Marketplace
Everything your AI needs, in one place.
Ready-made agents, skills, personas, prompts, templates and tools. Each one is checked before it goes live, works with any model, and installs in a click. Rate what you use so the best rises to the top.
- 143.8K
- listings
- 1
- installs
- 0
- reviews
- 38.7K
- publishers
A service that does a whole job for you - research, coding, support - and reports back.
Step-by-step instructions an AI follows for one kind of task. Install once, reuse everywhere.
A voice and set of rules layered onto any model: tone, audience, do's and don'ts.
A ready-to-use prompt with fill-in-the-blank variables and notes on when it works best.
A complete routing setup - models, rules and settings - in one file you can apply in a minute.
A single function an AI can call: a calculator, a search, a database lookup.
A language model endpoint with its price, speed and quality declared so the router can compare it.
influxdb
Set up and manage InfluxDB for time-series data storage, querying, and analysis. Use when a user needs to configure InfluxDB buckets, write Flux queries, set up retention policies, create tasks for da
timesfm
Forecast time series data using Google's TimesFM foundation model with zero-shot prediction. Use when: forecasting sales or demand, predicting server metrics, financial time series analysis, anomaly d
victoriametrics
Deploy and configure VictoriaMetrics as a high-performance time-series database for metrics storage and querying. Use when a user needs a Prometheus-compatible long-term storage backend, wants to writ
Time Series Imputation Feasibility Analysis
Analyze the feasibility of imputing missing data for short time series by checking date alignment with similar series based on shared key columns using Polars.
obspy
Seismology data processing with ObsPy. Helps with reading seismic waveforms, filtering/processing time series, fetching data from FDSN services, and earthquake analysis. Use when Claude needs to: (1)
statsforecast_polars_ensemble_pipeline
Execute a univariate time series forecasting pipeline using StatsForecast and Polars. Includes ID concatenation, cross-validation, ensemble generation (AutoARIMA, AutoETS, DynamicOptimizedTheta), non-
forecast-operational-metrics
キャパシティプランニング、コスト最適化、プロアクティブなスケーリングのためにProphetまたは statsmodelsを使用してインフラおよびアプリケーションメトリクスを予測する。Grafanaで予測を 可視化し、予測されるリソース枯渇のアラートを設定する。インフラキャパシティ需要（CPU、 メモリ、ディスク）の予測時、次の四半期のハードウェア調達計画時、コストトレンドの予測に よるクラウド支出
pandas-data-processing
Pandas for time series analysis, OrcaFlex results processing, and marine engineering data workflows
Find
Search or browse by kind. Every card shows who made it, how many people installed it and what they think.
Install
One click. You get a manifest the router understands, plus copy-paste snippets for the CLI, Python and YAML.
Rate and publish
Leave a star rating after you have used it. Made something useful? Publish it - free listings go live immediately.
Prefer the terminal? osr stack apply registry://starter installs the starter template.