analyze-voice

Analyzes voice memo transcriptions and creates structured meeting or resource notes in Obsidian.

6|1|Updated Nov 26, 2025
One-click install
npx skills add https://github.com/nathanvale/side-quest-marketplace-old --skill analyze-voice-nathanvale
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: analyze-voice
Source: https://github.com/nathanvale/side-quest-marketplace-old/tree/main/plugins/para-obsidian/skills/analyze-voice
Command: npx skills add https://github.com/nathanvale/side-quest-marketplace-old --skill analyze-voice-nathanvale

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Voice memo transcriptions are ambiguous and unstructured, making them hard to file into a PARA-organized Obsidian vault. This Skill reads a transcription, classifies it as a meeting or resource, extracts structured content, and creates the note automatically. ## Core Features & Use Cases - Speaker Matching: Matches speaker names and aliases against a known stakeholder list and outputs wikilinks, inferring projects when all speakers share a squad. - Meeting Extraction: Pulls attendees, discussion notes, decisions, action items with assignees and due dates, and follow-ups from multi-speaker recordings. - Resource Creation: For single-speaker ideas or reflections, injects the transcription as Layer 1 content, sampling key segments when it exceeds token limits. - Use Case: After recording a sprint planning session on your phone, drop the transcription into your inbox and let the Skill produce a fully structured meeting note with action items assigned to matched stakeholders. ## Quick Start Analyze the voice memo transcription in my inbox and create the appropriate meeting or resource note with a triage proposal.

Frequently Asked Questions about analyze-voice

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

FAQPage Schema
How do I process voice memo transcriptions into Obsidian notes?

Provide the transcription file path along with available areas, projects, and stakeholders. The Skill reads the file, classifies the content, creates a meeting or resource note via para_create, and returns a lightweight JSON proposal.

How does speaker matching work with a stakeholder list?

Speaker names are matched against stakeholder names, aliases, and email prefixes. Matched speakers become wikilinks like [[June Xu]], while unmatched ones stay as plain text. If all speakers share a squad, the project is inferred automatically.

What meeting types can be detected from a voice recording?

The Skill classifies meetings as standup, 1on1, planning, retro, workshop, or general based on speaker count, roles, tone, and structure. Single-speaker recordings become ideas, reflections, or conversations instead.

What happens when a transcription is too long to include fully?

For transcriptions over about 2k tokens, the Skill samples the opening, key insight sections, action items, and closing while preserving timestamps, targeting 2-3k tokens total for the Layer 1 injection.

When should confidence be set to low for voice memos?

Set confidence to low when content is ambiguous, covers multiple topics, or has several valid interpretations. Voice memos default to medium or low because they lack clear boundaries and may contain transcription errors.