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 skills add LeoLin990405/r-analytics-skill --skill r-mlgit clone --depth 1 https://github.com/LeoLin990405/r-analytics-skillWrote 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.
[](https://agentmods.dev/skills/leolin990405/r-analytics-skill/r-ml)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/r-ml"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/r-ml/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.
<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/r-ml"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/r-ml.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.01630 |
| Opus 5.5 | $0.00017 | $0.00652 |
| Sonnet 5.5 | $0.00008 | $0.00326 |
| Haiku 4.5 | $0.00004 | $0.00163 |
Grade A, and why
r-ml 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 2mo 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
R Machine Learning Skill
Sub-skills
| Sub-skill | Description |
|---|---|
| r-ml-frameworks | tidymodels, caret, mlr3, h2o |
| r-ml-boosting | xgboost, lightgbm, gbm |
| r-ml-trees | randomForest, ranger, rpart |
| r-ml-regularization | glmnet, lasso, elastic-net |
| r-ml-deeplearning | torch, keras, neural networks |
| r-ml-timeseries | prophet, fable, forecast |
| r-ml-survival | survival, survminer |
| r-ml-anomaly | AnomalyDetection, anomalize |
Machine learning and predictive modeling in R.
ML Frameworks
| Package | Description |
|---|---|
| caret ★ | Classification and Regression Training |
| mlr3 ★ | Next-gen extensible ML framework |
| tidymodels ★ | Tidyverse-friendly modeling |
| h2o | Deep learning, RF, GBM, GLM |
Gradient Boosting
| Package | Description |
|---|---|
| xgboost ★ | eXtreme Gradient Boosting |
| lightgbm ★ | Light Gradient Boosting Machine |
| gbm | Generalized Boosted Regression |
| bst | Gradient Boosting |
| mboost | Model-Based Boosting |
| CoxBoost | Cox models boosting |
| GAMBoost | GAM boosting |
| gamboostLSS | GAMLSS boosting |
| GMMBoost | Mixed models boosting |
Tree-Based Methods
| Package | Description |
|---|---|
| randomForest | Breiman's random forests |
| ranger ★ | Fast random forests |
| randomForestSRC | RF for survival/regression/classification |
| rpart | Recursive partitioning trees |
| party | Recursive partitioning lab |
| partykit | Partitioning toolkit |
| C50 | C5.0 Decision Trees |
| Cubist | Rule-based regression |
| evtree | Evolutionary trees |
| tree | Classification/regression trees |
| bigrf | Big Random Forests |
What ships with it
56 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- r-ml-anomaly/anomalize/SKILL.md 3.1 KB
- r-ml-anomaly/AnomalyDetection/SKILL.md 3.0 KB
- r-ml-anomaly/SKILL.md 3.1 KB
- r-ml-boosting/lightgbm/SKILL.md 3.2 KB
- r-ml-boosting/SKILL.md 3.2 KB
- r-ml-boosting/xgboost/SKILL.md 3.5 KB
- r-ml-clustering/cluster/SKILL.md 1.7 KB
- r-ml-clustering/dbscan/SKILL.md 1.6 KB
- r-ml-clustering/factoextra/SKILL.md 1.9 KB
- r-ml-clustering/mclust/SKILL.md 1.7 KB
- r-ml-clustering/SKILL.md 428 B
- r-ml-deeplearning/keras/SKILL.md 1.8 KB
- r-ml-deeplearning/SKILL.md 3.6 KB
- r-ml-deeplearning/torch/SKILL.md 1.6 KB
- r-ml-dimensionality/irlba/SKILL.md 1.6 KB
- r-ml-dimensionality/Rtsne/SKILL.md 1.7 KB
- r-ml-dimensionality/SKILL.md 390 B
- r-ml-dimensionality/umap/SKILL.md 1.8 KB
- r-ml-frameworks/arules/SKILL.md 3.3 KB
- r-ml-frameworks/Boruta/SKILL.md 2.7 KB
- r-ml-frameworks/caret/SKILL.md 3.3 KB
- r-ml-frameworks/e1071/SKILL.md 3.1 KB
- r-ml-frameworks/gbm/SKILL.md 3.7 KB
- r-ml-frameworks/h2o/SKILL.md 1.5 KB
- r-ml-frameworks/kernlab/SKILL.md 3.4 KB
- r-ml-frameworks/lme4/SKILL.md 2.6 KB
- r-ml-frameworks/mlr3/SKILL.md 1.7 KB
- r-ml-frameworks/nlme/SKILL.md 3.5 KB
- r-ml-frameworks/randomForest/SKILL.md 3.1 KB
- r-ml-frameworks/rpart/SKILL.md 3.2 KB
- r-ml-frameworks/SKILL.md 3.3 KB
- r-ml-frameworks/tidymodels/SKILL.md 3.8 KB
- r-ml-interpretability/DALEX/SKILL.md 2.0 KB
- r-ml-interpretability/iml/SKILL.md 1.8 KB
- r-ml-interpretability/lime/SKILL.md 2.3 KB
- r-ml-interpretability/SKILL.md 398 B
- r-ml-interpretability/vip/SKILL.md 2.1 KB
- r-ml-regularization/glmnet/SKILL.md 2.5 KB
- r-ml-regularization/SKILL.md 3.0 KB
- r-ml-survival/SKILL.md 2.8 KB
- r-ml-survival/survival/SKILL.md 3.2 KB
- r-ml-survival/survminer/SKILL.md 3.7 KB
- r-ml-timeseries/fable/SKILL.md 1.6 KB
- r-ml-timeseries/forecast/SKILL.md 1.6 KB
- r-ml-timeseries/prophet/SKILL.md 2.9 KB
- r-ml-timeseries/SKILL.md 3.0 KB
- r-ml-timeseries/tsibble/SKILL.md 1.5 KB
- r-ml-trees/ranger/SKILL.md 3.0 KB
- r-ml-trees/SKILL.md 2.8 KB
- sub-skills/r-ml-deeplearning/sub-skills/keras/SKILL.md 1.8 KB
- sub-skills/r-ml-deeplearning/sub-skills/torch/SKILL.md 1.6 KB
- sub-skills/r-ml-frameworks/sub-skills/h2o/SKILL.md 1.5 KB
- sub-skills/r-ml-frameworks/sub-skills/mlr3/SKILL.md 1.7 KB
- sub-skills/r-ml-timeseries/sub-skills/fable/SKILL.md 1.6 KB
- sub-skills/r-ml-timeseries/sub-skills/forecast/SKILL.md 1.6 KB
- sub-skills/r-ml-timeseries/sub-skills/tsibble/SKILL.md 1.5 KB
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.
- 2mo ago First seen · 199 lines · 42 tokens per session scan A 9453c6252588
r-ml is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 2d ago), licensed MIT. It adds 42 tokens to every session and 1,630 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
r-ml compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| r-mlLeoLin990405/r-analytics-skill | Skill | 5 | 2d ago | MIT | A | 42 | Claude Code, Codex |
| ask-zillizzilliztech/zilliz-plugin | Skill | 3 | 14d ago | Apache-2.0 | A | 236 | Claude Code |
| collectionzilliztech/zilliz-plugin | Skill | 3 | 14d ago | Apache-2.0 | A | 32 | Claude Code |
| importzilliztech/zilliz-plugin | Skill | 3 | 14d ago | Apache-2.0 | A | 35 | Claude Code |
| vectorzilliztech/zilliz-plugin | Skill | 3 | 14d ago | Apache-2.0 | A | 28 | Claude Code |
| volumezilliztech/zilliz-plugin | Skill | 3 | 14d ago | Apache-2.0 | A | 41 | Claude Code |
| data-analysisfurkangonel/cowrangler | Skill | 1 | 1mo ago | MIT | A | 15 | Claude Code, Codex |