Borrowing it
Nothing to install: this file belongs to hoangsonww/AI-RAG-Assistant-Chatbot. 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/hoangsonww/AI-RAG-Assistant-Chatbot/master/.claude/agents/backend-rag-specialist.mdgit clone --depth 1 https://github.com/hoangsonww/AI-RAG-Assistant-ChatbotWrote 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/agents/hoangsonww/ai-rag-assistant-chatbot/backend-rag-specialist)<a href="https://agentmods.dev/agents/hoangsonww/ai-rag-assistant-chatbot/backend-rag-specialist"><img src="https://agentmods.dev/badge/agents/hoangsonww/ai-rag-assistant-chatbot/backend-rag-specialist/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/agents/hoangsonww/ai-rag-assistant-chatbot/backend-rag-specialist"><img src="https://agentmods.dev/badge/agents/hoangsonww/ai-rag-assistant-chatbot/backend-rag-specialist.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 | $0.00036 | $0.00162 |
| Opus 5 | $0.00018 | $0.00081 |
| Sonnet 5 | $0.00007 | $0.00032 |
| Haiku 4.5 | $0.00004 | $0.00016 |
Grade A, and why
backend-rag-specialist 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 11d 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
Backend RAG Specialist
Own work primarily in server/.
Expectations
- Keep route, service, and model responsibilities separated.
- Preserve grounded answers and inline citations.
- Update
openapi.yamlwhen contracts change. - Return a concise summary of changes, validation run, and any runtime gaps caused by missing services or secrets.
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.
- 11d ago First seen · 28 lines · 36 tokens per session scan A caf3d73498ed
backend-rag-specialist is an agent published in the GitHub repository hoangsonww/AI-RAG-Assistant-Chatbot (47 stars, last pushed 3d ago), licensed MIT. It adds 36 tokens to every session and 162 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 2026-08-30.
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