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/florianbruniaux/claude-code-plugins/rtk-optimizernpx skills add FlorianBruniaux/claude-code-plugins --skill rtk-optimizergit clone --depth 1 https://github.com/FlorianBruniaux/claude-code-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 | $0.00044 | $0.01205 |
| Opus 5 | $0.00022 | $0.00602 |
| Sonnet 5 | $0.00009 | $0.00241 |
| Haiku 4.5 | $0.00004 | $0.00120 |
Grade A, and why
rtk-optimizer 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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RTK Optimizer Skill
Purpose: Automatically suggest RTK wrappers for high-verbosity commands to reduce token consumption.
How It Works
- Detect high-verbosity commands in user requests
- Suggest RTK wrapper if applicable
- Execute with RTK when user confirms
- Track savings over session
Supported Commands
Git (>70% reduction)
git log→rtk git log(92.3% reduction)git status→rtk git status(76.0% reduction)find→rtk find(76.3% reduction)
Medium-Value (50-70% reduction)
git diff→rtk git diff(55.9% reduction)cat <large-file>→rtk read <file>(62.5% reduction)
JS/TS Stack (70-90% reduction)
pnpm list→rtk pnpm list(82% reduction)pnpm test/vitest run→rtk vitest run(90% reduction)
Rust Toolchain (80-90% reduction)
cargo test→rtk cargo test(90% reduction)cargo build→rtk cargo build(80% reduction)cargo clippy→rtk cargo clippy(80% reduction)
Python & Go (90% reduction)
pytest→rtk python pytest(90% reduction)go test→rtk go test(90% reduction)
GitHub CLI (79-87% reduction)
gh pr view→rtk gh pr view(87% reduction)gh pr checks→rtk gh pr checks(79% reduction)
File Operations
ls→rtk ls(condensed output)grep→rtk grep(filtered output)
Activation Examples
User: "Show me the git history"
Skill: Detects git log → Suggests rtk git log → Explains 92.3% token savings
User: "Find all markdown files"
Skill: Detects find → Suggests rtk find "*.md" . → Explains 76.3% savings
Installation Check
Before first use, verify RTK is installed:
rtk --version # Should output: rtk 0.16.0+
If not installed:
# Homebrew (macOS/Linux)
brew install rtk-ai/tap/rtk
# Cargo (all platforms)
cargo install rtk
Usage Pattern
# When user requests high-verbosity command:
1. Acknowledge request
2. Suggest RTK optimization:
"I'll use `rtk git log` to reduce token usage by ~92%"
3. Execute RTK command
4. Track savings (optional):
"Saved ~13K tokens (baseline: 14K, RTK: 1K)"
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 · 147 lines · 44 tokens per session scan A 7a821397c656
rtk-optimizer is a skill published in the GitHub repository FlorianBruniaux/claude-code-plugins (40 stars, last pushed 3mo ago), licensed MIT. It adds 44 tokens to every session and 1,205 once invoked, about $0.0002 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.
Other skills, from other repositories
setup
创建一个新的 Workframe 项目，或把已有项目接入 Workframe。按用户意图与目标目录状态分流（新建 / 接入），对话采集业务上下文后落骨架、订阅 core 插件、完成落盘验收。仅用于 Workframe 框架的项目初始化，不承担 npm init / create-react-app / git init 等通用脚手架。.
material-intake
存量资料的盘点、分流与结构推荐。扫描给定路径产出资料台账（形态 × 数量 × 覆盖率），按资料形态判定每一批的去向（migrate-to-modules / requirement-archiving / code-to-doc / 手动放置），并从资料聚类推荐 basic/sub 模块树。只出计划不做搬运，重型执行交给对应 skill。.
code-review
代码审查，从需求符合度/正确性/安全性/可维护性/性能五维度评审代码变更，输出风险分级的 Finding 列表.
product-metrics-design
产品度量体系设计，支持 AARRR/HEART/North Star/OKR 四框架，输出三层指标体系与监控方案.
requirement-analysis
结构化需求澄清与优先级评估：判断需求形态（Full PRD / One-Pager / Quick Brief）、6 问澄清、RICE + MoSCoW 评估；Full PRD 移交 prd-writer，中小需求输出轻量需求摘要.
technical-design
技术方案设计与实施，提供轻量路径（小改动直接落地）和完整路径（架构/数据/API/多文件高风险变更走完整方案+实施+交付）双档分流.