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/maintain-greptile-rules/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/maintain-greptile-rules)<a href="https://agentmods.dev/skills/every-app/open-seo/maintain-greptile-rules"><img src="https://agentmods.dev/badge/skills/every-app/open-seo/maintain-greptile-rules/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/maintain-greptile-rules"><img src="https://agentmods.dev/badge/skills/every-app/open-seo/maintain-greptile-rules.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00097 | $0.00928 |
| Opus 5 | $0.00048 | $0.00464 |
| Sonnet 5 | $0.00019 | $0.00186 |
| Haiku 4.5 | $0.00010 | $0.00093 |
Grade A, and why
maintain-greptile-rules 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 9d 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:
- maintain-greptile-rules — 100% identical, 0 lines differ
- maintain-greptile-rules — 98% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Maintain Greptile rules
Keep .greptile/ high-signal. A review finding is evidence to evaluate, not automatically a new rule.
1. Verify the finding
- Reproduce or trace the finding against the current repository, including the relevant call path, tests, and intentional exceptions.
- Read
.greptile/config.json,.greptile/rules.md, and.greptile/files.jsonbefore proposing a change. - Distinguish a newly introduced risk from adjacent legacy debt. Do not encode an unverified assumption or a one-off implementation detail.
- Repository absence is not policy evidence. If a reviewer infers a preference only because no current example exists, leave Greptile, code, and CI unchanged unless an owner explicitly adopts the policy.
2. Route it to the right mechanism
- One-off bug: fix the code and add a focused regression test. Do not add a Greptile rule.
- Verified deterministic policy violation: prefer TypeScript, Oxlint, Knip, a focused test, or CI.
- Repeatable, diff-enforceable invariant: add or refine a scoped structured rule in
.greptile/config.json. - Architecture, preference, or false-positive calibration: update
.greptile/rules.md. - Canonical implementation Greptile should consult: add a narrowly scoped reference in
.greptile/files.json. - Small workflow friction: use the
papercutsskill and log it in.agents/PAPERCUTS.md.
3. Apply the promotion bar
Promote a finding only when all applicable checks pass:
- It is verified against current code.
- A future reviewer can observe it from the diff and relevant call path.
- It is repository-specific or materially improves false-positive calibration.
- It is likely to recur, or its impact is high enough to justify prevention: authorization, security, billing, data loss, or cross-database correctness.
- Existing Greptile context and automated checks do not already cover it adequately.
- The instruction can be specific, measurable, narrowly scoped, and explicit about legitimate exceptions.
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.
- 9d ago First seen · 63 lines · 97 tokens per session scan A 0028e9716262
maintain-greptile-rules is a skill published in the GitHub repository every-app/open-seo (17,762 stars, last pushed 5d ago), licensed MIT. It adds 97 tokens to every session and 928 once invoked, about $0.0005 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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