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 programmatic-seogit 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/programmatic-seo)<a href="https://agentmods.dev/skills/fcakyon/claude-codex-settings/programmatic-seo"><img src="https://agentmods.dev/badge/skills/fcakyon/claude-codex-settings/programmatic-seo/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/programmatic-seo"><img src="https://agentmods.dev/badge/skills/fcakyon/claude-codex-settings/programmatic-seo.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 | $0.00044 | $0.01061 |
| Opus 5.5 | $0.00018 | $0.00424 |
| Sonnet 5.5 | $0.00009 | $0.00212 |
| Haiku 4.5 | $0.00004 | $0.00106 |
Grade A, and why
programmatic-seo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- programmatic-seo — 95% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Programmatic SEO
Building pages from a template and a data set works when each page answers a real query with something only your data can say. It fails the same way every time: a template with the variable swapped, published at volume, on queries nobody searches. That is the definition of a doorway page, and Google's spam policies name it.
So the question to settle before any of the mechanics is whether the data is worth a page.
Does the data carry it
Defensibility runs in this order, strongest first:
- Proprietary, because you generated it.
- Product-derived, from how your own users behave.
- User-generated, from your community.
- Licensed, where the license is exclusive.
- Public, which anyone can use and everyone already has.
A set built on public data competes with every other set built on the same public data, so it has to win on presentation, freshness, or aggregation instead. That is possible and it is a much harder brief. Say so rather than shipping 5,000 pages that restate a public API.
Then check demand actually exists: aggregate volume across the pattern, how it splits between head and long tail, and whether the trend is going anywhere. A pattern with 10,000 combinations and no searches for 9,000 of them is a 1,000-page opportunity.
Choosing a pattern
| You have | Consider |
|---|---|
| Proprietary data set | Directory, Profiles |
| A product with integrations | Integrations |
| A design or creative product | Templates, Examples |
| Several distinct audience segments | Personas |
| A local footprint | Locations |
| A utility or calculator | Conversions |
| Deep subject expertise | Glossary, Curation |
| A crowded competitive field | Comparisons |
references/playbooks.md covers the twelve patterns, each with its query shape, what data it needs, and how it usually fails.
Patterns layer, and layering is often where the real opportunity is: "best coworking spaces in Austin" is Curation crossed with Locations.
Making each page worth indexing
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.
- 1mo ago First seen · 75 lines · 44 tokens per session scan A 1d2251fc47de
programmatic-seo is a skill published in the GitHub repository fcakyon/claude-codex-settings (1,191 stars, last pushed today), licensed Apache-2.0. It adds 44 tokens to every session and 1,061 once invoked, about $0.0002 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 2026-09-03.
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