TimesFM Forecasting
google-research/timesfm
Forecasts any univariate time series zero-shot with Google's TimesFM model, returning point forecasts and calibrated prediction intervals without training.
Agent skill
Forecasting Time Series Data
by jeremylongshore in jeremylongshore/tons-of-skills-marketplace
Process this skill enables AI assistant to forecast future values based on historical time series data.
Install Forecasting Time Series Data
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill forecasting-time-series-data -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace forecasting-time-series-data --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/forecasting-time-series-data .claude/skills/forecasting-time-series-data && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "forecasting-time-series-data" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/forecasting-time-series-data into .claude/skills/forecasting-time-series-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "forecasting-time-series-data", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/forecasting-time-series-dataType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill forecasting-time-series-data -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace forecasting-time-series-data --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/.curated/forecasting-time-series-data .agents/skills/forecasting-time-series-data && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "forecasting-time-series-data" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/forecasting-time-series-data into .agents/skills/forecasting-time-series-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "forecasting-time-series-data", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill forecasting-time-series-data -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace forecasting-time-series-data --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/.curated/forecasting-time-series-data .cursor/skills/forecasting-time-series-data && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "forecasting-time-series-data" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/forecasting-time-series-data into .cursor/skills/forecasting-time-series-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "forecasting-time-series-data", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/jeremylongshore/tons-of-skills-marketplace.git --path skills/.curated/forecasting-time-series-data--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill forecasting-time-series-data -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace forecasting-time-series-data --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/.curated/forecasting-time-series-data .gemini/skills/forecasting-time-series-data && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "forecasting-time-series-data" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/forecasting-time-series-data into .gemini/skills/forecasting-time-series-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "forecasting-time-series-data", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install jeremylongshore/tons-of-skills-marketplace forecasting-time-series-dataInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill forecasting-time-series-data -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/.curated/forecasting-time-series-data .github/skills/forecasting-time-series-data && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "forecasting-time-series-data" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/forecasting-time-series-data into .github/skills/forecasting-time-series-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "forecasting-time-series-data", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill forecasting-time-series-data -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace forecasting-time-series-data --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/.curated/forecasting-time-series-data .opencode/skills/forecasting-time-series-data && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "forecasting-time-series-data" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/forecasting-time-series-data into .opencode/skills/forecasting-time-series-data/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "forecasting-time-series-data", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
forecasting-time-series-data- GitHub stars
- 2.8k
- Token cost
- ~938 tokens
- SKILL.md length
- 432 words
- Files
- 7 (incl. scripts, references, assets)
- Skills in repo
- 3,342
- Repo updated
- First seen
- Licence
- MIT
At a glance
Process this skill enables AI assistant to forecast future values based on historical time series data.
- Works in 3 steps: Data Analysis: Claude analyzes the… → Model Selection: Based on the data… → Prediction Generation: The selected…
- The user asks to predict future values of a time ser..
- SKILL.md covers Overview, How It Works, When to Use This Skill and Examples, plus 7 more sections
- Runs Python scripts from its folder
What it does
Forecasting Time Series Data is an agent skill from jeremylongshore/tons-of-skills-marketplace. Process this skill enables AI assistant to forecast future values based on historical time series data. it analyzes time-dependent data to identify trends, seasonality, and other patterns. use this skill when the user asks to predict future values of a time ser... Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
Its SKILL.md is about 940 tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts, reference files and assets (for example `assets/README.md`, `assets/configuration_template.json` and `assets/visualization_template.py`). Compatibility notes: Designed for Claude Code
It sits in Data & Analytics, covering Forecasting and time series. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.
When your agent uses it
- The user asks to predict future values of a time ser..
- Appropriate context detected
- With relevant phrases based on skill purpose
Example prompts
- “/forecasting-time-series-data”
Requirements
- Python 3
- Compatibility (from SKILL.md): Designed for Claude Code
- Pre-approved tools (allowed-tools): Read, Write, Edit, Grep, Glob, Bash(cmd:*)
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Data Analysis: Claude analyzes the provided time series data, identifying key characteristics such as trends, seasonality, and…
- Model Selection: Based on the data characteristics, Claude selects an appropriate forecasting model (e.g., ARIMA, Prophet).
- Prediction Generation: The selected model is trained on the historical data, and future values are predicted along with confidence…
What it can do on your machine
Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteEditGrepGlobBash(cmd:*)
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Compatibility
Designed for Claude Code
From compatibility in the SKILL.md frontmatter.
Context cost
Forecasting Time Series Data loads about 938 tokens when it runs, and up to ~955 if it reads all its reference files. Until then it costs about 97 tokens; SKILL.md has 432 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 432 words, ~938 tokens.
Download SKILL.mdSave it as
.claude/skills/forecasting-time-series-data/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- forecasting-time-series-data
- description
- Process this skill enables AI assistant to forecast future values based on historical time series data. it analyzes time-dependent data to identify trends, seasonality, and other patterns. use this skill when the user asks to predict future values of a time ser... Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
- allowed-tools
- Read, Write, Edit, Grep, Glob, Bash(cmd:*)
- compatibility
- Designed for Claude Code
- version
- 1.23.0
- author
- Jeremy Longshore <jeremy@intentsolutions.io>
- license
- MIT
- tags
- ai, forecasting-time
Time Series Forecaster
Forecast future values from historical time series data using ARIMA, Prophet, and other models with trend, seasonality, and confidence interval analysis.
Overview
This skill empowers Claude to perform time series forecasting, providing insights into future trends and patterns. It automates the process of data analysis, model selection, and prediction generation, delivering valuable information for decision-making.
How It Works
- Data Analysis: Claude analyzes the provided time series data, identifying key characteristics such as trends, seasonality, and autocorrelation.
- Model Selection: Based on the data characteristics, Claude selects an appropriate forecasting model (e.g., ARIMA, Prophet).
- Prediction Generation: The selected model is trained on the historical data, and future values are predicted along with confidence intervals.
When to Use This Skill
This skill activates when you need to:
- Forecast future sales based on past sales data.
- Predict website traffic for the next month.
- Analyze trends in stock prices over the past year.
Examples
Example 1: Forecasting Sales
User request: "Forecast sales for the next quarter based on the past 3 years of monthly sales data."
The skill will:
- Analyze the historical sales data to identify trends and seasonality.
- Select and train a suitable forecasting model (e.g., ARIMA or Prophet).
- Generate a forecast of sales for the next quarter, including confidence intervals.
Example 2: Predicting Website Traffic
User request: "Predict weekly website traffic for the next month based on the last 6 months of data."
The skill will:
- Analyze the website traffic data to identify patterns and seasonality.
- Choose an appropriate time series forecasting model.
- Generate a forecast of weekly website traffic for the next month.
Show full SKILL.md (159 more words)Show less
Best Practices
- Data Quality: Ensure the time series data is clean, complete, and accurate for optimal forecasting results.
- Model Selection: Choose a forecasting model appropriate for the characteristics of the data (e.g., ARIMA for stationary data, Prophet for data with strong seasonality).
- Evaluation: Evaluate the performance of the forecasting model using appropriate metrics (e.g., Mean Absolute Error, Root Mean Squared Error).
Integration
This skill can be integrated with other data analysis and visualization tools within the Claude Code ecosystem to provide a comprehensive solution for time series analysis and forecasting.
Prerequisites
- Appropriate file access permissions
- Required dependencies installed
Instructions
- Invoke this skill when the trigger conditions are met
- Provide necessary context and parameters
- Review the generated output
- Apply modifications as needed
Output
The skill produces structured output relevant to the task.
Error Handling
- Invalid input: Prompts for correction
- Missing dependencies: Lists required components
- Permission errors: Suggests remediation steps
Resources
- Project documentation
- Related skills and commands
© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 6 other files (scripts, references, assets) in skills/.curated/forecasting-time-series-data of jeremylongshore/tons-of-skills-marketplace.
- SKILL.md
- assets/README.md
- assets/configuration_template.json
- assets/example_data.csv
- assets/visualization_template.py
- references/README.md
- scripts/README.md
Open the folder on GitHubat commit cfae287
Compare with similar skills
Forecasting Time Series Data next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Forecasting Time Series Data this skilljeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~938 | Automated safety check: Pass | MIT | |
| TimesFM Forecastinggoogle-research/timesfm | 34k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 | |
| StatsmodelszLanqing/codex-claude-academic-skills | 4.7k | 15 repos | ~4.9k | Automated safety check: Pass | BSD-3-Clause | |
| Timesfm ForecastingzLanqing/codex-claude-academic-skills | 4.7k | 3 repos | ~7.5k | Automated safety check: Notes | Apache-2.0 | |
| Find Hypertable Candidatestimescale/pg-aiguide | 1.9k | 1 repos | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Pensieve Searcharkohut/pensieve | 1.4k | — | ~8.2k | Automated safety check: Pass | Apache-2.0 |
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Categories
Questions about Forecasting Time Series Data
What does Forecasting Time Series Data do?
Process this skill enables AI assistant to forecast future values based on historical time series data. Forecasting Time Series Data is an agent skill from jeremylongshore/tons-of-skills-marketplace. Process this skill enables AI assistant to forecast future values based on historical time series data.
When should I use Forecasting Time Series Data?
Forecasting Time Series Data fits situations like: the user asks to predict future values of a time ser.; appropriate context detected; with relevant phrases based on skill purpose.
How do I install Forecasting Time Series Data in Claude Code?
Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill forecasting-time-series-data -a claude-code`. Or copy the skill folder (skills/.curated/forecasting-time-series-data in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/forecasting-time-series-data in your project. Claude Code loads it when a task matches its description.
How do I install Forecasting Time Series Data in Codex?
Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill forecasting-time-series-data -a codex`. Or copy the skill folder (skills/.curated/forecasting-time-series-data in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/forecasting-time-series-data in your project. Codex loads it when a task matches its description.
Can I use Forecasting Time Series Data in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill forecasting-time-series-data -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/forecasting-time-series-data, .gemini/skills/forecasting-time-series-data, .github/skills/forecasting-time-series-data and .opencode/skills/forecasting-time-series-data in your project.
What does Forecasting Time Series Data need to run?
Going by SKILL.md and its folder, Forecasting Time Series Data needs Python for the scripts in its folder. Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep, Glob, Bash(cmd:*). Compatibility (from SKILL.md): Designed for Claude Code.
Does Forecasting Time Series Data access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Forecasting Time Series Data safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Forecasting Time Series Data use?
Forecasting Time Series Data is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Forecasting Time Series Data use?
About 938 tokens (SKILL.md is roughly 3.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 17 tokens, read only when the agent opens those files.
What are the alternatives to Forecasting Time Series Data?
Skills that share tags, products or a category with Forecasting Time Series Data: TimesFM Forecasting (google-research/timesfm, 34k stars), Statsmodels (zLanqing/codex-claude-academic-skills, 4.7k stars), Timesfm Forecasting (zLanqing/codex-claude-academic-skills, 4.7k stars) and Find Hypertable Candidates (timescale/pg-aiguide, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Forecasting Time Series Data?
jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.
Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.