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/rileyhilliard/rr/rrnpx skills add rileyhilliard/rr --skill rrgit clone --depth 1 https://github.com/rileyhilliard/rrWrote 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/rileyhilliard/rr/rr)<a href="https://agentmods.dev/skills/rileyhilliard/rr/rr"><img src="https://agentmods.dev/badge/skills/rileyhilliard/rr/rr.svg" alt="Measured on agentmods" 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 | $0.00037 | $0.02930 |
| Opus 5 | $0.00018 | $0.01465 |
| Sonnet 5 | $0.00007 | $0.00586 |
| Haiku 4.5 | $0.00004 | $0.00293 |
Grade C, and why
rr scanned grade C with 1 finding 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.
Reaches for credential fileshighPrivilege escalation
SSH keys, cloud credentials, git-credentials, .npmrc, /etc/shadow: reading these is how a config file becomes a credential leak.
| "handshake failed" but ssh works | Key not in agent: `ssh-add ~/.ssh/id_rsa`, add `AddKeysToAgent yes` to SSH config | How it starts
The opening of the file, as written. The whole thing — 405 lines — stays where its author put it; the contents beside it link to each section on GitHub.
rr (Road Runner) CLI
rr syncs code to remote machines and runs commands there. Handles host failover, file sync with rsync, distributed locking, and test output formatting.
Quick Reference
rr run "make test" # Sync files + run command
rr exec "git status" # Run command without syncing
rr sync # Just sync files
rr <taskname> # Run named task from config
rr provision # Install missing tools on hosts
rr doctor # Diagnose issues
rr monitor # TUI dashboard for host metrics
Two-Config System
rr uses two config files:
| Config | Location | Purpose |
|---|---|---|
| Global | ~/.rr/config.yaml |
Personal host definitions (SSH, directories) |
| Project | .rr.yaml |
Shareable project settings (tasks, sync rules) |
See config.md for complete config reference.
Minimal Global Config
version: 1
hosts:
mini:
ssh: [mac-mini.local, mac-mini-tailscale]
dir: ${HOME}/projects/${PROJECT}
Minimal Project Config
version: 1
hosts: [mini]
sync:
exclude: [.git/, node_modules/, .venv/]
tasks:
test:
run: pytest -v
Commands Overview
| Command | Purpose |
|---|---|
rr run "cmd" |
Sync files, then run command |
rr exec "cmd" |
Run command without syncing |
rr sync |
Just sync files |
rr <taskname> |
Run named task |
rr tasks |
List available tasks |
rr provision |
Install missing tools on hosts |
rr doctor |
Diagnose issues |
rr host list/add/remove |
Manage hosts |
See commands.md for full command reference.
Common Flags
--pretty/-p- Opt into human-readable output (spinners, colors). Default is structured JSON.--host <name>- Target specific host--tag <tag>- Select host by tag--local- Force local execution--skip-requirements- Skip requirement checks
Run rr --help or rr <command> --help for complete flag reference.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 405 lines · 37 tokens per session scan C f9ffe64e6481
rr is a skill published in the GitHub repository rileyhilliard/rr (195 stars, last pushed 9d ago), licensed MIT. It adds 37 tokens to every session and 2,930 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 1 finding (reaches for credential files). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-01.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…