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/dallay/agentsync/performancenpx skills add dallay/agentsync --skill performancegit clone --depth 1 https://github.com/dallay/agentsyncWhat 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 | $0.00050 | $0.02402 |
| Opus 5 | $0.00025 | $0.01201 |
| Sonnet 5 | $0.00010 | $0.00480 |
| Haiku 4.5 | $0.00005 | $0.00240 |
Grade A, and why
performance scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
return cached || fetch(event.request).then((response) => { This is a copy
92% identical to performance — 134 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 388 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance optimization
Deep performance optimization based on Lighthouse performance audits. Focuses on loading speed, runtime efficiency, and resource optimization.
How it works
- Identify performance bottlenecks in code and assets
- Prioritize by impact on Core Web Vitals
- Provide specific optimizations with code examples
- Measure improvement with before/after metrics
Performance budget
| Resource | Budget | Rationale |
|---|---|---|
| Total page weight | < 1.5 MB | 3G loads in ~4s |
| JavaScript (compressed) | < 300 KB | Parsing + execution time |
| CSS (compressed) | < 100 KB | Render blocking |
| Images (above-fold) | < 500 KB | LCP impact |
| Fonts | < 100 KB | FOIT/FOUT prevention |
| Third-party | < 200 KB | Uncontrolled latency |
Critical rendering path
Server response
- TTFB < 800ms. Time to First Byte should be fast. Use CDN, caching, and efficient backends.
- Enable compression. Gzip or Brotli for text assets. Brotli preferred (15-20% smaller).
- HTTP/2 or HTTP/3. Multiplexing reduces connection overhead.
- Edge caching. Cache HTML at CDN edge when possible.
Resource loading
Preconnect to required origins:
<link rel="preconnect" href="https://fonts.googleapis.com">
<link rel="preconnect" href="https://cdn.example.com" crossorigin>
Preload critical resources:
<!-- LCP image -->
<link rel="preload" href="/hero.webp" as="image" fetchpriority="high">
<!-- Critical font -->
<link rel="preload" href="/font.woff2" as="font" type="font/woff2" crossorigin>
Defer non-critical CSS:
<!-- Critical CSS inlined -->
<style>/* Above-fold styles */</style>
<!-- Non-critical CSS -->
<link rel="preload" href="/styles.css" as="style" onload="this.onload=null;this.rel='stylesheet'">
<noscript><link rel="stylesheet" href="/styles.css"></noscript>
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 · 388 lines · 50 tokens per session scan A d934cf4c83fc
performance is a skill published in the GitHub repository dallay/agentsync (54 stars, last pushed 2d ago), licensed MIT. It adds 50 tokens to every session and 2,402 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 92% identical to performance, differing in 134 lines, and is treated as a copy.
Other skills, from other repositories
agent-code-analyzer
Agent skill for code-analyzer - invoke with $agent-code-analyzer.
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
haiku
When writing a haiku for this bot, follow these conventions.
deploy-docker-compose
Run the Omnigent server as a Docker compose stack (server + Postgres) on any Docker host — your laptop, a VPS, EC2 by hand, or as the base layer of any container-platform deploy. Invoke when the user wants to build the image, bring up the compose stack, debug the stack on a host they already have, or extend the stack…
azure-mgmt-botservice-dotnet
Azure Resource Manager SDK for Bot Service in .NET. Management plane operations for creating and managing Azure Bot resources, channels (Teams, DirectLine, Slack), and connection settings. Triggers: "Bot Service", "BotResource", "Azure Bot", "DirectLine channel", "Teams channel", "bot management .NET", "create bot".
dogfood
Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or test this app on mobile.