Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/attaxr/attaxr-seo-pipelinenpx agentmods add skills/attaxr/attaxr-seo-pipeline/seo-pipeline-bashWrote 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/attaxr/attaxr-seo-pipeline/seo-pipeline-bash)<a href="https://agentmods.dev/skills/attaxr/attaxr-seo-pipeline/seo-pipeline-bash"><img src="https://agentmods.dev/badge/skills/attaxr/attaxr-seo-pipeline/seo-pipeline-bash/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/attaxr/attaxr-seo-pipeline/seo-pipeline-bash"><img src="https://agentmods.dev/badge/skills/attaxr/attaxr-seo-pipeline/seo-pipeline-bash.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 | $0.00032 | $0.00264 |
| Opus 5 | $0.00016 | $0.00132 |
| Sonnet 5 | $0.00006 | $0.00053 |
| Haiku 4.5 | $0.00003 | $0.00026 |
Grade A, and why
seo-pipeline-bash 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 12d 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.
What it actually says
SEO Pipeline (bash)
Runs a 3-stage pipeline:
- Scrape —
python -m seo_pipeline --from-json keywords.json- Browser Use SDK primary (AI-driven article extraction)
- DuckDuckGo search fallback (URL discovery only)
- Analyze — review scraped content manually or via agent
- Create — write article draft to
pipeline_data/drafts/
Setup
python scripts/setup.py # interactive (installs browser-use-sdk, sets .env, redacted key input)
# or:
export BROWSER_USE_API_KEY=bu_...
Run
python -m seo_pipeline --from-json keywords.json
python -m seo_pipeline "your search keyword"
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.
- 12d ago First seen · 40 lines · 32 tokens per session scan A 652f3c316e2f
seo-pipeline-bash is a skill published in the GitHub repository attaxr/attaxr-seo-pipeline (2 stars, last pushed 2mo ago), licensed MIT. It adds 32 tokens to every session and 264 once invoked, about $0.0002 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 2026-08-31.
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