Time Series Analysis Agent Skill

Temporal pattern detection and forecasting — trends, seasonality, anomaly detection and simple forecasting models for planning.

Context cost
2.3k tokensestimated from the bundle, loaded when it triggers
Bundle
4 files · 16.2 kB1 script among them — read before you run
Licence
MITits repository’s licence
Last change
—no release on file
Servers it uses
Noneruns standalone

What it does

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.

What this skill changes about the agent has not been set out here as a list. Its SKILL.md, shown below, says it in the author’s own words.

anomaly-detectionforecastingtime-series

The skill itself

A skill is instructions the model reads, so you can see what you are getting: below is the start of its SKILL.md. The front matter loads with every session, the body loads when the skill triggers, and the whole file comes with the install.

SKILL.md2.9 kB · preview
--- name: time-series-analysis ---
6# Time Series Analysis
7
8# When to use
9- Building a forecast for operational planning (staffing, inventory, infrastructure capacity)
10- Identifying whether a trend is genuine or driven by seasonality
11- Detecting anomalies in a metric stream (traffic spikes, revenue dips, error rate surges)
12- Providing a "what would have happened" baseline for measuring initiative impact
13- Presenting year-over-year growth in a way that accounts for seasonal patterns
14
15# Process
161. **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).
172. **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.
183. **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.
194. **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.
205. **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.
216. **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.
22
23# Inputs the skill needs
24- Time series data: date column + one numeric metric column, minimum 2 full seasonal cycles
This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md396 words
Files4
LicenceMIT (repository)
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈60
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
2,190
on trigger
The instruction body and 3 supporting files, read only when the skill fires.
1.1%
of a 200k window
Ten skills this size would take about 11% of the window before you open a file.
050k100k150k200k context window

2.3k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Middling. Fine to keep on in a project where you use it weekly, worth unloading in one where you never do.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

The procedure it runs

The procedure has not been set out here step by step. It is in the body of its SKILL.md: the start of it is shown above, and the whole file comes with the install.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

Its SKILL.md does not declare which tools it asks the agent for, so what it touches is whatever the instructions themselves ask for — read them before you install it.

What it asks for
Writes filesnot declared
Network accessnot declared

This SKILL.md carries no allowed-tools line, so neither is declared. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

4 files, 16.2 kB on disk. Mostly text — the instructions the model reads — with 1 script in it that your client would run only if the instructions tell it to.

  • SKILL.md2.9 kB
  • assets/ts_report_template.md2.3 kB
  • references/ts_patterns_guide.md3.8 kB
  • scripts/ts_analyzer.py7.2 kB
What is not in it

A skill installs nothing and depends on nothing: it is a folder your client reads. This one carries 1 script beside the text, so the bundle is 4 files you can review in full before installing. The MIT licence covers the templates and examples as well as the instructions.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

# Time Series Analysis · 2.3k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/time-series-analysis/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/time-series-analysis" ] && { [ ! -e .claude/skills/time-series-analysis ] || { mv .claude/skills/time-series-analysis "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/time-series-analysis" .claude/skills/ && echo "Installed .claude/skills/time-series-analysis"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add nimrodfisher/time-series-analysis

Windows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither. Writes to .claude/skills/time-series-analysis/ in the current project. For every project instead, run mkdir -p ~/.claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/time-series-analysis/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/time-series-analysis" ] && { [ ! -e ~/.claude/skills/time-series-analysis ] || { mv ~/.claude/skills/time-series-analysis "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/time-series-analysis" ~/.claude/skills/ && echo "Installed ~/.claude/skills/time-series-analysis" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/time-series-analysis/ only after the download succeeds, so files left there by another skill of the same name, or by an older release, do not mix in. A copy already there is moved aside, not deleted, and the line prints where.

Which clients pick it up on their own

A skill is a folder of text. Most of these read a skills folder and pick it up without being told; the rest take the same folder another way — an upload in the app, a parameter on an API call — and then choose it by its description just the same.

Claude Code.claude/skills/
Claude DesktopCustomize › Skills
ChatGPTSkills › Create › Upload
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok Build.grok/skills/
Microsoft CopilotSkills › Upload a skill
PerplexityComputer › Skills › Upload a skill
DeepSeek Harness.dsh/skills/
Zed.agents/skills/
Devin Desktop.devin/skills/
Windsurf (legacy).windsurf/skills/
OpenAI Agents SDKInstructions or sandbox Skills
HTTP / APIa request parameter
This release
Versionnot versioned
Publishedno release date on file
PriceFree
Referencenimrodfisher/time-series-analysis

Versions

Its author publishes no version number, so there is nothing here to pin to: what you install is the folder as it stands today. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

Pinning

Nothing to pin to: this skill carries no version number of its own. What you install is what the folder holds on the day you install it.

Reviews

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Who wrote it

NI
nimrodfisher

Publishes on mcprush.

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