claude-codex-settings is a collection of configurations and reusable extensions for Claude Code, OpenAI Codex, Cursor, and related coding tools. Developers use its skills, commands, hooks, agents, plugins, and MCP servers to shape coding-agent workflows and connect alternative model APIs. The catalogue entries are components of this collection that can be installed into supported coding tools.
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 fcakyon/claude-codex-settings --skill ui-regressiongit clone --depth 1 https://github.com/fcakyon/claude-codex-settingsWrote 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/fcakyon/claude-codex-settings/ui-regression)<a href="https://agentmods.dev/skills/fcakyon/claude-codex-settings/ui-regression"><img src="https://agentmods.dev/badge/skills/fcakyon/claude-codex-settings/ui-regression/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/fcakyon/claude-codex-settings/ui-regression"><img src="https://agentmods.dev/badge/skills/fcakyon/claude-codex-settings/ui-regression.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 | $0.00082 | $0.01438 |
| Opus 5.5 | $0.00033 | $0.00575 |
| Sonnet 5.5 | $0.00016 | $0.00288 |
| Haiku 4.5 | $0.00008 | $0.00144 |
Grade A, and why
ui-regression 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 yesterday.
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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
UI Regression
Verify that the requested UI works from entry to outcome. Cover the changed surface and its dependencies, without expanding a small edit into an unrelated product audit.
Use the browser tools available and permitted in the current environment. When using the agent-browser CLI, read its skill first. This workflow does not require a particular browser driver or local source access.
Scope and evidence
- Identify the target URL or extension build, environment, affected screens, actions, roles, locales, and dimensions. Inspect source and API contracts when available. For deployed-only QA, derive coverage from visible navigation and the requested workflows.
- Keep a compact coverage ledger in working notes or an existing artifact: screen/action, locale/account state, expected outcome, observed result, evidence, and pass/fail/blocked/not-applicable. Inventory before testing, then update as results arrive. A screenshot does not cover its buttons.
- Record the tested revision or deployed version when observable, browser, viewport, data source, and build mode. Mark unknown revisions explicitly. Compare visuals with matching content, state, and dimensions when a baseline exists.
- When asked to test every function, account for every inventoried action. Do not silently omit blocked checks or impose an arbitrary bug-count stopping point.
Real behavior and safe boundaries
- Exercise the actual UI, API, and persistence together against an authorized environment. A mocked UI test plus a direct endpoint test does not prove their integration.
- Use fixtures or an isolated test environment to reproduce loading, empty, failure, and recovery states. Do not inject failures into production. Keep fixture results separate from live integration and packaged-extension results. Never present simulated playback as real third-party playback.
- Use dedicated test accounts and test-mode resources for side effects. Existing task authorization still applies. QA alone does not authorize payments, emails, production mutations, or broader access. Prefer read-only deployed checks unless the requested workflow authorizes more.
- If credentials, browser capabilities, source access, or external dependencies block a check, record the exact boundary. Continue independent checks. Never bypass browser protections or substitute a mock to claim a pass.
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.
- yesterday First seen · 60 lines · 82 tokens per session scan A d9a2d16579cb
ui-regression is a skill published in the GitHub repository fcakyon/claude-codex-settings (1,178 stars, last pushed yesterday), licensed Apache-2.0. It adds 82 tokens to every session and 1,438 once invoked, about $0.0003 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 2026-10-15.
Other skills, from other repositories
build-verification-skill
Build this project's verification skill - a small CLI that drives the running app and captures evidence, plus a feature map of what exists and how to reach it - and the CI check that keeps the map current. Use when asked to 'build a verification skill', 'let the agent drive the app', 'make a feature map', 'the agent…
e2e-testing-patterns
Master end-to-end testing with Playwright and Cypress to build reliable test suites that catch bugs, improve confidence, and enable fast deployment. Use when implementing E2E tests, debugging flaky tests, or establishing testing standards.
browser-testing-with-devtools
Tests in real browsers via Chrome DevTools MCP. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data. Requires the chrome-devtools MCP server to be…
qa/e2e-playwright
A method for writing Playwright end-to-end tests, which automate a browser to verify complete user journeys. It covers setup, reusable page objects, login reuse, API mocking, visual checks, multiple browsers and screen sizes, CI, and debugging.
selectors
Selector strategy, exploration-first workflow, locator priority order (getByRole then getByLabel then getByPlaceholder then getByText then getByTestId), and feedback/validation-message selector rules for Playwright page objects. Use when creating page objects, writing or updating locators, generating UI tests, or…
Console Error Hunter
Systematically detect, capture, and categorize browser console errors, warnings, and unhandled exceptions during automated test execution.