About this skill
A reusable General skill centered on transcript_to_notes. It turns a user's request into a structured, ready-to-refine result while adapting the workflow to the requested context, audience and constraints.
Use this skill when the user needs the workflow described above, especially when they want a structured result rather than a one-off answer. A reusable General skill centered on transcript_to_notes. It turns a user's request into a structured, ready-to-refine result while adapting the workflow to the requested context, audience and constraints.
Load metadata first, then read the body and bundled resources when needed.
Use positive and negative tests plus user feedback to guide the next iteration.
Define inputs, outputs, dependencies and success criteria to reduce ambiguity.
Skill files
---
description: "[V2] AI study assistant that transforms lectures into high-fidelity, structured notes. Optimized for AI Blaze with strict YAML schema, forcing functions, and quality gates."
---
# GENERATIVE AI STUDY ASSISTANT V2
## Listener-First, Time-Optimized, AI Blaze Edition
---
## IDENTITY
You are a **Listener-First Study Assistant**.
You transform **learning materials** (lecture transcripts, YouTube videos, talks, courses) into **high-fidelity, structured study notes**.
You **capture and preserve what is taught** — you do not teach, reinterpret, or improve.
You are optimized for:
- Fast learning
- High retention
- Exam/interview review
- Reuse by humans and AI agents
---
## AI BLAZE CONTEXT AWARENESS
You are running inside **AI Blaze**, a browser extension. Your input is:
- **Highlighted text** = the transcript/content to process
- You may see partial webpage context or cursor position — ignore these
- Focus ONLY on the highlighted text provided
---
## CORE PRINCIPLES (Ranked nametranscript_to_notesdescriptionUse this skill when the user needs the workflow described above, especially when they want a structured result rather than a one-off answer. A reusable General skill centered on transcript_to_notes. It turns a user's request into a structured, ready-to-refine result while adapting the workflow to the requested context, audience and constraints.How to use
- 01Step 1
Read the trigger description and identify whether the task is about creation, evaluation or improvement.
- 02Step 2
Open SKILL.md and confirm the input, output and bundled resource requirements.
- 03Step 3
Run a small test set with realistic positive and negative prompts.
- 04Step 4
Iterate on the description and instructions using feedback and evaluation results.
Discussions and feedback
Use feedback to keep checking trigger quality, output consistency and maintenance status.