Borrowing it
Nothing to install: this file belongs to attaxr/attaxr-seo-pipeline. 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/attaxr/attaxr-seo-pipeline/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/attaxr/attaxr-seo-pipelineWrote 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/instructions/attaxr/attaxr-seo-pipeline/copilot-instructions)<a href="https://agentmods.dev/instructions/attaxr/attaxr-seo-pipeline/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/attaxr/attaxr-seo-pipeline/copilot-instructions/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/instructions/attaxr/attaxr-seo-pipeline/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/attaxr/attaxr-seo-pipeline/copilot-instructions.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 | $0.00636 | $0.00636 |
| Opus 5 | $0.00318 | $0.00318 |
| Sonnet 5 | $0.00127 | $0.00127 |
| Haiku 4.5 | $0.00064 | $0.00064 |
Grade A, and why
attaxr-seo-pipeline copilot-instructions.md 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.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SEO Content Pipeline — Copilot Instructions
Canonical source:
AGENTS.md(project root) — this file summarizes; the full pipeline lives there.
Pipeline Overview
4 stages, sequential, fail-stop. Each feeds the next. Runs entirely on local files — no CMS.
Keyword Research → Content Collection → SEO Analysis → Content Creation
Stage 1 — Keyword Research
- Search for domain-relevant keywords using web search.
- Capture: term, search volume, difficulty (1-100), relevance (1-5), intent (informational/commercial/navigational), cluster name.
- Prioritize long-tail keywords with commercial intent.
- Save to
keywords.json.
Stage 2 — Content Collection
CREDENTIAL CHECK (required before any scraping):
- Check
BROWSER_USE_API_KEYenv var → if missing, source.env→ if still missing, prompt user with redacted input. - Never echo the key in tool output, terminal, or conversation history.
- Do not proceed without a valid key.
Primary: python -m seo_pipeline --from-json keywords.json (Browser Use Cloud SDK v3).
Fallback: DuckDuckGo HTML search (URL discovery only — no article body).
If both yield zero articles: Stop. Do not proceed to Stage 3.
Stage 3 — SEO Analysis
Per article, analyze: keyword usage (title, H1, first 100 words, density), keyword gaps, content depth/missing subtopics, readability (jargon, paragraph length), structure (H2/H3 hierarchy, lists, tables), 3-5 actionable improvements.
Critical: Identify the unique angle none of the top competitors cover.
Save to pipeline_data/analysis/.
Stage 4 — Content Creation
Per keyword cluster: 1,500+ words, original insight in first 200 words, H2/H3 hierarchy targeting primary + secondary keywords, at least one bullet/numbered list, concrete example or case study, CTA paragraph, 2-3 image suggestions.
Post-creation: Humanization pass — strip AI-isms, adjust tone, vary sentence rhythm, active voice.
Save to pipeline_data/drafts/.
Quality Checklist
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 · 66 lines · 636 tokens per session scan A d4de645f9ac2
attaxr-seo-pipeline copilot-instructions.md is an instructions file published in the GitHub repository attaxr/attaxr-seo-pipeline (2 stars, last pushed 2mo ago), licensed MIT. It adds 636 tokens to every session, about $0.0032 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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