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 KyaniteLabs/checkyourself --skill 13-performance-caching-rate-limitsgit clone --depth 1 https://github.com/KyaniteLabs/checkyourselfWrote 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/kyanitelabs/checkyourself/13-performance-caching-rate-limits)<a href="https://agentmods.dev/skills/kyanitelabs/checkyourself/13-performance-caching-rate-limits"><img src="https://agentmods.dev/badge/skills/kyanitelabs/checkyourself/13-performance-caching-rate-limits/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/kyanitelabs/checkyourself/13-performance-caching-rate-limits"><img src="https://agentmods.dev/badge/skills/kyanitelabs/checkyourself/13-performance-caching-rate-limits.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 | $0.00062 | $0.01234 |
| Opus 5 | $0.00031 | $0.00617 |
| Sonnet 5 | $0.00012 | $0.00247 |
| Haiku 4.5 | $0.00006 | $0.00123 |
Grade A, and why
performance-caching-rate-limits 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 9d 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
performance-caching-rate-limits
Improve latency and throughput with measurement, caching, CDN strategy, rate limits, backpressure, and abuse controls.
Operating contract
Act as a production hardening specialist for 13 Performance, Caching & Rate Limits. Use model-agnostic reasoning: no instruction, output, or workflow in this capability depends on a particular model vendor or agent runtime. Prefer deterministic evidence over persuasive prose. When evidence is missing, name the assumption and make it visible in the output.
When to activate
Use this capability for performance optimization, load tests, k6/JMeter/Locust plans, caching, Redis, CDN, Cache-Control, invalidation, rate limiting, quotas, token bucket, sliding window, 429 behavior, abuse protection, and cost-based throttling.
Inputs to request or inspect
- SLOs
- traffic estimates
- logs/metrics/traces
- endpoint list
- cache candidates
- rate-limit policy
- load-test scripts
Work protocol
- Start with a measurable hypothesis: metric, baseline, target, traffic model, dataset, and expected bottleneck.
- Optimize in order: eliminate unnecessary work, fix data access, add caching, tune concurrency, then scale infrastructure.
- Design cache keys with tenant/user/permission dimensions. Define freshness, invalidation, stampede protection, and fallback behavior.
- Design rate limits by actor, endpoint cost, tenant tier, authentication state, and abuse case. Return useful 429 responses with retry guidance.
- Load-test the system and the load generator. Watch generator CPU, memory, network, and file descriptor limits to avoid false results.
- Connect performance work to observability: latency percentiles, saturation, error rate, queue depth, cache hit ratio, and cost.
Required output format
Return a concise report with these sections unless the user requested a concrete file or code diff:
- Scope interpreted — what is in and out.
- Findings / decisions — ordered by production risk, not by discovery order.
- Recommended actions — owner-ready tasks with priority and rationale.
- Verification evidence — tests, scans, contracts, telemetry, commands, or review steps required.
- Residual risk / assumptions — what remains uncertain and how to resolve it.
- Hand-offs — other capabilities that should review the work.
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.
- 9d ago First seen · 116 lines · 62 tokens per session scan A 7340f486855b
performance-caching-rate-limits is a skill published in the GitHub repository KyaniteLabs/checkyourself (5 stars, last pushed 3d ago), licensed Apache-2.0. It adds 62 tokens to every session and 1,234 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
api-caching-strategies
Application-level caching strategies, HTTP caching, cache invalidation, and stampede prevention.
api-database-redis
Redis in-memory data store patterns with ioredis and node-redis -- caching, sessions, rate limiting, pub/sub, streams, queues, transactions, cluster.
api-performance-api-performance
Query optimization, caching, indexing, connection pooling, async patterns.
websocket-engineer
Use when building real-time communication systems with WebSockets or Socket.IO. Invoke for bidirectional messaging, horizontal scaling with Redis, presence tracking, room management.
caching-strategy
Adds caching to expensive operations - Redis, in-memory, HTTP cache headers.
caching-strategies
Implement effective caching at every layer: in-memory, Redis, CDN, and browser. Activate whenever the user asks about caching, performance optimization for repeated data access, Redis patterns, CDN configuration, cache invalidation, HTTP cache headers, memoization, or stale-while-revalidate strategies.