OpenSEO is an open-source SEO platform for keyword research, rank tracking, competitor analysis, backlink analysis, site audits, and AI visibility work. It connects SEO data to AI agents through an MCP server and reusable agent skills, while allowing users to supply their own DataForSEO API key and self-host the tool. Catalogue add-ons guide agents through OpenSEO's SEO workflows.
Borrowing it
Nothing to install: this file belongs to every-app/open-seo. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/every-app/open-seo/main/.agents/skills/openseo-review-web-content/SKILL.mdgit clone --depth 1 https://github.com/every-app/open-seoWrote 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/every-app/open-seo/openseo-review-web-content)<a href="https://agentmods.dev/skills/every-app/open-seo/openseo-review-web-content"><img src="https://agentmods.dev/badge/skills/every-app/open-seo/openseo-review-web-content/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/every-app/open-seo/openseo-review-web-content"><img src="https://agentmods.dev/badge/skills/every-app/open-seo/openseo-review-web-content.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 | $0.00058 | $0.00811 |
| Opus 5 | $0.00029 | $0.00405 |
| Sonnet 5 | $0.00012 | $0.00162 |
| Haiku 4.5 | $0.00006 | $0.00081 |
Grade A, and why
openseo-review-web-content 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 13d 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
2 near-identical copies found in the catalogue:
- openseo-review-web-content — 100% identical, 0 lines differ
- upgradeseo-review-web-content — 97% identical, 14 lines differ
How it starts
The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenSEO Web Content
Everything we publish must be traceable to what the product actually does and costs, and must read like a practitioner wrote it. The reader's interest comes first: teach something they can act on, and answer straight — including when the honest answer is "no" or "it costs money."
Principles
- Traceable truth. Every capability claim, price, and screenshot is verifiable against the code, the fact sheet (
src/server/features/onboarding/openseo-fact-sheet.md), or the live product. If you can't point to where it's true, it doesn't ship. - Lead with the real answer. "No," "not unlimited," and "it costs money" are complete answers. Hedging that lets a reader infer something more flattering than the truth is a way of misleading them.
- Honest pricing, with its reasoning. Quality SEO data is expensive everywhere — that's why the big suites run $100/month and up. OpenSEO is the affordable option: $10/month, free to start. Never simply "free."
- Sound like a person. Fix AI tells by restating the underlying claim plainly, not by polishing the flourish. The deslop skill is the reference for what to hunt and how to fix it.
- Reader-first altitude. Guides teach actionable SEO that stands on its own — not product documentation, not generic filler. Credit free resources to their real owners (Google's autocomplete, the reader's own Search Console).
- One bar, whole surface. When a standard improves, sweep everything to it — all the FAQs, all the pages — not just the instance that got noticed.
- Playbook terminology. Call each approach within any OpenSEO playbook a "strategy," never a "play." Use "workflow" for the steps readers execute; use "playbook" only for the complete collection.
Questions to ask while reviewing
- If a reader trusted every claim and screenshot, then opened OpenSEO right now, where would reality not match?
- Does each answer open with the real answer, or quietly steer toward a more flattering inference?
- Read the sharpest line aloud: would a person say it that way?
- Is anything called free that actually costs credits?
- Is this teaching the reader something useful on its own, or drifting into product docs or padding?
- Does every link, image, and example on the page earn its place for the reader?
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.
- 13d ago First seen · 38 lines · 58 tokens per session scan A 52dc4858851d
openseo-review-web-content is a skill published in the GitHub repository every-app/open-seo (18,432 stars, last pushed 9d ago), licensed MIT. It adds 58 tokens to every session and 811 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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