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 adriannoes/awesome-agentic-ai --skill generategit clone --depth 1 https://github.com/adriannoes/awesome-agentic-aiWrote 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/adriannoes/awesome-agentic-ai/generate)<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/generate"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/generate/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/adriannoes/awesome-agentic-ai/generate"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/generate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 130 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00051 | $0.01121 |
| Opus 5 | $0.00026 | $0.00561 |
| Sonnet 5 | $0.00010 | $0.00224 |
| Haiku 4.5 | $0.00005 | $0.00112 |
Grade A, and why
generate 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.
How it starts
The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Playwright Tests
Generate production-ready Playwright tests from a user story, URL, component name, or feature description.
Input
$ARGUMENTS contains what to test. Examples:
"user can log in with email and password""the checkout flow""src/components/UserProfile.tsx""the search page with filters"
Steps
1. Understand the Target
Parse $ARGUMENTS to determine:
- User story: Extract the behavior to verify
- Component path: Read the component source code
- Page/URL: Identify the route and its elements
- Feature name: Map to relevant app areas
2. Explore the Codebase
Use the Explore subagent to gather context:
- Read
playwright.config.tsfortestDir,baseURL,projects - Check existing tests in
testDirfor patterns, fixtures, and conventions - If a component path is given, read the component to understand its props, states, and interactions
- Check for existing page objects in
pages/ - Check for existing fixtures in
fixtures/ - Check for auth setup (
auth.setup.tsorstorageStateconfig)
3. Select Templates
Check templates/ in this plugin for matching patterns:
| If testing... | Load template from |
|---|---|
| Login/auth flow | ../pw/templates/auth/login.md |
| CRUD operations | templates/crud/ |
| Checkout/payment | templates/checkout/ |
| Search/filter UI | templates/search/ |
| Form submission | templates/forms/ |
| Dashboard/data | templates/dashboard/ |
| Settings page | templates/settings/ |
| Onboarding flow | templates/onboarding/ |
| API endpoints | templates/api/ |
| Accessibility | templates/accessibility/ |
Adapt the template to the specific app — replace {{placeholders}} with actual selectors, URLs, and data.
4. Generate the Test
Follow these rules:
Structure:
import { test, expect } from '@playwright/test';
// Import custom fixtures if the project uses them
test.describe('Feature Name', () => {
// Group related behaviors
test('should <expected behavior>', async ({ page }) => {
// Arrange: navigate, set up state
// Act: perform user action
// Assert: verify outcome
});
});
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 First seen · 145 lines · 51 tokens per session scan A 995f6cf36563
generate is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 12d ago), licensed MIT. It adds 51 tokens to every session and 1,121 once invoked, about $0.0003 per session on Opus 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.
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