Borrowing it
Nothing to install: this file belongs to saeedkolivand/ai-job-hunter-app. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/saeedkolivand/ai-job-hunter-app/main/.claude/skills/performance-checklist/SKILL.mdgit clone --depth 1 https://github.com/saeedkolivand/ai-job-hunter-appWrote 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/saeedkolivand/ai-job-hunter-app/performance-checklist)<a href="https://agentmods.dev/skills/saeedkolivand/ai-job-hunter-app/performance-checklist"><img src="https://agentmods.dev/badge/skills/saeedkolivand/ai-job-hunter-app/performance-checklist/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/saeedkolivand/ai-job-hunter-app/performance-checklist"><img src="https://agentmods.dev/badge/skills/saeedkolivand/ai-job-hunter-app/performance-checklist.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00038 | $0.00846 |
| Opus 5 | $0.00019 | $0.00423 |
| Sonnet 5 | $0.00008 | $0.00169 |
| Haiku 4.5 | $0.00004 | $0.00085 |
Grade A, and why
performance-checklist 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 8d 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 — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance checklist
Authoritative: docs/knowledge/performance-rules.md. Bias perf findings toward MEDIUM unless there's a concrete on-a-hot-path regression.
Async runtime (HIGH if blocking)
- No blocking I/O or CPU-bound work on the tokio runtime — use
spawn_blocking/ the data layer. SQLite never blocks the async runtime.
Hot paths
- Scraping — bounded concurrency, chromiumoxide page lifecycle reused, per-board rate limits.
- Embeddings / AI — batch sizing, streaming back-pressure, token/context budget minimized, cheapest viable model.
- Layout / export — pre-measure before render; don't re-shape fonts per glyph; pagination computed once.
- Data — no N+1 queries, no full-table scans on warm paths.
Renderer
- React Query
staleTime/gcTimetuned (desktop: no refetch-on-focus); large lists virtualized; avoid needless re-renders (stable deps, memo where measured).
Token efficiency
- Minimize prompt/context size in AI calls; reuse cached/embedded context; don't resend unchanged context.
External standards & best-practices (verified 2026-06-19)
Only genuinely 2026-changed item: React Compiler 1.0 (2025-10-07) flips the default from hand-memoize to compiler-memoize. CWV thresholds + Tokio/SQLite discipline are stable.
- Core Web Vitals (p75): LCP ≤ 2.5s · INP ≤ 200ms · CLS ≤ 0.1 (INP replaced FID 2024; ignore SEO claims of a tightened 2.0s LCP). Field via web-vitals lib; lab via Lighthouse. https://web.dev/articles/vitals
- React — with Compiler on, don't add (or rip out) manual
useMemo/useCallback/memo; without it, memoize only after a measured >16ms render. Virtualize long/unbounded lists (TanStack Virtual → ~viewport-only DOM); route-level code-split. https://react.dev/learn/react-compiler/introduction - Rust/Tokio — never block the executor; offload std-blocking / >~1ms-CPU to
spawn_blocking(short) or a dedicated thread (long); bound CPU concurrency with aSemaphore;spawn_blockingtasks can't be aborted and block shutdown (shutdown_timeout). Profile:cargo flamegraph/samply(CPU), DHAT/heaptrack (heap),tokio-console(async stalls). https://docs.rs/tokio/latest/tokio/task/fn.spawn_blocking.html - SQLite —
journal_mode=WAL+synchronous=NORMAL(loses only durability on power-loss);cache_size(negative = KiB),mmap_size30–256MB read-heavy,temp_store=MEMORY;busy_timeout(e.g. 5000) to avoidSQLITE_BUSY; index WHERE/JOIN/ORDER-BY cols; prepared/bound statements; SQLite calls block → run on a pool insidespawn_blocking. https://www.sqlite.org/pragma.html
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.
- 8d ago First seen · 39 lines · 38 tokens per session scan A d306017a5935
performance-checklist is a skill published in the GitHub repository saeedkolivand/ai-job-hunter-app (55 stars, last pushed today), licensed Apache-2.0. It adds 38 tokens to every session and 846 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 2026-09-03.
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