Agent skill · Media & Video

wavecap-hallucination

Configure WaveCap hallucination detection and prevention. Use when Whisper outputs gibberish, repeated phrases, or phantom text on silent audio.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill wavecap-hallucination-tobiaswooldridge-wavecap --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 6 KB
Bundled scripts: none
Path: skills/ai-llm/wavecap-hallucination-tobiaswooldridge-wavecap/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# WaveCap Hallucination Prevention Skill Use this skill to detect and filter out Whisper hallucinations - false transcriptions generated when there's no actual speech. ## What Are Hallucinations? Whisper sometimes generates plausible-sounding text when fed: - Silent audio or white noise - Background music or tones - Very low-quality speech Common hallucination patterns: - "Thank you for watching" - "Transcription by CastingWords" - Repeated phrases like "the the the the" - Random punctuation or symbols ## Configuration Location Hallucination settings are in the `whisper:` section: - **User config:** `/Users/thw/Projects/WaveCap/state/config.yaml` ## Silence Hallucination Phrases Phrases that indicate Whisper hallucinated rather than transcribed: ```yaml whisper: silenceHallucinationPhrases: - "thank you" - "thanks for watching" - "transcription by castingwords" - "casting words" - "all right here we go" - "alright here we go" - "all right let's go" - "alright let's go" - "you" - "bye" - "uh" - "hmm" ``` When these phrases appear on low-energy audio, the transcription is discarded. ### Add Custom Hallucination Phrases If you notice recurring false phrases, add them: ```bash # View c

What's inside
Steps it walks through
  1. What Are Hallucinations?
  2. Configuration Location
  3. Silence Hallucination Phrases
  4. Add Custom Hallucination Phrases
  5. Segment Repetition Detection
  6. Blank Audio Detection
  7. View Current Settings
  8. Diagnose Hallucination Issues
  9. Find potential hallucinations in transcriptions
  10. Find repeated phrase patterns
  11. Count BLANKAUDIO tokens
  12. Find low-confidence + short transcriptions (likely noise)
  13. Tuning Scenarios
  14. Aggressive Hallucination Filtering
Ships with 1 file
  • metadata.json
Commands it runs
View current phrases
grep -A20 "silenceHallucinationPhrases:" /Users/thw/Projects/WaveCap/state/config.yaml
grep -E "(hallucination|repetition|blank)" /Users/thw/Projects/WaveCap/state/config.yaml
curl -s http://localhost:8000/api/transcriptions/export | \
jq '[.[] | select(
jq '[.[] | select(.text | test("(\\b\\w{4,}\\b).*\\1.*\\1.*\\1"))] |
jq '[.[] | select(.text == "[BLANK_AUDIO]")] | length'
jq '[.[] | select(.confidence < 0.6 and (.text | length) < 20)] |
launchctl stop com.wavecap.server && sleep 2 && launchctl start com.wavecap.server
cd /Users/thw/Projects/WaveCap/backend && source .venv/bin/activate && python3 << 'EOF'
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About this skill
What does the wavecap-hallucination skill do?

Configure WaveCap hallucination detection and prevention. Use when Whisper outputs gibberish, repeated phrases, or phantom text on silent audio.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill wavecap-hallucination-tobiaswooldridge-wavecap --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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