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/test-audit/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/test-audit)<a href="https://agentmods.dev/skills/every-app/open-seo/test-audit"><img src="https://agentmods.dev/badge/skills/every-app/open-seo/test-audit/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/test-audit"><img src="https://agentmods.dev/badge/skills/every-app/open-seo/test-audit.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 | $0.00080 | $0.02518 |
| Opus 5.5 | $0.00032 | $0.01007 |
| Sonnet 5.5 | $0.00016 | $0.00504 |
| Haiku 4.5 | $0.00008 | $0.00252 |
Grade A, and why
test-audit 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 16d 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 — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Audit
Three modes, one value bar. Authoring mode gates every new or changed test at write time. Audit mode runs focused sweeps for tests that re-assert source, duplicate stronger proof, couple behavior to implementation, or keep test-only production seams alive. Campaign mode reviews every test file with a per-test verdict when the maintainer asks to prune the whole suite; see Campaign mode. Optimize for confidence, not deletion count. Land one coherent batch per PR; continue broad audits as separate follow-ups.
The repository's own rules live in the "Testing" section of AGENTS.md. This
skill is the procedure for applying them; when the two disagree, AGENTS.md
wins and this file needs an update.
Authoring gate
Before adding a test, answer four questions. A missing answer means do not add it yet:
- What observable behavior, invariant, or independent contract does it protect?
- What credible regression makes it fail?
- Why does existing coverage not already catch that failure? Each contract has
one primary owner at the strongest boundary (usually the service or the MCP
tool handler, not the repository or a private helper). Another layer needs
its own distinct risk. Prefer extending a table-driven case or a shared
factory (
ga4-test-fixtures.ts,tool-test-support.ts) over a near-duplicate test, and consolidate duplicated setup in the same change. - Does it need a production seam (export, flag, wrapper, injection hook) that
no production caller needs? If yes, test at the real boundary instead.
Grep the whole repo for callers, not just
src/;scripts/counts.
Then check the test against every junk pattern; a match fails the gate unless the retention bar names the contract it independently guards. A test that would break under behavior-preserving refactoring is asserting implementation, not behavior; rewrite it at the owning boundary before landing it.
Bug regression tests must fail on the pre-fix code for the intended reason and pass after the fix. A regression test that never demonstrably failed proves the mock, not the fix. One regression at the owner boundary covers the bug; do not replay it at every layer it crosses.
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.
- 16d ago First seen · 231 lines · 80 tokens per session scan A 97a44695d48c
test-audit is a skill published in the GitHub repository every-app/open-seo (23,850 stars, last pushed 3d ago), licensed MIT. It adds 80 tokens to every session and 2,518 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 2026-10-01.
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