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.
Temporal pattern detection and forecasting. An agent skill from nimrodfisher/data-analytics-skills.
Install Time Series Analysis
$ npx skills add nimrodfisher/data-analytics-skills --skill time-series-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install nimrodfisher/data-analytics-skills time-series-analysis --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/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/03-data-analysis-investigation/time-series-analysis .claude/skills/time-series-analysis && 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 "time-series-analysis" agent skill from https://github.com/nimrodfisher/data-analytics-skills/tree/main/03-data-analysis-investigation/time-series-analysis into .claude/skills/time-series-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "time-series-analysis", 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/nimrodfisher/data-analytics-skills/tree/main/03-data-analysis-investigation/time-series-analysisType 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 nimrodfisher/data-analytics-skills --skill time-series-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install nimrodfisher/data-analytics-skills time-series-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/03-data-analysis-investigation/time-series-analysis .agents/skills/time-series-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "time-series-analysis" agent skill from https://github.com/nimrodfisher/data-analytics-skills/tree/main/03-data-analysis-investigation/time-series-analysis into .agents/skills/time-series-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "time-series-analysis", 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 nimrodfisher/data-analytics-skills --skill time-series-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install nimrodfisher/data-analytics-skills time-series-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/03-data-analysis-investigation/time-series-analysis .cursor/skills/time-series-analysis && 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 "time-series-analysis" agent skill from https://github.com/nimrodfisher/data-analytics-skills/tree/main/03-data-analysis-investigation/time-series-analysis into .cursor/skills/time-series-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "time-series-analysis", 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/nimrodfisher/data-analytics-skills.git --path 03-data-analysis-investigation/time-series-analysis--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 nimrodfisher/data-analytics-skills --skill time-series-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install nimrodfisher/data-analytics-skills time-series-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/03-data-analysis-investigation/time-series-analysis .gemini/skills/time-series-analysis && 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 "time-series-analysis" agent skill from https://github.com/nimrodfisher/data-analytics-skills/tree/main/03-data-analysis-investigation/time-series-analysis into .gemini/skills/time-series-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "time-series-analysis", 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 nimrodfisher/data-analytics-skills time-series-analysisInstalls 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 nimrodfisher/data-analytics-skills --skill time-series-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/03-data-analysis-investigation/time-series-analysis .github/skills/time-series-analysis && 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 "time-series-analysis" agent skill from https://github.com/nimrodfisher/data-analytics-skills/tree/main/03-data-analysis-investigation/time-series-analysis into .github/skills/time-series-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "time-series-analysis", 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 nimrodfisher/data-analytics-skills --skill time-series-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install nimrodfisher/data-analytics-skills time-series-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nimrodfisher/data-analytics-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/03-data-analysis-investigation/time-series-analysis .opencode/skills/time-series-analysis && 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 "time-series-analysis" agent skill from https://github.com/nimrodfisher/data-analytics-skills/tree/main/03-data-analysis-investigation/time-series-analysis into .opencode/skills/time-series-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "time-series-analysis", 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
time-series-analysis- GitHub stars
- 470
- Token cost
- ~710 tokens
- SKILL.md length
- 337 words
- Files
- 4 (incl. scripts, references, assets)
- Skills in repo
- 31
- Repo updated
- First seen
- Licence
- MIT
At a glance
Temporal pattern detection and forecasting. An agent skill from nimrodfisher/data-analytics-skills.
- Works in 6 steps: Load and inspect the time series —… → Test for stationarity — run an ADF test.… → Decompose into components — separate the… → …
- Analyzing trends over time
- Runs Python scripts from its folder
- Detecting seasonality
What it does
Time Series Analysis is an agent skill from nimrodfisher/data-analytics-skills. Temporal pattern detection and forecasting. Use when analyzing trends over time, detecting seasonality, identifying anomalies in time series, or building simple forecasting models for planning.
Its SKILL.md is about 710 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts, reference files and assets (for example `assets/ts_report_template.md`, `references/ts_patterns_guide.md` and `scripts/ts_analyzer.py`).
It sits in Data & Analytics, covering Forecasting and time series. The repository describes itself as: A comprehensive list of Claude & Codex skills for a wide range of data analytics tasks. The licence is MIT.
When your agent uses it
- Analyzing trends over time
- Detecting seasonality
- Identifying anomalies in time series
- Building simple forecasting models for planning
Example prompts
- “/time-series-analysis”
Requirements
- Python 3
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Load and inspect the time series — confirm regular intervals (fill gaps if needed), check for obvious data quality issues (negative…
- Test for stationarity — run an ADF test. If non-stationary (trend or seasonality present), note this — it informs decomposition and model…
- Decompose into components — separate the time series into trend, seasonal, and residual using additive or multiplicative decomposition…
- Detect anomalies — flag points more than 3 standard deviations from the rolling median. Investigate the top 5 anomalies against the event…
- Fit a forecast model — fit an ARIMA model (or simpler moving average if data is short). Validate on a held-out 20% test set and report…
- Produce the analysis report — summarise trend direction and strength, seasonal patterns and their business implications, anomaly findings…
What it can do on your machine
Read from SKILL.md and the folder at commit 9449d36. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
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.
Context cost
Time Series Analysis loads about 710 tokens when it runs, and up to ~1.7k if it reads all its reference files. Until then it costs about 54 tokens; SKILL.md has 337 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 nimrodfisher/data-analytics-skills at commit 9449d36, republished under its MIT licence (© nimrodfisher). 337 words, ~710 tokens.
Download SKILL.mdSave it as
.claude/skills/time-series-analysis/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- time-series-analysis
- description
- Temporal pattern detection and forecasting. Use when analyzing trends over time, detecting seasonality, identifying anomalies in time series, or building simple forecasting models for planning.
Time Series Analysis
When to use
- Building a forecast for operational planning (staffing, inventory, infrastructure capacity)
- Identifying whether a trend is genuine or driven by seasonality
- Detecting anomalies in a metric stream (traffic spikes, revenue dips, error rate surges)
- Providing a "what would have happened" baseline for measuring initiative impact
- Presenting year-over-year growth in a way that accounts for seasonal patterns
Process
- Load and inspect the time series — confirm regular intervals (fill gaps if needed), check for obvious data quality issues (negative values, zeros in non-zero series), and identify the natural granularity (daily, weekly, monthly).
- Test for stationarity — run an ADF test. If non-stationary (trend or seasonality present), note this — it informs decomposition and model choice rather than blocking analysis. See
references/ts_patterns_guide.md. - Decompose into components — separate the time series into trend, seasonal, and residual using additive or multiplicative decomposition. Measure the strength of each component (0–1). Strong seasonality (>0.6) means raw values are misleading without seasonal adjustment.
- Detect anomalies — flag points more than 3 standard deviations from the rolling median. Investigate the top 5 anomalies against the event log (product releases, campaigns, incidents). Use
scripts/ts_analyzer.py --detect-anomalies. - Fit a forecast model — fit an ARIMA model (or simpler moving average if data is short). Validate on a held-out 20% test set and report MAPE. Generate point estimates and 95% confidence intervals for the forecast horizon.
- Produce the analysis report — summarise trend direction and strength, seasonal patterns and their business implications, anomaly findings, and the forecast with uncertainty. Use
assets/ts_report_template.md.
Inputs the skill needs
- Time series data: date column + one numeric metric column, minimum 2 full seasonal cycles
- Granularity of the data (daily, weekly, monthly)
- Forecast horizon required (days, weeks, months ahead)
- Event log or change log for anomaly investigation
- Business context: what drives this metric, known seasonal patterns
Output
scripts/ts_analyzer.py— decomposes, detects anomalies, and fits an ARIMA forecast; outputs charts and CSVreferences/ts_patterns_guide.md— stationarity, seasonality types, model selection guide, and common pitfallsassets/ts_report_template.md— report template: characteristics, decomposition summary, anomaly list, forecast table, insights
© nimrodfisher, 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 3 other files (scripts, references, assets) in 03-data-analysis-investigation/time-series-analysis of nimrodfisher/data-analytics-skills.
- SKILL.md
- assets/ts_report_template.md
- references/ts_patterns_guide.md
- scripts/ts_analyzer.py
Open the folder on GitHubat commit 9449d36
Compare with similar skills
Time Series Analysis 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 |
|---|---|---|---|---|---|---|
| Time Series Analysis this skillnimrodfisher/data-analytics-skills | 470 | — | ~710 | 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 Time Series Analysis
What does Time Series Analysis do?
Temporal pattern detection and forecasting. An agent skill from nimrodfisher/data-analytics-skills. Time Series Analysis is an agent skill from nimrodfisher/data-analytics-skills. Temporal pattern detection and forecasting.
When should I use Time Series Analysis?
Time Series Analysis fits situations like: analyzing trends over time; detecting seasonality; identifying anomalies in time series; building simple forecasting models for planning.
How do I install Time Series Analysis in Claude Code?
Run `npx skills add nimrodfisher/data-analytics-skills --skill time-series-analysis -a claude-code`. Or copy the skill folder (03-data-analysis-investigation/time-series-analysis in nimrodfisher/data-analytics-skills) into .claude/skills/time-series-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Time Series Analysis in Codex?
Run `npx skills add nimrodfisher/data-analytics-skills --skill time-series-analysis -a codex`. Or copy the skill folder (03-data-analysis-investigation/time-series-analysis in nimrodfisher/data-analytics-skills) into .agents/skills/time-series-analysis in your project. Codex loads it when a task matches its description.
Can I use Time Series Analysis 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 nimrodfisher/data-analytics-skills --skill time-series-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/time-series-analysis, .gemini/skills/time-series-analysis, .github/skills/time-series-analysis and .opencode/skills/time-series-analysis in your project.
What does Time Series Analysis need to run?
Going by SKILL.md and its folder, Time Series Analysis needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Time Series Analysis 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 Time Series Analysis 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 Time Series Analysis use?
Time Series Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Time Series Analysis use?
About 710 tokens (SKILL.md is roughly 2.8k 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 941 tokens, read only when the agent opens those files.
What are the alternatives to Time Series Analysis?
Skills that share tags, products or a category with Time Series Analysis: 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 Time Series Analysis?
nimrodfisher (a GitHub user) maintains it in nimrodfisher/data-analytics-skills, which has 470 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on September 25, 2026.
Source: nimrodfisher/data-analytics-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.