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Time series decomposition v1.0.0
Use this resource to decompose a time series into trend, seasonality and residual
New
- 367 downloads
- 218 likes
- 241 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install time-series-decompositionWith no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.
First time: connect the CLI with
npx --yes palatekit@latest loginThe agent picks the decomposition model, runs the analysis and interprets each component. You get the computed components and a note on what they show.
Mostly picked by
Updated November 2, 2026
Previews
Details
- Install guides
- Generates with
- Your agent's model
- Licence
- MIT
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What you get
- SKILL.md: decomposition method and interpretation steps
- SKILL.md: analysis examples and expected output
Good fit for
- Your monthly sales show seasonality you want to isolate
- You need to know whether a rise is lasting or one-off
Not for
Tags
- time series
- seasonality
- trend
- analysis
About
You say
“Decompose my weekly sales over three years and tell me whether the trend is really rising.”
Skill published by Jeremy Longshore <jeremy@intentsolutions.io> under the MIT license, delivered in its original version.
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How to use it
- Install the skill in your agent's skills folder
- Ask your agent to decompose a time series into trend, seasonality and residual
- Review and adjust the result
Content preview
Files
- LICENSE1.1 KB
- NOTICE-PALATEKIT.md0.6 KB
- SKILL.md2.3 KB
Origin and licence
Listed unmodified
- Author
- Jeremy Longshore <jeremy@intentsolutions.io>
- Source
- github.com/jeremylongshore/tons-of-skills-marketplace/tree/ab85a061f7bcc039dac13ee193de7a4cd4388571/skills/12-data-analytics/time-series-decomposer
- Licence
- MIT
Notice
« time-series-decomposer » (Jeremy Longshore <jeremy@intentsolutions.io>, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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