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.
npx agentmods add skills/wentorai/research-plugins/panel-data-guidenpx skills add wentorai/research-plugins --skill panel-data-guidegit clone --depth 1 https://github.com/wentorai/research-pluginsWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00013 | $0.02886 |
| Opus 5 | $0.00006 | $0.01443 |
| Sonnet 5 | $0.00003 | $0.00577 |
| Haiku 4.5 | $0.00001 | $0.00289 |
Grade A, and why
panel-data-guide 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 364 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Panel Data Analysis Guide
Estimate and interpret fixed effects, random effects, and dynamic panel models using Stata, R, and Python for longitudinal/panel datasets.
What Is Panel Data?
Panel data (also called longitudinal or cross-sectional time-series data) tracks the same units (individuals, firms, countries) across multiple time periods. This structure enables:
- Controlling for unobserved heterogeneity (time-invariant omitted variables)
- Studying dynamic relationships (how X at time t affects Y at time t+1)
- Increased statistical power through more observations
Data Structure
| unit_id | year | gdp_growth | investment | trade_openness |
|---------|------|-----------|------------|----------------|
| USA | 2015 | 2.9 | 20.5 | 28.3 |
| USA | 2016 | 1.7 | 20.1 | 27.1 |
| USA | 2017 | 2.3 | 20.8 | 27.5 |
| CHN | 2015 | 6.9 | 43.3 | 39.9 |
| CHN | 2016 | 6.7 | 42.7 | 37.2 |
| CHN | 2017 | 6.9 | 43.1 | 38.1 |
Key notation:
- i = unit (cross-sectional dimension): i = 1, ..., N
- t = time period: t = 1, ..., T
- Y_it = dependent variable for unit i at time t
Model Specification
Pooled OLS
Y_it = alpha + beta * X_it + epsilon_it
Ignores panel structure; assumes no unit-specific effects. Rarely appropriate.
Fixed Effects (FE) Model
Y_it = alpha_i + beta * X_it + epsilon_it
Each unit has its own intercept (alpha_i) that captures all time-invariant unobserved heterogeneity. The "within" estimator removes alpha_i by demeaning.
Random Effects (RE) Model
Y_it = alpha + beta * X_it + u_i + epsilon_it
The unit-specific effect u_i is treated as random and uncorrelated with X_it.
Estimation in Stata
Setting Up Panel Data
* Declare panel structure
xtset country_id year
* Summarize within and between variation
xtsum gdp_growth investment trade_openness
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.
- 3d ago First seen · 364 lines · 13 tokens per session scan A 8de12f06f62f
panel-data-guide is a skill published in the GitHub repository wentorai/research-plugins (284 stars, last pushed 2mo ago), licensed MIT. It adds 13 tokens to every session and 2,886 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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