memory-ingest

Convert unstructured transcripts and documents into structured Basic Memory entities with observations and relations.

4.0k|282|Updated Dec 2, 2024
One-click install
npx skills add https://github.com/basicmachines-co/basic-memory --skill memory-ingest-basicmachines-co
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memory-ingest
Source: https://github.com/basicmachines-co/basic-memory/tree/main/skills/memory-ingest
Command: npx skills add https://github.com/basicmachines-co/basic-memory --skill memory-ingest-basicmachines-co

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Raw meeting transcripts, conversation logs, and pasted documents contain valuable knowledge that gets lost without structure. This Skill turns unstructured external input into organized Basic Memory notes with extracted entities, categorized observations, and linked relations. ## Core Features & Use Cases - Entity Extraction & Deduplication: Identifies people, organizations, and topics from raw text, then searches existing notes with multiple query variations to avoid duplicates. - Approval-Gated Creation: Presents proposed new entities for user approval before writing anything to the knowledge graph. - Structured Note Templates: Creates source notes preserving verbatim content plus categorized observations (decisions, insights, next steps) and wiki-linked relations. - Use Case: Paste a meeting transcript with a new client and get a verbatim source note, approved Person and Organization entity notes, and extracted action items with follow-up reminders. ## Quick Start Process this pasted meeting transcript into Basic Memory, extract the people and organizations mentioned, and create notes for the entities I approve.

Frequently Asked Questions about memory-ingest

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I turn a meeting transcript into structured notes?▼

Paste the transcript and ask for it to be processed into Basic Memory. The workflow extracts people, organizations, and topics, searches for existing matches, proposes new entities for your approval, then creates a source note with verbatim content plus categorized observations and relations.

How does entity extraction avoid creating duplicate notes?▼

Each extracted entity is searched with multiple query variations, such as full name, last name, abbreviations, and acronyms. Entities found in Basic Memory are linked with wiki-links instead of being recreated, and only unmatched entities are proposed as new.

Can I control which new entities get created?▼

Yes. Before anything is written, the workflow presents a proposal listing existing entities and proposed new ones with context for each. You can approve all, select individually, or skip entity creation entirely.

What types of content can be ingested into Basic Memory?▼

Meeting transcripts, conversation logs, email threads, pasted documents, articles, and freeform notes are supported. The workflow detects the format and applies an appropriate note template, such as meeting notes or reference notes.

Does the ingestion process modify the original source text?▼

No. Source content is preserved verbatim in the note as the ground truth. Structured observations, categories, and relations are layered on top as interpretation without rewriting or summarizing the original material.