← Back to list

granola-performance-tuning
by jeremylongshore
Hundreds of Claude Code plugins with embedded AI skills. Learn via interactive Jupyter tutorials.
⭐ 1,042🍴 135📅 Jan 23, 2026
SKILL.md
name: granola-performance-tuning description: | Optimize Granola transcription quality and note performance. Use when improving transcription accuracy, reducing processing time, or enhancing note quality. Trigger with phrases like "granola performance", "granola accuracy", "granola quality", "improve granola", "granola optimization". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io
Granola Performance Tuning
Overview
Optimize Granola for best transcription accuracy and note quality.
Transcription Quality Factors
Audio Quality Hierarchy
Transcription Accuracy
↑
[Professional Microphone] 98%
↑
[Quality Headset Mic] 95%
↑
[Laptop Built-in Mic] 85%
↑
[Phone Speaker] 70%
Environmental Factors
| Factor | Impact | Optimization |
|---|---|---|
| Background noise | High | Use quiet room, noise cancellation |
| Echo/reverb | High | Soft furnishings, smaller room |
| Distance from mic | Medium | Within 12 inches of microphone |
| Multiple speakers | Medium | Use identification phrases |
| Accent variation | Low | Improves over time with usage |
Audio Setup Optimization
Recommended Equipment
## Microphone Recommendations
Budget (~$50):
- Blue Snowball iCE
- Fifine K669
Mid-Range (~$100):
- Blue Yeti
- Rode NT-USB Mini
- Audio-Technica AT2020USB+
Professional (~$200+):
- Shure MV7
- Elgato Wave:3
- Rode PodMic + interface
Microphone Settings (macOS)
# Check current input device
system_profiler SPAudioDataType | grep -A5 "Default Input"
# Adjust input volume (System Preferences)
# Aim for: Input level peaks at 75% during normal speech
Room Optimization
## Environment Checklist
- [ ] Close windows to reduce outside noise
- [ ] Turn off fans, AC if possible
- [ ] Use soft surfaces (carpet, curtains)
- [ ] Position away from keyboard clicks
- [ ] Mute when not speaking
Note Quality Optimization
Meeting Preparation
## Pre-Meeting Checklist
- [ ] Share agenda in advance
- [ ] Send attendee list to calendar
- [ ] Prepare context notes in template
- [ ] Test audio before meeting
During Meeting
## Best Practices
1. State names when addressing people
"Sarah, what do you think about..."
2. Summarize decisions verbally
"So we're agreed: deadline is Friday."
3. Spell out technical terms
"The API endpoint, A-P-I..."
4. Avoid crosstalk
One person speaking at a time
5. Use clear action item language
"Action item: Mike will review the PR by Thursday."
Post-Meeting Enhancement
## Note Review Checklist (5 min)
- [ ] Correct obvious transcription errors
- [ ] Add context AI might have missed
- [ ] Verify action items are complete
- [ ] Add links to referenced documents
- [ ] Tag key decisions
Template Optimization
Effective Template Structure
# Meeting Template: Sprint Planning
## Agenda (Pre-filled)
-
## Context
[Add links to relevant docs]
## Discussion Notes
[AI-enhanced during meeting]
## Decisions
- [ ] Decision 1: [Clear statement]
## Action Items
Format: - [ ] What (@who, by when)
## Follow-up
Next meeting: [date]
Template Best Practices
| Practice | Reason | Impact |
|---|---|---|
| Use headers | Better AI parsing | +20% accuracy |
| Pre-fill context | Reduces ambiguity | +15% relevance |
| Standard formats | Consistent output | +10% usability |
| Action item format | Auto-extraction | +25% detection |
Processing Speed Optimization
Factors Affecting Speed
| Factor | Impact | Optimization |
|---|---|---|
| Meeting length | Linear | Expect 1 min processing per 10 min meeting |
| Internet speed | High | Ensure stable connection during upload |
| Peak times | Medium | Processing queue varies |
| Audio quality | Low | Cleaner audio = faster processing |
Speed Expectations
Meeting Duration → Processing Time
15 minutes → 1-2 minutes
30 minutes → 2-3 minutes
60 minutes → 3-5 minutes
120 minutes → 5-8 minutes
Integration Performance
Zapier Optimization
## Reduce Zapier Latency
1. Use Instant triggers (not polling)
2. Minimize steps in Zap
3. Avoid unnecessary filters
4. Use multi-step Zaps efficiently
5. Monitor task usage
Batch Processing
# Instead of real-time, batch for efficiency
Schedule: Every 30 minutes
Process:
- Collect all new notes
- Batch update Notion
- Single Slack summary
- Aggregate CRM updates
Accuracy Improvement
Training the AI
## Improve Over Time
1. Correct errors when you see them
- AI learns from corrections
2. Use consistent terminology
- Builds vocabulary
3. Identify speakers
- Improves attribution
4. Regular editing
- Provides feedback loop
Custom Vocabulary
## Teach Domain Terms
Add to meeting intros:
"We'll discuss the OAuth2 implementation,
that's O-Auth-Two, and the GraphQL API,
spelled G-R-A-P-H-Q-L..."
Common terms to spell out:
- Acronyms (API, SDK, CI/CD)
- Product names
- People names with unusual spellings
Performance Metrics
What to Track
| Metric | Target | How to Measure |
|---|---|---|
| Transcription accuracy | >95% | Sample review |
| Action item detection | >90% | Compare to meeting |
| Processing time | <5 min | Timestamp comparison |
| Note usefulness | 4+/5 | Team survey |
Weekly Review
## Performance Check
Monday:
- [ ] Review last week's meeting notes
- [ ] Note common transcription errors
- [ ] Identify improvement opportunities
- [ ] Adjust templates if needed
Resources
Next Steps
Proceed to granola-cost-tuning for cost optimization strategies.
Score
Total Score
85/100
Based on repository quality metrics
✓SKILL.md
SKILL.mdファイルが含まれている
+20
✓LICENSE
ライセンスが設定されている
+10
○説明文
100文字以上の説明がある
0/10
✓人気
GitHub Stars 1000以上
+15
✓最近の活動
1ヶ月以内に更新
+10
✓フォーク
10回以上フォークされている
+5
✓Issue管理
オープンIssueが50未満
+5
✓言語
プログラミング言語が設定されている
+5
✓タグ
1つ以上のタグが設定されている
+5
Reviews
💬
Reviews coming soon

