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 aeogit 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/aeo)<a href="https://agentmods.dev/skills/fcakyon/claude-codex-settings/aeo"><img src="https://agentmods.dev/badge/skills/fcakyon/claude-codex-settings/aeo/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/aeo"><img src="https://agentmods.dev/badge/skills/fcakyon/claude-codex-settings/aeo.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 | $0.00079 | $0.02699 |
| Opus 5.5 | $0.00032 | $0.01080 |
| Sonnet 5.5 | $0.00016 | $0.00540 |
| Haiku 4.5 | $0.00008 | $0.00270 |
Grade A, and why
aeo 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 17d 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Answer engine optimization
Help a product become discoverable and accurately recommended when prospective customers ask AI assistants buying questions. Adapt to software, physical goods, consumer products, services, marketplaces, and local businesses. Default to acquiring people who have not heard of the product. Success means the answer introduces the product or cites useful owned content without the buyer naming it.
Use the loop: buyer question → observed answer and sources → diagnosed gap → page or source improvement → repeated measurement → customer outcome.
Scope and evidence
Match the requested work: strategy, baseline audit, prompt set, source analysis, content brief, or performance review. Keep explicitly requested branded accuracy or conversion work scoped to that purpose. Use existing product material, research, analytics, and monitoring exports before requesting missing inputs. Ask only for information that changes the next decision. With no analytics or answer-engine access, produce a proposed measurement plan and label assumptions. Never fill missing observations with invented results.
Treat case-study growth figures as hypotheses to investigate, not expected returns. Neither a fixed prompt count nor a particular engine's traffic share transfers between products. AEO guidance alone does not authorize publishing, outreach, paid monitoring, or recurring jobs.
1. Define the buying context
Identify the product, canonical domain, brand aliases, category, target markets and languages, audience, substitutes, differentiators with evidence, buying constraints, and desired customer action. Distinguish the buyer, user, and decision-maker where useful. For consumer or local purchases, use the shopper's situation, location, and constraints instead of inventing enterprise personas.
Define one primary outcome, such as a paid order, qualified inquiry, booking, or activated trial. Keep intermediate events such as page views and signups separate. Record the normal purchase or sales lag and the available attribution window.
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.
- 17d ago First seen · 134 lines · 79 tokens per session scan A 9c9e8bafcfb0
aeo is a skill published in the GitHub repository fcakyon/claude-codex-settings (1,211 stars, last pushed today), licensed Apache-2.0. It adds 79 tokens to every session and 2,699 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 2026-10-29.
aeo compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| aeofcakyon/claude-codex-settings | Skill | 1.2k | today | Apache-2.0 | A | 79 | Claude Code |
| github-pr-workflowpaperclipai/paperclip | Skill | 114k | today | MIT | A | 39 | Claude Code, Codex |
| voiceChatCut-Inc/agent-plugin | Skill | 1.0k | 2d ago | Apache-2.0 | A | 124 | Claude Code |
| chatcut-plugin-basics-kimi-workChatCut-Inc/agent-plugin | Skill | 1.0k | 2d ago | Apache-2.0 | A | 152 | Claude Code, Codex |
| chatcut-verification-guideChatCut-Inc/agent-plugin | Skill | 1.0k | 2d ago | Apache-2.0 | A | 31 | Claude Code, Codex |
| githubinitializ/forge | Skill | 230 | yesterday | Apache-2.0 | A | 15 | Claude Code, Codex |
| dsh-plugin-publisherlovstudio/skills | Skill | 72 | 4d ago | MIT | A | 82 | Claude Code |