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/kreek/consult/performancenpx skills add kreek/consult --skill performancegit clone --depth 1 https://github.com/kreek/consultWhat 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 | $0.00019 | $0.01066 |
| Opus 5 | $0.00010 | $0.00533 |
| Sonnet 5 | $0.00004 | $0.00213 |
| Haiku 4.5 | $0.00002 | $0.00107 |
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 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance
Iron Law
MEASURE BEFORE OPTIMIZING. MEASURE AGAIN BEFORE KEEPING THE CHANGE.
When to Use
- Diagnosing slowness, optimizing latency/throughput/allocation, reading profiles, designing benchmarks, investigating p99/p99.9, or deciding whether a performance change is worth it.
- Adding, reviewing, tuning, or debugging caches (application, database, Redis/Memcached, CDN, browser, edge), including stale data, stampedes, hot keys, and miss latency.
When NOT to Use
- Concurrency correctness without measured slowness; use
async-systems. - Database query safety without profiling context; use
database. - HTTP API cache semantics unrelated to storage or performance; use
api.
Core Ideas
- Name the target metric before changing code.
- Use a realistic workload and identical before/after conditions.
- Optimize the measured bottleneck, not the code that only looks suspicious.
- Tail latency matters; averages hide the slow requests users feel.
- CPU, off-CPU, memory, allocation, I/O, lock contention, and network wait are different problems.
- Micro-benchmarks prove local mechanics, not end-to-end wins.
- Keep complexity only when the measured gain justifies it.
- Caches need a source of truth, invalidation trigger, stale tolerance, key contract, stampede protection, and metrics before they are kept.
- Cache keys encode every input that changes the value, including freshness, tenant, permissions, locale, and version.
- Treat cache contents as sensitive storage when keys or values contain secrets, raw PII, tenant data, or authorization context.
Workflow
- Define the metric: p99 latency, throughput, CPU time, allocation rate, memory, or error budget impact. Capture baseline with production-shaped data and concurrency.
- Profile to find the dominant bottleneck. If caching is considered, state the value being cached, source of truth, invalidation trigger, stale tolerance, key contract, stampede policy, TTL/jitter, and cache metrics.
- Make one change.
- Re-measure under the same conditions. Check adjacent regressions: memory, error rate, tail latency, CPU, maintainability.
What ships with it
1 file 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.
- yesterday First seen · 99 lines · 19 tokens per session scan A 37277e7b91f5
performance is a skill published in the GitHub repository kreek/consult (1 stars, last pushed 6d ago), licensed MIT. It adds 19 tokens to every session and 1,066 once invoked, about $0.0001 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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