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 benjaminthomas/spec-driven-dev --skill generative-seogit clone --depth 1 https://github.com/benjaminthomas/spec-driven-devWrote 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/benjaminthomas/spec-driven-dev/generative-seo)<a href="https://agentmods.dev/skills/benjaminthomas/spec-driven-dev/generative-seo"><img src="https://agentmods.dev/badge/skills/benjaminthomas/spec-driven-dev/generative-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/benjaminthomas/spec-driven-dev/generative-seo"><img src="https://agentmods.dev/badge/skills/benjaminthomas/spec-driven-dev/generative-seo.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 | $0.00180 | $0.03515 |
| Opus 5.5 | $0.00072 | $0.01406 |
| Sonnet 5.5 | $0.00036 | $0.00703 |
| Haiku 4.5 | $0.00018 | $0.00351 |
Grade A, and why
generative-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 2mo 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 — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generative SEO (GEO) Operations
Runs an SEO + GEO program the same way a sharp in-house SEO operator would: technical audits, answer-first content built to be quoted by AI engines, an AI-citation tracker, competitor watch, and (draft-only) distribution. It is deliberately generic — first use in a repo spends a few minutes learning that project's facts, then behaves like a project-specific skill from then on.
Mode selection: the argument names the mode (content, audit, optimize,
competitors, citations, report, social). No argument → read the project's docs
(below), summarize current state, and recommend the highest-impact next action.
For the full evidence behind every rule below (which studies, what they found, why
each technique works) and the complete technical checklist, see
references/geo-methodology.md. Read it before an audit or before writing a
first piece of content in a new project; skip re-reading it on later runs in the
same project.
First run in a project: learn the project
Look for a config file at docs/seo/geo-config.md (or wherever the user says their
SEO docs live — some repos keep them in content/, marketing/, or a wiki instead).
If it exists, read it and skip to Read these first.
If it does not exist, this is the first run — ask the user (batch these, don't interview one question at a time):
- Product/brand name(s) — and critically, if the product is a sub-brand of a parent company or a different name than the company that builds it, get that distinction explicit now (e.g. "Acme Corp is the company; Acme Flow is the product we're marketing" or "same name, no distinction needed"). Getting this wrong (writing "is Acme Corp free?" when the product is Acme Flow) is a real, recurring mistake — nail it once here instead of guessing per-page later.
- Primary domain the content lives on (affects sitemap/robots checks and internal-link audits).
- Framework — Next.js, Astro, Remix, SvelteKit, plain static HTML, a CMS
(WordPress/Webflow/etc.), or something else. This determines where
sitemap/robots/metadata/JSON-LD live (see
references/geo-methodology.mdfor the per-framework map) — if unsure, look at the repo yourself first (package.json, top-level config files) before asking. - Where marketing/content pages live in the repo (a directory, a headless CMS, or "not in this repo" if content is managed elsewhere).
- Existing design system doc, if any (a
DESIGN.md, a Storybook, a Figma library) — new/edited pages should match it rather than invent a new look. - How to source real statistics for content — product analytics the user can query, a public dataset, or "external sources only." Never invent numbers regardless of the answer.
- Docs folder for this skill's own working files (default:
docs/seo/at repo root — offer this default rather than making the user think of one).
What ships with it
7 files 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.
- 2mo ago First seen · 256 lines · 180 tokens per session scan A 9bced6f1fa4b
generative-seo is a skill published in the GitHub repository benjaminthomas/spec-driven-dev (2 stars, last pushed today), licensed MIT. It adds 180 tokens to every session and 3,515 once invoked, about $0.0007 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 2026-08-31.
generative-seo compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| generative-seobenjaminthomas/spec-driven-dev | Skill | 2 | today | MIT | A | 180 | Claude Code |
| academic-paperhamzabellouch/agent-skills | Skill | 8 | 26d ago | MIT | A | 184 | Claude Code |
| deep-researchhamzabellouch/agent-skills | Skill | 8 | 26d ago | MIT | A | 291 | Claude Code |
| agent-platform-alert-configurationhamzabellouch/agent-skills | Skill | 8 | 26d ago | MIT | A | 106 | Claude Code |
| academic-paper-reviewerhamzabellouch/agent-skills | Skill | 8 | 26d ago | MIT | A | 187 | Claude Code |
| agent-platform-inferencehamzabellouch/agent-skills | Skill | 8 | 26d ago | MIT | A | 125 | Claude Code, Codex |
| gemini-omni-flash-apihamzabellouch/agent-skills | Skill | 8 | 26d ago | MIT | A | 79 | Claude Code, Codex |