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 survminergit 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/survminer)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/survminer"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/survminer.svg" alt="Measured on agentmods" 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 | $0.00024 | $0.01194 |
| Opus 5 | $0.00012 | $0.00597 |
| Sonnet 5 | $0.00005 | $0.00239 |
| Haiku 4.5 | $0.00002 | $0.00119 |
Grade A, and why
survminer 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 4d 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 — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
survminer
Publication-ready survival analysis plots.
Kaplan-Meier Plots
library(survminer)
library(survival)
# Fit survival
fit <- survfit(Surv(time, status) ~ sex, data = lung)
# Basic plot
ggsurvplot(fit, data = lung)
# With confidence intervals
ggsurvplot(fit, data = lung, conf.int = TRUE)
# With risk table
ggsurvplot(fit, data = lung, risk.table = TRUE)
# With p-value
ggsurvplot(fit, data = lung, pval = TRUE)
# With median survival
ggsurvplot(fit, data = lung, surv.median.line = "hv")
Customization
ggsurvplot(fit, data = lung,
# Colors
palette = c("#E7B800", "#2E9FDF"),
# Line types
linetype = "strata",
# Confidence interval
conf.int = TRUE,
conf.int.style = "ribbon",
# Risk table
risk.table = TRUE,
risk.table.col = "strata",
# Labels
legend.title = "Sex",
legend.labs = c("Male", "Female"),
xlab = "Time (days)",
ylab = "Survival probability",
# Theme
ggtheme = theme_bw()
)
Faceted Plots
# Facet by variable
ggsurvplot_facet(fit, data = lung, facet.by = "ph.ecog")
# Multiple groups
ggsurvplot_list(list(fit1, fit2), data = lung)
# Combined plot
ggsurvplot_combine(list(fit1, fit2), data = lung)
Risk Tables
ggsurvplot(fit, data = lung,
risk.table = TRUE,
risk.table.height = 0.25,
risk.table.y.text = FALSE,
risk.table.title = "Number at risk",
tables.theme = theme_cleantable()
)
# Cumulative events
ggsurvplot(fit, data = lung,
cumevents = TRUE,
cumcensor = TRUE
)
Cox Model Visualization
# Fit Cox model
cox_fit <- coxph(Surv(time, status) ~ age + sex + ph.ecog, data = lung)
# Forest plot
ggforest(cox_fit, data = lung)
# Adjusted survival curves
ggadjustedcurves(cox_fit, data = lung, variable = "sex")
# Survival curves at specific covariate values
new_data <- data.frame(age = c(50, 70), sex = 1, ph.ecog = 1)
fit_cox <- survfit(cox_fit, newdata = new_data)
ggsurvplot(fit_cox, data = lung)
Statistical Tests
# Log-rank test
surv_diff <- survdiff(Surv(time, status) ~ sex, data = lung)
# Pairwise comparisons
pairwise_survdiff(Surv(time, status) ~ ph.ecog, data = lung)
# Add p-value to plot
ggsurvplot(fit, data = lung,
pval = TRUE,
pval.method = TRUE,
log.rank.weights = "1" # Log-rank
)
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.
- 4d ago First seen · 201 lines · 24 tokens per session scan A 46bf4318e142
survminer is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 5mo ago), licensed MIT. It adds 24 tokens to every session and 1,194 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 2026-09-03.
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