Summary
Extracts decisions, action items, opinions, questions, and terminology from meeting transcripts using Cerebras AI's llama-3.3-70b model. It chunks large transcripts, processes them through the API, and outputs structured markdown with confidence scores for each extraction. The glossary feature is interesting: it can preload existing terms and suggest new ones with definitions as it encounters domain-specific language. You'll need to install npm dependencies and add your Cerebras API key first. Output includes token usage metrics in YAML frontmatter, which is helpful for tracking costs. Good for teams that record meetings and need consistent extraction without manually reading through everything.
Install to Claude Code
npx -y skills add glebis/claude-skills --skill transcript-analyzer --agent claude-codeInstalls into .claude/skills of the current project.
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Files
SKILL.mdView on GitHub
Transcript Analyzer
Overview
Analyze meeting transcripts using AI to automatically extract and categorize:
- Decisions - Explicit agreements or choices made
- Action Items - Tasks assigned to people
- Opinions - Viewpoints expressed but not agreed upon
- Questions - Unresolved questions raised
- Terms - Domain-specific terminology for glossary
Prerequisites
Before first use, install dependencies:
cd ~/.claude/skills/transcript-analyzer/scripts && npm install
Usage
To analyze a transcript:
cd ~/.claude/skills/transcript-analyzer/scripts && npm run cli -- <transcript-file> -o <output.md> [options]
Options
| Option | Description |
|---|---|
<file> | Transcript file to analyze (first positional arg) |
-o, --output <path> | Write markdown to file instead of stdout |
--include-transcript | Include full transcript in output [default: off] |
--no-extractions | Exclude extractions section |
--no-glossary | Exclude glossary section |
--glossary <path> | Custom glossary JSON path |
--skip-glossary | Don't preload glossary terms |
--max-terms <num> | Limit glossary suggestions |
--chunk-size <num> | Override chunk size (default: 3000) |
Examples
Basic Analysis
cd ~/.claude/skills/transcript-analyzer/scripts && npm run cli -- /path/to/meeting.md -o /path/to/analysis.md
Include Original Transcript
cd ~/.claude/skills/transcript-analyzer/scripts && npm run cli -- /path/to/meeting.md -o /path/to/analysis.md --include-transcript
Extractions Only (No Glossary)
cd ~/.claude/skills/transcript-analyzer/scripts && npm run cli -- /path/to/meeting.md -o /path/to/analysis.md --no-glossary
Analyze Specific Section
To analyze only part of a transcript, extract the section first:
sed -n '50,100p' /path/to/meeting.md > /tmp/section.md
cd ~/.claude/skills/transcript-analyzer/scripts && npm run cli -- /tmp/section.md -o /path/to/section-analysis.md
Output Format
The tool generates markdown with:
-
YAML Frontmatter - Processing metadata:
- chunks processed
- extractions count by type
- new terms discovered
- model used (llama-3.3-70b via Cerebras)
- token usage (input/output/total)
-
Extractions - Categorized findings with confidence scores:
- Each extraction includes speaker (if identified), source snippet, and related terms
-
Glossary - Approved terms from existing glossary + suggested new terms with definitions
Configuration
The skill uses Cerebras API with the key stored in scripts/.env:
CEREBRAS_API_KEY=<your-key>
Scripts
scripts/cli.ts- Main CLI entry pointscripts/src/lib/extract-service.ts- AI processing logic using Cerebrasscripts/src/lib/markdown.ts- Markdown output generationscripts/src/lib/term-utils.ts- Term deduplication utilitiesscripts/src/lib/mockExtractor.ts- Mock mode for testingscripts/src/types/index.ts- TypeScript type definitionsscripts/data/glossary.json- Default glossary storage
Featured
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →First SeenJun 3, 2026
