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alexica00
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talk-stage3-concepts

Extract and categorize talk concepts into a numbered catalogue with potential scores.

Updated May 30, 2026
Search Tags:#timeline#scoring#output#concepts#catalogue#talk
One-click install
npx skills add https://github.com/alexica00/claude-code-ultimate-guide --skill talk-stage3-concepts-alexica00
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: talk-stage3-concepts
Source: https://github.com/alexica00/claude-code-ultimate-guide/tree/main/examples/skills/talk-pipeline/stage-3-concepts
Command: npx skills add https://github.com/alexica00/claude-code-ultimate-guide --skill talk-stage3-concepts-alexica00

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Builds an exhaustive catalogue of all identifiable concepts in the source material, with each concept numbered, categorized, and scored for talk potential.

Core Features & Use Cases

  • Reads the summary file to extract key concepts.
  • Optionally enriches scores with timeline data.
  • Categorizes concepts into domains and assigns HIGH/MEDIUM/LOW talk potential.
  • Writes a ready-to-use concepts catalogue for Stage 4 positioning.
  • Supports optional repo enrichment when a repository path is provided.

Quick Start

Run the stage 3 concept extraction on talks/{YYYY}-{slug}-summary.md to generate the concepts catalogue.

Frequently Asked Questions about talk-stage3-concepts

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

FAQPage Schema
How do I extract and organize talk concepts from a summary into a structured catalogue?▼

To build a structured talk concepts catalogue, extract identifiable concepts from your summary file, categorize them by domain, and assign each a talk-potential score of HIGH, MEDIUM, or LOW. This produces a numbered markdown catalogue ready for positioning.

What is talk-potential scoring and how does it help structure presentation concepts?▼

Talk-potential scoring evaluates extracted concepts by assigning HIGH, MEDIUM, or LOW ratings based on their suitability for a talk. This scoring mechanism helps prioritize which concepts to focus on during stage 4 positioning and presentation drafting.

Can I use timeline data to improve concept scoring accuracy for my talk catalogue?▼

Yes, you can enrich concept scoring accuracy by providing an available timeline. The Skill verifies dates from the timeline to adjust and improve the HIGH, MEDIUM, or LOW talk-potential scores assigned to your extracted concepts.

Does the concept extraction process support repository enrichment when a repo path is provided?▼

Yes, the concept extraction supports optional repository enrichment. When a repo_path is provided, the Skill performs repository enrichment and outputs an additional enriched markdown file alongside the main concepts catalogue.

What file format and naming convention is used for the generated concepts catalogue output?▼

The concepts catalogue output is written as a markdown file named talks/{YYYY}-{slug}-concepts.md. If repository enrichment is performed, an enriched file named talks/{YYYY}-{slug}-concepts-enriched.md is also generated.

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