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/leolin990405/r-analytics-skill/stringinpx skills add LeoLin990405/r-analytics-skill --skill stringigit clone --depth 1 https://github.com/LeoLin990405/r-analytics-skillWhat 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 | $0.00022 | $0.00825 |
| Opus 5 | $0.00011 | $0.00413 |
| Sonnet 5 | $0.00004 | $0.00165 |
| Haiku 4.5 | $0.00002 | $0.00082 |
Grade A, and why
stringi 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
stringi
Fast string processing with ICU.
Basic Operations
library(stringi)
# Length
stri_length("hello")
stri_length(c("hello", "world"))
# Concatenation
stri_c("hello", "world")
stri_c("a", "b", "c", sep = "-")
stri_paste(letters[1:3], collapse = ", ")
# Duplication
stri_dup("ab", 3) # "ababab"
Case Conversion
stri_trans_toupper("hello")
stri_trans_tolower("HELLO")
stri_trans_totitle("hello world")
# Locale-aware
stri_trans_toupper("istanbul", locale = "tr_TR")
Substring
# Extract
stri_sub("hello", 1, 3) # "hel"
stri_sub("hello", -2) # "lo"
# Replace
x <- "hello"
stri_sub(x, 1, 2) <- "XX" # "XXllo"
# Multiple extractions
stri_sub_all("hello", list(c(1, 3), c(2, 4)))
Pattern Matching
# Detect
stri_detect_regex("hello123", "\\d+")
stri_detect_fixed("hello", "ell")
# Count
stri_count_regex("a1b2c3", "\\d")
stri_count_fixed("banana", "a")
# Locate
stri_locate_first_regex("hello123", "\\d+")
stri_locate_all_regex("a1b2c3", "\\d")
Extract and Replace
# Extract matches
stri_extract_first_regex("hello123", "\\d+")
stri_extract_all_regex("a1b2c3", "\\d+")
# Replace
stri_replace_first_regex("hello123", "\\d+", "XXX")
stri_replace_all_regex("a1b2c3", "\\d", "X")
stri_replace_all_fixed("banana", "a", "o")
Split
stri_split_fixed("a,b,c", ",")
stri_split_regex("a1b2c3", "\\d")
stri_split_boundaries("hello world", type = "word")
Trim and Pad
# Trim whitespace
stri_trim(" hello ")
stri_trim_left(" hello ")
stri_trim_right(" hello ")
# Pad
stri_pad_left("42", 5, "0") # "00042"
stri_pad_right("hi", 5, "-") # "hi---"
stri_pad_both("hi", 6, "*") # "**hi**"
Encoding
# Detect encoding
stri_enc_detect(raw_bytes)
# Convert encoding
stri_encode(x, from = "latin1", to = "UTF-8")
# Check if valid UTF-8
stri_enc_isutf8(x)
Comparison
# Compare strings
stri_cmp("a", "b") # -1, 0, or 1
# Locale-aware comparison
stri_cmp("ä", "z", locale = "de_DE")
# Sorting
stri_sort(c("b", "a", "c"))
stri_order(c("b", "a", "c"))
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 · 149 lines · 22 tokens per session scan A 15a02e3f3771
stringi is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 5mo ago), licensed MIT. It adds 22 tokens to every session and 825 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 2026-08-31.
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