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 clustergit 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/cluster)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/cluster"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/cluster/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/cluster"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/cluster.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 | $0.00027 | $0.00514 |
| Opus 5 | $0.00014 | $0.00257 |
| Sonnet 5 | $0.00005 | $0.00103 |
| Haiku 4.5 | $0.00003 | $0.00051 |
Grade A, and why
cluster scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
cluster
Finding groups in data.
K-Medoids (PAM)
library(cluster)
# PAM clustering
pam_result <- pam(data, k = 3)
# Results
pam_result$clustering # Cluster assignments
pam_result$medoids # Medoid points
pam_result$silinfo # Silhouette info
# Plot
plot(pam_result)
CLARA (Large Data)
# CLARA for large datasets
clara_result <- clara(data, k = 3, samples = 50)
# Results
clara_result$clustering
clara_result$medoids
Hierarchical Clustering
# Agglomerative (AGNES)
agnes_result <- agnes(data, method = "ward")
plot(agnes_result)
cutree(agnes_result, k = 3)
# Divisive (DIANA)
diana_result <- diana(data)
plot(diana_result)
cutree(diana_result, k = 3)
Fuzzy Clustering
# Fuzzy c-means
fanny_result <- fanny(data, k = 3)
# Membership matrix
fanny_result$membership
# Hard clustering
fanny_result$clustering
Silhouette Analysis
# Compute silhouette
sil <- silhouette(clustering, dist(data))
# Summary
summary(sil)
# Plot
plot(sil)
# Average silhouette width
mean(sil[, 3])
Distance Matrix
# Compute distances
d <- daisy(data)
# Mixed data types
d <- daisy(data, metric = "gower")
# With weights
d <- daisy(data, weights = c(1, 2, 1))
Optimal Clusters
# Gap statistic
gap_stat <- clusGap(data, FUN = pam, K.max = 10, B = 50)
plot(gap_stat)
# Optimal k
maxSE(gap_stat$Tab[, "gap"], gap_stat$Tab[, "SE.sim"])
Plotting
# Cluster plot
clusplot(data, clustering,
color = TRUE,
shade = TRUE,
labels = 2,
lines = 0)
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.
- 5d ago First seen · 115 lines · 27 tokens per session scan A 186cedce3554
cluster is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 5mo ago), licensed MIT. It adds 27 tokens to every session and 514 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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