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Install in OpenClaw
/install time-series-analysis
Description
Comprehensive time series data science skill covering feature engineering, model training, and competition-winning strategies for forecasting and prediction problems.
Usage Guidance
This skill is an instruction-only guide for time-series modeling and appears coherent and proportionate. Before using it, ensure your runtime has the expected libraries (numpy, pandas, lightgbm, sklearn) installed in a controlled environment. Review any code snippets and test them on non-sensitive or synthetic data first — the skill will produce runnable code patterns but does not itself validate security or data privacy. If you plan to run it inside an agent that can execute code, run it in an isolated environment (container or VM) and avoid feeding the skill sensitive credentials or private data unless you trust where execution will run.
Capability Assessment
Purpose & Capability
The name and description match the content: the SKILL.md is a comprehensive guide for feature engineering, validation, and model training for time-series forecasting. The examples reference libraries and patterns (pandas, numpy, LightGBM, sklearn) that are appropriate for the stated purpose. (Minor cosmetic inconsistency: the provided skill name has a small typo 'time-sereis-analysis' while the slug is 'time-series-analysis', but this does not affect security.)
Instruction Scope
The SKILL.md contains code snippets and prescriptive modeling advice but does not instruct the agent to read arbitrary system files, access environment variables, or contact external endpoints. It stays within the data-science scope (data transforms, model training, validation).
Install Mechanism
No install spec is provided (instruction-only), so nothing will be written to disk by the skill itself — this is low risk. Note: the guide assumes common Python libraries (numpy, pandas, lightgbm, sklearn) but does not declare dependencies; an agent or user may need to install these separately.
Credentials
The skill requests no environment variables, credentials, or config paths. The only resources implied are typical ML libraries and compute; no secret access is requested nor appears necessary for the described tasks.
Persistence & Privilege
The skill is not always-enabled and does not request persistent system presence or modify other skills. Autonomous invocation is allowed by default (platform normal), but the skill itself does not request elevated privileges.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install time-series-analysis - After installation, invoke the skill by name or use
/time-series-analysis - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of the Time Series Data Science skill, a comprehensive end-to-end guide and toolkit for competitive time series forecasting and prediction.
- Covers feature engineering (lags, rolling stats, EWM, target encoding, interactions), model training, and robust validation strategies tailored for time series.
- Provides proven best practices and code templates for LightGBM training, ensembling, and horizon-specific modeling.
- Includes a full EDA checklist, practical competition workflow diagram, and ready-to-use pipeline commands.
- Lists common pitfalls in time series forecasting and actionable solutions.
- Designed for integration with related data science and analytics workflows.
Metadata
Frequently Asked Questions
What is time-sereis-analysis?
Comprehensive time series data science skill covering feature engineering, model training, and competition-winning strategies for forecasting and prediction problems. It is an AI Agent Skill for Claude Code / OpenClaw, with 1589 downloads so far.
How do I install time-sereis-analysis?
Run "/install time-series-analysis" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is time-sereis-analysis free?
Yes, time-sereis-analysis is completely free (open-source). You can download, install and use it at no cost.
Which platforms does time-sereis-analysis support?
time-sereis-analysis is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created time-sereis-analysis?
It is built and maintained by dubnium0 (@dubnium0); the current version is v1.0.0.
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