Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add giovannifrontera/academic-research-prisma-wiki-rag --skill hybrid-raggit clone --depth 1 https://github.com/giovannifrontera/academic-research-prisma-wiki-ragWrote 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/giovannifrontera/academic-research-prisma-wiki-rag/hybrid-rag)<a href="https://agentmods.dev/skills/giovannifrontera/academic-research-prisma-wiki-rag/hybrid-rag"><img src="https://agentmods.dev/badge/skills/giovannifrontera/academic-research-prisma-wiki-rag/hybrid-rag/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/giovannifrontera/academic-research-prisma-wiki-rag/hybrid-rag"><img src="https://agentmods.dev/badge/skills/giovannifrontera/academic-research-prisma-wiki-rag/hybrid-rag.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 | $0.00096 | $0.03169 |
| Opus 5 | $0.00048 | $0.01584 |
| Sonnet 5 | $0.00019 | $0.00634 |
| Haiku 4.5 | $0.00010 | $0.00317 |
Grade C, and why
hybrid-rag scanned grade C with 1 finding 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
**Il DB è idempotente:** `init` e `index-prisma` usano `upsert` — è sempre sicuro rieseguirli. Per svuotare il DB da zero: `rm -rf rag_db/` poi `py hybrid_rag.py init`. The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- 12d ago First seen · 224 lines · 96 tokens per session scan C 35054239b583
hybrid-rag is a skill published in the GitHub repository giovannifrontera/academic-research-prisma-wiki-rag (2 stars, last pushed 3mo ago), licensed AGPL-3.0. It adds 96 tokens to every session and 3,169 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
markitdown
Convert heterogeneous documents and selected URIs to Markdown with Microsoft MarkItDown for text analysis, search, and LLM/RAG ingestion. Covers safe local conversion, streams, Office/PDF/data formats, batch workflows, plugins, vision OCR, Azure extraction, and the official MCP server.
azure-ai
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
haiku-rag
Search, read and compute over the user's haiku.rag knowledge base through the haiku-rag MCP tools. Use whenever a request could be answered from the user's ingested documents, when asked to find, look up, check or cite something in their documents or knowledge base, or when the question is about the user's own…
basemind-documents
Semantic + full-text search over documents and the web via basemind's RAG store — PDFs, Office, HTML, email, images (OCR), plus scraped/crawled web pages, with cross-encoder reranking, keyword and named-entity (NER) filters, and per-document summaries. Reach for it whenever the user asks to "search the docs / PDFs"…
doc-parse
A document parser that converts PDFs, PowerPoint files, spreadsheets, and Word files into structured Markdown with metadata and a confidence score.
orchardcore-ai-documents
Skill for configuring AI Documents in Orchard Core with CrestApps modules. Covers document upload, text extraction, chunking, vector indexing, and Retrieval-Augmented Generation (RAG) for AI chat. Supports PDF, OpenXml (docx, xlsx, pptx), and plain-text formats with file-system or Azure Blob storage and Azure AI…