research-time-series-econometrics

research-time-series-econometrics is a skill for Claude Code, Codex from ItamarZand88/awesome-agent-conventions. It costs 0 tokens per session (1,767 once invoked), scanned A, a copy of time-series-guide, MIT.

A guide to analysing data recorded over time, known as time-series econometrics. It covers methods such as ARIMA and VAR models, relationships between long-term trends, forecasting, and tests for whether a series is statistically stable.

In plain words
What is it for?
Use it for economic or financial forecasting, stationarity and unit-root tests, cointegration analysis, VAR models, ARIMA models, and diagnostic checks.
Why use it?
It helps prevent misleading analyses caused by changing statistical behaviour over time, including false relationships between unrelated trends.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it for economic or financial forecasting, stationarity and unit-root tests, cointegration analysis, VAR models, ARIMA models, and diagnostic checks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/itamarzand88/awesome-agent-conventions/research-time-series-econometrics
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ItamarZand88/awesome-agent-conventions --skill research-time-series-econometrics
Clone the repo
git clone --depth 1 https://github.com/ItamarZand88/awesome-agent-conventions

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for research-time-series-econometrics

README.md
[![agentmods](https://agentmods.dev/badge/skills/itamarzand88/awesome-agent-conventions/research-time-series-econometrics/github.svg)](https://agentmods.dev/skills/itamarzand88/awesome-agent-conventions/research-time-series-econometrics)
Your own site
<a href="https://agentmods.dev/skills/itamarzand88/awesome-agent-conventions/research-time-series-econometrics"><img src="https://agentmods.dev/badge/skills/itamarzand88/awesome-agent-conventions/research-time-series-econometrics/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for research-time-series-econometrics

Your own site · 80×15
<a href="https://agentmods.dev/skills/itamarzand88/awesome-agent-conventions/research-time-series-econometrics"><img src="https://agentmods.dev/badge/skills/itamarzand88/awesome-agent-conventions/research-time-series-econometrics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,767 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 91% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.01767
Opus 5 $0.00000 $0.00883
Sonnet 5 $0.00000 $0.00353
Haiku 4.5 $0.00000 $0.00177

Measured 12d ago against content hash b37b44c1f77f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

research-time-series-econometrics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

91% identical to time-series-guide — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

conventions/skill-md/examples/data-analysis/research-time-series-econometrics/SKILL.md · 237 lines

How it starts

The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.


name: time-series-guide description: "Apply ARIMA, VAR, cointegration, and time series econometric methods" metadata: openclaw: emoji: "📉" category: "analysis" subcategory: "econometrics" keywords: ["time series", "ARIMA", "VAR", "cointegration", "stationarity", "forecasting", "econometrics"] source: "wentor-research-plugins"

Time Series Guide

A skill for applying time series econometric methods including ARIMA modeling, VAR systems, cointegration analysis, and unit root tests. Covers stationarity concepts, model selection, forecasting, and diagnostic checking for economic and financial data.

Stationarity and Unit Root Tests

Why Stationarity Matters

A time series is stationary when its statistical properties (mean, variance, autocorrelation) do not change over time. Most econometric methods require stationarity. Non-stationary series can produce spurious regressions.

Testing for Stationarity

from statsmodels.tsa.stattools import adfuller, kpss
import pandas as pd


def test_stationarity(series: pd.Series, name: str = "Series") -> dict:
    """
    Test for stationarity using ADF and KPSS tests.

    Args:
        series: Time series data
        name: Label for the series
    """
    # Augmented Dickey-Fuller test
    # H0: Unit root exists (non-stationary)
    adf_result = adfuller(series.dropna(), autolag="AIC")

    # KPSS test
    # H0: Series is stationary
    kpss_result = kpss(series.dropna(), regression="c", nlags="auto")

    return {
        "series": name,
        "adf": {
            "statistic": adf_result[0],
            "p_value": adf_result[1],
            "lags_used": adf_result[2],
            "conclusion": (
                "Stationary (reject unit root)"
                if adf_result[1] < 0.05
                else "Non-stationary (fail to reject unit root)"
            )
        },
        "kpss": {
            "statistic": kpss_result[0],
            "p_value": kpss_result[1],
            "conclusion": (
                "Non-stationary (reject stationarity)"
                if kpss_result[1] < 0.05
                else "Stationary (fail to reject stationarity)"
            )
        }
    }

Read the full file on GitHub · 237 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 237 lines · 0 tokens per session scan A b37b44c1f77f

Subscribe to this mod's changes

research-time-series-econometrics is a skill published in the GitHub repository ItamarZand88/awesome-agent-conventions (31 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,767 tokens. A static security scan graded it A with 0 findings. It is 91% identical to time-series-guide, differing in 1 line, and is treated as a copy.