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/hautc-it/cil/performancenpx skills add hautc-it/cil --skill performancegit clone --depth 1 https://github.com/hautc-it/cilWhat 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 | $0.00060 | $0.00366 |
| Opus 5 | $0.00030 | $0.00183 |
| Sonnet 5 | $0.00012 | $0.00073 |
| Haiku 4.5 | $0.00006 | $0.00037 |
Grade A, and why
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 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.
What it actually says
Skill: Performance
Measure first. Optimize the right thing.
Protocol
- Profile — Identify the actual bottleneck. Don't guess. Use profiler, metrics, or timing.
- One change — Change one variable at a time. Otherwise you can't tell what helped.
- Algorithm first — O(n log n) beats O(n²) regardless of constants. Fix the algorithm.
- I/O second — Reduce round trips. Batch reads/writes. Use connection pools.
- Cache last — Caching hides problems. Fix the underlying query/computation first.
Database
- EXPLAIN the query plan before optimizing.
- Index on columns in WHERE, JOIN ON, ORDER BY.
- SELECT only the columns you need.
- Avoid N+1: use JOIN or batch fetch, never query in a loop.
- Paginate large result sets. Never SELECT *.
- Use read replicas for read-heavy workloads.
Application
- Avoid synchronous I/O in request paths.
- Pool connections (DB, HTTP, Redis).
- Lazy-load what isn't needed on startup.
- Avoid holding locks across I/O.
- Profile memory, not just CPU.
Anti-patterns
- Premature optimization (before measuring)
- Optimizing cold paths (measure which path is hot first)
- Cache without invalidation strategy
- Adding indexes without analyzing query plans
- Treating all latency as CPU (often it's I/O waiting)
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 · 42 lines · 60 tokens per session scan A 67f58c22f794
performance is a skill published in the GitHub repository hautc-it/cil (1 stars, last pushed 1mo ago), licensed MIT. It adds 60 tokens to every session and 366 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.
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