multipart-audio-smoke
Smoke test an audio upload endpoint using multipart/form-data. Use for quick end-to-end validation of transcription pipelines.
اپنے ایجنٹ کے لیے موزوں صلاحیت تلاش کریں۔
Smoke test an audio upload endpoint using multipart/form-data. Use for quick end-to-end validation of transcription pipelines.
Expert in digital signal processing for audio applications. Validates biquad filter implementations, frequency response calculations, and audio algorithms. Use when modifying audio-math.ts, implementing new filter types, or adding spectral analysis features.
Generate a tiny non-sensitive WAV file using only the Python standard library. Use for deterministic smoke tests without committing real user audio.
Complete workflow for detecting duplicate and near-duplicate images using MD5 hashes and perceptual hashing (dHash/pHash). Use when implementing duplicate detection features.
Create charts and data visualizations for blog posts. Use when the user asks to add a chart, create a graph, visualize data, or add a FilterableChart component. This includes bar charts, line charts, area charts, composed charts (bar+line), time series visualizations, and multi-series comparisons.
Generates The Edmund Bogen Team's weekly market intelligence package: email, article page, dashboard, and community listings pages. Guides team through data collection, validates consistency, and produces all HTML assets ready for deployment to Constant Contact and GitHub.
データ分析・可視化・レポート作成。pandas、SQL、BigQuery、スプレッドシート操作、統計分析、グラフ作成。「データ分析」「SQL」「BigQuery」「pandas」「集計」「可視化」「レポート」に関する質問で使用。
Build a complete data clustering and visualization pipeline from any data source. Use when the user wants to analyze patterns in text data (GitHub issues, Slack messages, support tickets, code reviews, forum posts, customer feedback, etc.), cluster similar items, or build an interactive visualization to explore the patterns. Triggers on: "cluster", "analyze patterns", "group similar", "clio-style", "pattern analysis", "visualize clusters", "find themes", "topic modeling", "semantic clustering".
Create geographic maps for Belgian data visualizations. Use when the user asks to add a map, create a choropleth map, visualize geographic data, show data by region/province/municipality, or add a MunicipalityMap component. This skill covers Belgian geographic data (regions, provinces, municipalities) using NIS codes.
Database schema specification using Mermaid ER diagrams, table structures, constraints, and indexes for multi-tenant applications.
Master SOTA data prep for Kaggle comps: automated EDA (Sweetviz), cleaning (Pyjanitor), and feature selection (Polars + XGBoost) for medium datasets (100MB–5GB) in Colab.
Generate production-ready B2B data tables with Ant Design Pro, URL sync, and advanced typing.
Generate HTML reports, charts, and dashboards with neo-brutal design. Use for creating GitHub activity reports, Fieldy summaries, Skillz analytics, and other data visualizations.
Edit or create interactive Plotly.js graph components in Svelte 5. Use when asked to create a graph, add a visualization, build a chart, make a plot, visualize data, add slider controls to a graph, or create a new graph page. Handles 60fps slider updates, throttling, data precomputation, and proper Svelte 5 reactivity patterns.
Basketball statistics formatting using BasketballStats\StatsFormatter for percentages, averages, and totals. Use when displaying stats, calculating averages, or formatting basketball numbers.
Automate Splunk queries and analyze results using Chrome DevTools MCP. Use when the user wants to run Splunk searches, export log data, or analyze Splunk results. Triggers on requests like "check error rates", "search Splunk for X", "run a Splunk query", "analyze logs from Splunk", or "find errors in payment-service".
Create new blog posts and data analyses for the Data Blog. Use when the user wants to create a new blog post, add a new analysis, or set up a new data visualization. This includes creating the content.mdx file with proper frontmatter, setting up the directory structure (data/, results/, src/), and implementing dashboard components with charts, tables, and maps.
Automate the end-to-end process of handling a new API request, from model generation to Data Source integration.
Use when implementing a new data source adapter for metapyle, before writing any source code