Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.
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Detect pauses and silence in audio using local dynamic thresholds. Use when you need to find natural pauses in lectures, board-writing silences, or breaks between sections. Uses local context comparison to avoid false positives from volume variation.
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Detects pauses and low-energy segments using local dynamic thresholds on pre-computed energy data. Unlike global threshold methods, this compares energy to surrounding context, avoiding false positives when speaker volume varies.
python3 /root/.claude/skills/pause-detector/scripts/detect_pauses.py \
--energies /path/to/energies.json \
--output /path/to/pauses.json
--energies: Path to energy JSON file (from energy-calculator)--output: Path to output JSON file--start-time: Start analyzing from this second (default: 0)--threshold-ratio: Ratio of local average for low energy (default: 0.5)--min-duration: Minimum pause duration in seconds (default: 2)--window-size: Local average window size (default: 30){
"method": "local_dynamic_threshold",
"segments": [
{"start": 610, "end": 613, "duration": 3},
{"start": 720, "end": 724, "duration": 4}
],
"total_segments": 11,
"total_duration_seconds": 28,
"parameters": {
"threshold_ratio": 0.5,
"window_size": 30,
"min_duration": 2
}
}
# Detect pauses after opening (start at 221s)
python3 /root/.claude/skills/pause-detector/scripts/detect_pauses.py \
--energies energies.json \
--start-time 221 \
--output pauses.json
# Result: Found 11 pauses totaling 28 seconds
| Parameter | Lower Value | Higher Value |
|---|---|---|
threshold_ratio | More aggressive | More conservative |
min_duration | Shorter pauses | Longer pauses only |
window_size | Local context | Broader context |
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Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.
中文简介正在准备中。当前显示原文说明。
AC branch pi-model power flow equations (P/Q and |S|) with transformer tap ratio and phase shift, matching `acopf-math-model.md` and MATPOWER branch fields. Use when computing branch flows in either direction, aggregating bus injections for nodal balance, checking MVA (rateA) limits, computing branch loading %, or debugging sign/units issues in AC power flow.
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Redact text from PDF documents for blind review anonymization
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Use when checking simplified ADA-derived plan-view bathroom accessibility constraints such as turning space, door clear width, toilet centerline, grab bars, and lavatory knee/toe clearance.
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Analyze failed GitHub Action jobs for a pull request.
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Use when extracting plan-view architectural geometry from DXF files with semantic CAD layers, especially when outputs must normalize rooms, doors, fixtures, clearances, and grab bars into machine-checkable JSON.
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