productivity▌

Structured prompt template for generating standardized conventional commit messages. \n \n Provides XML-formatted workflow guiding users through staging changes, inspecting diffs, and constructing commits with type, scope, description, body, and footer fields \n Includes validation rules enforcing Conventional Commits specification compliance, with allowed types (feat, fix, docs, style, refactor, perf, test, build, ci, chore, revert) \n Offers six practical examples covering common commit patter

Role: Scroll Experience Architect

$22

Transcribe audio and video to text with speaker identification, word-level timestamps, and 90+ language support. \n \n Two models available: scribe_v2 for batch transcription with high accuracy, and scribe_v2_realtime for live transcription with ~150ms latency \n Speaker diarization labels each word with speaker ID; keyterm prompting helps recognize domain-specific vocabulary and proper nouns \n Word-level timestamps include type classification (word, spacing, audio event) for precise timing and

Transform generic writing into Xiaohongshu-native format with authentic, relatable style. \n \n Converts formal article structure into short paragraphs, numbered lists, and visual hierarchy optimized for fast mobile browsing \n Applies platform-specific tone: conversational language (\"姐妹们\"), moderate emoji use (1–2 per section), and real-experience framing over instructional voice \n Preserves all original images and captions while restructuring text into 300–800 word posts with clear section

Seamless AI agent session transfers with comprehensive context preservation and validation. \n \n Automatically triggers on user requests, context window capacity warnings, task milestones, or work session endings; proactively suggests handoffs after substantial work \n CREATE workflow generates timestamped handoff documents with pre-filled project metadata, git history, and modified files, then validates for completeness and security \n RESUME workflow loads handoffs with staleness checking, co

Essential Datadog skills for AI agents.

Master RxJS in Angular for handling async operations, data streams, and reactive programming patterns.

Keep this workflow focused on existing debug windows and menu entries. Do not add a new utility/debug control window unless the user asks explicitly.

Dataset exploration, cleaning, statistical analysis, and visualization in Python or SQL. \n \n Supports CSV, JSON, and SQL data sources with pandas DataFrames and direct database queries \n Covers the full analysis pipeline: data loading, missing value handling, outlier detection, grouping, correlation analysis, and pivot tables \n Includes visualization templates for histograms, boxplots, heatmaps, and time series using matplotlib and seaborn \n Generates structured markdown reports with datase