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 skills add YuDefine/nuxt-supabase-starter --skill rls-performancegit clone --depth 1 https://github.com/YuDefine/nuxt-supabase-starterWrote 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/yudefine/nuxt-supabase-starter/rls-performance)<a href="https://agentmods.dev/skills/yudefine/nuxt-supabase-starter/rls-performance"><img src="https://agentmods.dev/badge/skills/yudefine/nuxt-supabase-starter/rls-performance/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yudefine/nuxt-supabase-starter/rls-performance"><img src="https://agentmods.dev/badge/skills/yudefine/nuxt-supabase-starter/rls-performance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00058 | $0.02730 |
| Opus 5 | $0.00029 | $0.01365 |
| Sonnet 5 | $0.00012 | $0.00546 |
| Haiku 4.5 | $0.00006 | $0.00273 |
Grade A, and why
rls-performance 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 yesterday.
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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RLS Performance Playbook
大型專案常累積大量 RLS policy 與 SECURITY DEFINER function，加上 self-hosted LXC 的 connection pool 限制，任何 N+1 或 full scan 都會被放大。本 skill 是遇到效能問題時的操作手冊。
決策原則（「MUST 做 / NEVER 做」）仍在 db-runtime/<variant>/database.md 與 db-schema/<variant>/database-design.md 規約（依 consumer 的 module variant 投影，三端都送達），本檔提供實際診斷與優化工具。
何時開啟本 skill
- 新增涉及 policy join 的表
- 修改既有 RLS policy 的 WHERE 條件
- 新增 server API endpoint 含 pagination / filter
- 遇到
PGRST003（504 timeout）或 pool 耗盡 - 使用者抱怨特定頁面 / endpoint 變慢
- 需要稽核 production 效能或清理無用 index
- 排查 LXC 連線問題 / Tunnel 斷線
核心原則：policy 改動前先量，改動後驗證，不要憑感覺優化。
EXPLAIN ANALYZE — 正確的 RLS 測量方式
關鍵陷阱：superuser 跑 EXPLAIN 會 bypass RLS，測出來的 plan 跟 production 完全不同。一定要 set local role 模擬目標角色。
-- 1. 模擬目標 role（不是 postgres superuser！）
set local role authenticated;
set local request.jwt.claims to '{"sub": "<user_uuid>", "role": "authenticated"}';
-- 2. 跑實際 query
explain (analyze, buffers, verbose, format text)
select ... from <schema>.<table> where ...;
-- 3. 還原
reset role;
讀 plan 重點
| Plan 片段 | 意義 | 處理 |
|---|---|---|
Seq Scan on xxx |
全表掃描 | 檢查 WHERE 欄位是否有 index |
Rows Removed by Filter: > 1000 |
Index 取太多又濾掉 | Composite index 或 partial index |
Subquery Scan ... InitPlan |
(SELECT auth.uid()) 有快取 |
✅ 正確模式 |
Filter: (auth.uid() = user_id) |
沒快取 | 改 subselect (SELECT auth.uid()) |
Nested Loop + 高 rows |
Policy 內 per-row JOIN | 改 subselect 預先算 ID set |
Planning Time > Execution Time |
Plan cache 沒命中 | 通常是 schema cache 過期或 prepared statement 問題 |
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.
- yesterday Changed · +2 lines 920dcd835364
- 5d ago First seen · 201 lines · 58 tokens per session scan A e436b8b24352
rls-performance is a skill published in the GitHub repository YuDefine/nuxt-supabase-starter (45 stars, last pushed yesterday), licensed MIT. It adds 58 tokens to every session and 2,730 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 2026-09-03.
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