum, { price }) => sum + price, 0);
return subtotal > DISCOUNT_THRESHOLD ? subtotal * DISCOUNT_RATE : subtotal;
}
module.exports = { calculateTotal };
Test still passes — GREEN maintained. Constants now communicate intent.
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 · 169 lines · 90 tokens per session scan A a20e71fb1428
red-green-refactor is a skill published in the GitHub repository rohitg00/skillkit (1,558 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 90 tokens to every session and 1,319 once invoked, about $0.0004 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 skills, from other repositories
subagent-driven-development
Orchestrating sub-agents through TDD phases for complex features.
test-driven-development
Red-green-refactor TDD implementation cycle.
writing-plans
Convert test scenarios into ordered implementation plans for TDD.
fix-bug
Fixes a bug through test-driven debugging, reproduces it with a failing test, locates the root cause with evidence (file:line), then applies the smallest fix that resolves it without refactoring unrelated code. Use when the user wants to fix a bug, debug an issue, resolve an error, or investigate a failing test. Not…
am-command-build
Implement the next task incrementally — build, test, verify, commit.
brainstorming
Requirements exploration and test scenario generation for TDD.