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 tsnagit 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/tsna)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/tsna"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/tsna/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/tsna"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/tsna.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 | $0.00023 | $0.00521 |
| Opus 5 | $0.00012 | $0.00260 |
| Sonnet 5 | $0.00005 | $0.00104 |
| Haiku 4.5 | $0.00002 | $0.00052 |
Grade A, and why
tsna 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 9d 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
tsna
Tools for temporal social network analysis.
Temporal Paths
library(tsna)
# Forward reachable set
tPath(dnet, v = 1, direction = "fwd",
start = 0, end = 10)
# Backward reachable set
tPath(dnet, v = 1, direction = "bkwd",
start = 0, end = 10)
# Geodesic distance
tPath(dnet, v = 1, type = "geodesic")
Reachability
# Forward reachability
reach_fwd <- tReach(dnet, direction = "fwd")
# Backward reachability
reach_bkwd <- tReach(dnet, direction = "bkwd")
# Reachability matrix
tReach(dnet, graph = TRUE)
Temporal Metrics
# Temporal degree
tDegree(dnet)
# At specific time
tDegree(dnet, at = 5)
# Over interval
tDegree(dnet, start = 0, end = 10)
SNA Statistics Over Time
# Apply SNA function over time
tSnaStats(dnet, snafun = "betweenness")
tSnaStats(dnet, snafun = "closeness")
tSnaStats(dnet, snafun = "degree")
# Custom function
tSnaStats(dnet, snafun = function(x) {
mean(degree(x))
})
Edge Duration
# Edge durations
edgeDuration(dnet)
# Mean duration
mean(edgeDuration(dnet))
Vertex Activity
# Vertex activity duration
vertexDuration(dnet)
Transmission Trees
# Infection/transmission tree
tree <- tPath(dnet, v = 1, direction = "fwd",
type = "earliest.arrive")
# Plot tree
plot(tree)
Temporal Correlation
# Correlation between time slices
tCorrelate(dnet, lag = 1)
Aggregation
# Aggregate over time windows
tErgmStats(dnet,
formula = ~ edges + mutual,
start = 0, end = 10,
time.interval = 1)
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.
- 9d ago First seen · 111 lines · 23 tokens per session scan A 9f00fc12363e
tsna is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 6mo ago), licensed MIT. It adds 23 tokens to every session and 521 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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