⚠️Install with caution. This skill has very few installs. Always review the source and verify it on clawhub.ai before installing. Community-built skills run with agent permissions — only install ones you trust.

🧠 LLMs & Model APIs

OOMOL RAGv1.0.0

Name: OOMOL RAG
Author: oomol

oo-oomol-rag

oomol

OOMOL RAG (knowledge-base.oomol.com). Use this skill for ANY OOMOL RAG request — reading, creating, updating, and deleting data. Whenever a task involves OOMOL RAG, use this skill instead of calling the API directly.

Download Package View on ClawHub

Installs (all time)

Installs (current)

Downloads

215

Stars

CreatedSep 20, 2026

UpdatedSep 20, 2026

Install & Quick Start

Install via ClawdBot CLI:

clawdbot install oomol/oo-oomol-rag

Skill Package2 files

📋SKILL.mdmarkdown

Failed to load file.

Quality Score

B56/100

Grade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.

Market Validation4/35

· 169 downloads (low demand)
· No tracked installs (may still have real users via manual install)

Documentation25/25

· SKILL.md present
· Detailed documentation (≥3000 chars)
· Contains tool definitions
· Contains usage examples or trigger description
· Detailed summary

Package Completeness6/15

Security Analysis

💙 Low Risk

UNSAFE_SHELLmedium

Potentially destructive shell commands in tool definitions

curl -fsSL https://cli.oomol.com/install.sh | bash

UNDOCUMENTED_EXTERNALlow

Calls external URL not in known-safe list

https://static.oomol.com/logo/third-party/oomol_rag.svg

Audited Oct 9, 2026 · audit v1.0

💡

Usage Guide

Generated Oct 9, 2026

AI agent developers integrating retrieval-augmented generationEnterprise operations and support teams managing internal knowledge basesbeginner

💡 Application Scenarios

Customer Support Knowledge AgentSaaS & Customer Support

Embed an OOMOL RAG retrieval step into an AI support agent so it can answer product questions using the latest help-center articles, PDFs, and internal documentation. The agent queries the knowledge base with every user question and returns grounded answers with source context, reducing hallucinations and repetitive manual lookups.

Internal Policy & Onboarding AssistantHuman Resources & Operations

Let employees ask questions about HR policies, expense approval workflows, and onboarding guides in natural language. HR teams upload handbooks and policy documents once, and the RAG action retrieves the most relevant chunks on demand, cutting down internal email traffic and onboarding time.

Technical Documentation CopilotSoftware Development

Developers and technical writers use the retrieve action to surface relevant API references, deployment guides, and troubleshooting notes directly inside their IDE or chat workflow. Uploading updated documentation triggers asynchronous indexing, so answers always reflect the latest released version.

Sales Enablement & Proposal SearchSales & Marketing

Sales teams upload case studies, pricing decks, and competitive battlecards to the knowledge base and retrieve the most relevant proof points during deal preparation. The skill's file listing and download actions allow reps to audit available assets and export originals when needed.

Legal & Compliance Research LookupLegal & Compliance

Compliance officers upload regulations, contracts, and audit findings to a shared knowledge base, then use retrieval to quickly locate relevant clauses or precedents during reviews. The destructive delete action supports retention policies, while status checks ensure documents are fully indexed before being cited.

💼 Business Models

AI Agent Platform SubscriptionRecurring monthly subscription fees per seat or per workspace, with usage-based overage tiers.

A platform charges a monthly subscription to businesses that deploy AI agents with connected knowledge bases. The OOMOL RAG skill acts as the managed retrieval backbone, so customers pay for seats or usage while the platform bundles storage, indexing, and query costs.

Knowledge Base Setup & ConsultingOne-time implementation fees plus ongoing retainer or managed-service contracts.

Consultancies and agencies offer done-for-you services to ingest, structure, and maintain enterprise knowledge bases using OOMOL RAG actions. They handle file uploads, indexing wait cycles, and retrieval tuning, then hand over a production-ready RAG pipeline.

Usage-Based RAG API ResaleConsumption-based pricing per retrieve call, per uploaded document, or per active knowledge base.

Developers embed the oomol_rag connector into their own products and resell retrieval as part of a broader API or SaaS offering. Revenue is generated from per-query or per-document pricing, with OOMOL handling credential injection and execution.

💬 Integration Tip

Inspect each action's live schema with `oo connector schema` before building a payload, and remember upload_file requires a public HTTP(S) URL rather than a local path. For wait actions such as wait_for_file_ready, poll roughly every 15 seconds until the file status is ready, deleting, or deleted.