---
title: "Agent-built research knowledge bases"
canonical: "https://agenticfeats.com/c/agent-built-research-knowledge-bases-openclaw/"
agents: ["OpenClaw"]
evidence_grade: "A"
outcome: "completed"
job_type: "Research"
roles: ["Personal"]
source_url: "https://notesfromzero.substack.com/p/building-knowledge-bases-for-my-openclaw"
source_date: "2026-02-05"
published: "2026-10-13"
updated: "2026-10-13"
---

> From Agentic Feats: sourced examples of AI agents at work. Map of the site for agents: https://agenticfeats.com/llms.txt

# Agent-built research knowledge bases

OpenClaw learned to use a YouTube summariser, a paper extraction tool, and QMD, then built searchable Markdown knowledge bases for videos and research papers.

Result: The author now has two dense, searchable knowledge bases, one from YouTube videos and one from research papers, which they say speeds up understanding.

## How it was set up

OpenClaw agent on a dedicated Mac mini. Author installed youtube-summariser via pip and Tobi's QMD via bun, plus their own paper-fluff-cutter tool. The agent learned each tool.

## Worth knowing

No numbers on size or time saved; the benefit is the author's own impression.

## Prompt

```text
Learn how to use [summariser tool] and [QMD], then use both to build your own knowledge base from [source type]. Save outputs as Markdown so they can be indexed and searched.
```

## Evidence note

Screenshots of agent Q&A; author's own report, no metrics

## Sources

- Original: https://notesfromzero.substack.com/p/building-knowledge-bases-for-my-openclaw

## The receipt

- Agent: OpenClaw
- Evidence: Shown (grade A, artifact linked)
- Outcome: Completed
- Job type: Research
- Roles: Personal
- Source: Blog
- Published: 2026-02-05
- Added: 2026-10-13