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/sandsower/beislid/rinsenpx skills add sandsower/beislid --skill rinsegit clone --depth 1 https://github.com/sandsower/beislidWhat 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 | $0.00066 | $0.01388 |
| Opus 5 | $0.00033 | $0.00694 |
| Sonnet 5 | $0.00013 | $0.00278 |
| Haiku 4.5 | $0.00007 | $0.00139 |
Grade A, and why
rinse 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rinse
Run an iterative review/fix/verify loop around the side-effect-free review primitive. rinse is an orchestrator: it may edit files, run verification, and repeat review passes, but only within user-approved boundaries.
The boundary is strict:
reviewfinds issues and returns the review contract.rinsedecides, with the user, which findings to fix.rinseapplies fixes, runs verification, and reruns review.
Use this for:
- Hardening a local branch before
ready-for-review - Working through multiple review findings in a controlled loop
- Running a local review/fix cycle for routine PRs
- Coordinating optional external reviewers when the host provides an agent-neutral way to call them
Do not use this for:
- A single side-effect-free review — use
review - A final whole-diff pass — use
fresh-eyes - Inbound PR comment posting — use
pr-patrol - Post-submission feedback on your own PR — use
review-response - Open-ended redesign when repeated iterations show the approach is wrong — stop and route to
blueprint
Checklist
Complete these phases in order:
- Establish the diff, requirements, and allowed fix boundary
- Run
reviewusing the shared review contract - Triage findings with the user
- Apply approved fixes only
- Run applicable verification
- Rerun
review - Stop, continue, or escalate to redesign
Phase 1: Establish scope
Determine the review input:
git status --short
gh pr view --json baseRefName,headRefName 2>/dev/null
git merge-base HEAD main # or master / PR base when applicable
git diff <base-sha>...HEAD --stat
Load requirements/context from the caller, plans, specs, ticket summaries, or commit messages. If no requirements are available, say so and review against general production readiness.
Ask the user for the fix boundary before making any changes:
What may rinse change?
(a) Only fixes for Critical findings
(b) Critical + Important findings
(c) All findings including Minor cleanup
(d) A custom file/path boundary
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 · 173 lines · 66 tokens per session scan A 66edfafc0b7f
rinse is a skill published in the GitHub repository sandsower/beislid (10 stars, last pushed 3d ago), licensed MIT. It adds 66 tokens to every session and 1,388 once invoked, about $0.0003 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.
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…