talk-stage1-extract

Name: talk-stage1-extract
Availability: InStock
Author: alamator

Extract narratives, themes, metrics, and gaps from source material into a Markdown talk summary.

Updated Apr 12, 2026

Search Tags:#summarization #narrative #metrics #pipeline #presentation #extract #talk

Ready to run

npx skills add https://github.com/Alamator/code-ultimate --skill talk-stage1-extract-alamator

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: talk-stage1-extract
Source: https://github.com/Alamator/code-ultimate/tree/main/examples/skills/talk-pipeline/stage-1-extract
Command: npx skills add https://github.com/Alamator/code-ultimate --skill talk-stage1-extract-alamator

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Converts disparate source materials (articles, transcripts, notes) into a single, structured talk summary so creators avoid manual synthesis, missed metrics, and unclear narrative arcs before building a presentation.

Core Features & Use Cases

Metadata collection: Prompts for or validates slug, event, date, duration, audience, and type to ensure consistent talk records.
Source-type detection: Auto-detects REX (experience-based) versus Concept sources and adapts the narrative extraction accordingly.
Narrative & metrics extraction: Produces a clear narrative arc, 3–7 main themes, and extracts measurable metrics with sources while flagging gaps and next-stage recommendations.
Use Case: Prepare a conference talk from a long-form article and raw interview transcript by producing a concise talk summary that downstream stages consume.

Quick Start

Run the skill on your source file and provide any missing metadata like slug, event, date, duration, audience, and type so it writes the talks/{YYYY}-{slug}-summary.md output.

Frequently Asked Questions about talk-stage1-extract

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

FAQPage Schema

How do I structure raw notes and transcripts into a talk summary?▼

To structure raw notes and transcripts into a talk summary, provide your source file and optional metadata like event, date, and audience. The system extracts a narrative arc, main themes, and measurable metrics, flagging any content gaps to produce a markdown summary.

Can I extract presentation metrics and narrative arcs from long-form articles?▼

Yes, you can extract presentation metrics and narrative arcs from long-form articles. The process detects whether the source is experience-based or conceptual, then adapts the extraction to output 3–7 main themes alongside measurable metrics with their original sources.

What metadata do I need to prepare a conference talk from source material?▼

To prepare a conference talk from source material, you should provide a slug, event name, date, duration, audience, and type. This metadata ensures consistent talk records and writes a structured markdown summary file to your talks directory.

Does this talk extraction process work for both experience-based and conceptual content?▼

Yes, the talk extraction process works for both experience-based and conceptual content. It auto-detects the source type and adapts the narrative extraction accordingly, ensuring the generated summary accurately reflects the original material's structure.

What is the best way to audit existing presentation material before building slides?▼

The best way to audit existing presentation material before building slides is to run it through a talk summary extraction. This identifies clear narrative arcs, quantifiable metrics, and content gaps, providing actionable recommendations for downstream pipeline stages.