Borrowing it
Nothing to install: this file belongs to Aryanacoder/superragskills. 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/Aryanacoder/superragskills/main/AGENTS.mdgit clone --depth 1 https://github.com/Aryanacoder/superragskillsWrote 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/aryanacoder/superragskills/agents-md)<a href="https://agentmods.dev/instructions/aryanacoder/superragskills/agents-md"><img src="https://agentmods.dev/badge/instructions/aryanacoder/superragskills/agents-md/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/aryanacoder/superragskills/agents-md"><img src="https://agentmods.dev/badge/instructions/aryanacoder/superragskills/agents-md.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 | $0.00168 | $0.00168 |
| Opus 5.5 | $0.00067 | $0.00067 |
| Sonnet 5.5 | $0.00034 | $0.00034 |
| Haiku 4.5 | $0.00017 | $0.00017 |
Grade A, and why
superragskills AGENTS.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 2mo 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
Agent Instructions
When the user asks to design, build, evaluate, improve, or deploy a RAG app, use the skill at skills/superrag-build/SKILL.md.
Important behavior:
- Interview before implementation unless the user has already supplied enough detail.
- Ask questions in small batches.
- Select the correct RAG type before coding: basic, hybrid, reranked, agentic, GraphRAG, multimodal, structured-data, local/offline, AWS, Azure, or self-hosted.
- Produce a concrete architecture, backlog, evaluation plan, and deployment plan before broad implementation.
- Prioritize source grounding, citations, retrieval evaluation, access control, observability, and safe no-answer behavior.
- For existing repos, inspect ingestion, indexing, retrieval, prompts, UI, and tests before changing code.
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.
- 2mo ago First seen · 13 lines · 168 tokens per session scan A e5c7e418a1cc
superragskills AGENTS.md is an instructions file published in the GitHub repository Aryanacoder/superragskills (4 stars, last pushed 4mo ago), licensed MIT. It adds 168 tokens to every session, about $0.0007 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 2026-08-31.
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