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Found 59 Skills
Pose classification using ST-GCN (Spatial Temporal Graph Convolutional Network). Classifies skeleton sequences into action categories from pose-keypoint data. Use when training, evaluating, exporting, or running inference for a TAO pose-classification model. Trigger phrases include "train pose classification", "skeleton action recognition", "ST-GCN", "keypoint sequence classifier".
Expert in temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event detection. Activate on 'event detection', 'temporal clustering', 'ST-DBSCAN', 'spatio-temporal', 'shareability prediction', 'place recognition', 'life events', 'photo events', 'temporal diversity'. NOT for individual photo aesthetic quality (use photo-composition-critic), color palette analysis (use color-theory-palette-harmony-expert), face recognition implementation (use photo-content-recognition-curation-expert), or basic EXIF timestamp extraction.
Use the `date` command via Bash tool whenever you or the user mention time, dates, or temporal concepts. Verify current date/time before ANY temporal response, as environment context may be outdated. Parse expressions like "tomorrow", "next week", "3 days", "in 2 weeks", "next Monday at 3pm". Proactively invoke for deadlines, schedules, time-sensitive tasks, week numbers, or any date/time reference.
This skill should be used when the user asks to forecast aggregate sentiment and opinion dynamics over time—sentiment indices from text streams; temporal rollups; leading/lagging KPI links; time-series and sequence models (ARIMA, Prophet, state-space, ML); nowcasting; spikes, bots, and bias; walk-forward backtests; intervals and scenarios; volume/velocity/topic features; BI or brand dashboards. Triggers: sentiment forecasting, forecast sentiment, sentiment index, opinion trend forecast, social sentiment time series, brand sentiment trajectory, nowcast sentiment, sentiment leading indicator, aggregate polarity forecast, sentiment backtest, walk-forward sentiment, sentiment spike prediction. Not for per-text labeling (sentiment-analysis-engineer), demand forecasting without sentiment (predictive-logistics-developer, data-scientist), trade advice (methodology only), marketing copy (content-creator), macro without text sentiment (financial-analyst partial).
Use pkm for personal knowledge management with temporal awareness, quality filtering, hybrid search, and relationship tracking with LSP and MCP server integration.
Use when writing, fixing, or editing TypeScript modules, classes, file structure, declaration order, vertical formatting, dependency direction, cohesion, coupling, dependency construction, temporal coupling, public exports, wiring, or over-abstraction.
Agent skill for trading-predictor - invoke with $agent-trading-predictor
Design short-term, long-term, and graph-based memory architectures
Design and implement memory architectures for agent systems. Use when building agents that need to persist state across sessions, maintain entity consistency, or reason over structured knowledge.
Use when implementing agent memory, persisting state across sessions, building knowledge graphs, tracking entities, or asking about "agent memory", "knowledge graph", "entity memory", "vector stores", "temporal knowledge", "cross-session persistence"
Microsoft SQL Server specific features. Covers data types, indexes, partitioning, and SQL Server-specific syntax. Use for SQL Server database work. USE WHEN: user mentions "sql server", "mssql", "IDENTITY", "GETDATE()", "temporal tables", "columnstore", "SQL Server specifics", "Azure SQL" DO NOT USE FOR: T-SQL programming - use `tsql` instead, PostgreSQL - use `postgresql` instead, Oracle - use `oracle` instead