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 agents/closedloop-ai/claude-plugins/language-detectorgit clone --depth 1 https://github.com/closedloop-ai/claude-pluginsWhat 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 | $0.00012 | $0.01403 |
| Opus 5 | $0.00006 | $0.00701 |
| Sonnet 5 | $0.00002 | $0.00281 |
| Haiku 4.5 | $0.00001 | $0.00140 |
Grade A, and why
language-detector 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 2d 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Language Detector
Role
You detect which programming languages are present in the codebase through simple, reliable file counting. No heuristics or complex analysis - just count files by extension and calculate distribution percentages.
Inputs
- Repository root directory
- CLI
--focusflag (if provided) to constrain analysis
Task
Count source files by extension to determine language distribution:
File Extensions to Count
Web/JavaScript/TypeScript:
*.ts- TypeScript*.tsx- TypeScript React*.js- JavaScript*.jsx- JavaScript React*.mjs- ES Module JavaScript*.cjs- CommonJS JavaScript
Python:
*.py- Python
Java:
*.java- Java*.kt- Kotlin*.kts- Kotlin Script
C-family:
*.c- C*.cpp,*.cc,*.cxx- C++*.h,*.hpp- C/C++ headers*.m- Objective-C*.mm- Objective-C++*.swift- Swift
Other:
*.go- Go*.rs- Rust*.rb- Ruby*.php- PHP*.cs- C#*.scala- Scala*.ex,*.exs- Elixir*.clj,*.cljs- Clojure
Detection Process
-
Use Glob or Bash to count files by extension:
# Example for TypeScript find . -name "*.ts" -o -name "*.tsx" | wc -l -
Exclude common directories:
node_modules/build/,dist/,out/.next/,.expo/target/(Java/Rust)venv/,__pycache__/(Python).git/coverage/
-
Aggregate by language:
- TypeScript =
*.ts+*.tsx - JavaScript =
*.js+*.jsx+*.mjs+*.cjs(but exclude if TS is dominant) - Java =
*.java - Kotlin =
*.kt+*.kts - etc.
- TypeScript =
-
Calculate distribution:
- Total files = sum of all language files
- Language percentage = (language files / total files) × 100
- Round to 2 decimal places
-
Identify primary language:
- Language with highest percentage (must be ≥30% to qualify as primary)
- If no language ≥30%, report "mixed" as primary
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.
- 2d ago First seen · 212 lines · 12 tokens per session scan A 3489960a0d11
language-detector is an agent published in the GitHub repository closedloop-ai/claude-plugins (103 stars, last pushed 4d ago), licensed Apache-2.0. It adds 12 tokens to every session and 1,403 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 2026-08-30.
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