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Sub-skill of signal-analysis: Complete Signal Analysis Workflow (+1).
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Save/publish analysis or computation results from ANY ecosystem repo to Hugging Face as a queryable, viewer-renderable dataset. Use when the user wants to "save results to hugging face", "publish dataset to HF", "hugging face data saving", "save analysis results", "hf dataset", "make results queryable", or "render via datasets-server API". Reshapes nested results into flat parquet tables, writes a dataset card with a viewer `configs:` block and provenance, applies license/public-vs-private routing, enforces a domain data-quality gate (faithful-to-source != correct), publishes to `aceengineer/<repo>-<projection>`, and verifies via the datasets-server API.
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基于 SOC 职业分类
| name | signal-analysis-complete-signal-analysis-workflow |
| description | Sub-skill of signal-analysis: Complete Signal Analysis Workflow (+1). |
| version | 1.0.0 |
| category | engineering |
| type | reference |
| scripts_exempt | true |
basename: signal_analysis_workflow
signal_analysis:
# Step 1: Condition raw signals
conditioning:
flag: true
input_file: "data/raw_stress.csv"
output_file: "data/conditioned_stress.csv"
operations:
*See sub-skills for full details.*
## Fatigue-Focused Analysis
```yaml
signal_analysis:
rainflow:
flag: true
input_file: "data/stress_history.csv"
output:
cycles_file: "results/fatigue_cycles.csv"
summary_file: "results/fatigue_summary.json"
options:
hysteresis_filter: 0.01 # Filter cycles < 1% of range
*See sub-skills for full details.*