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/itallstartedwithaidea/agent-skills/edge-renderingnpx skills add itallstartedwithaidea/agent-skills --skill edge-renderinggit clone --depth 1 https://github.com/itallstartedwithaidea/agent-skillsWrote 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/itallstartedwithaidea/agent-skills/edge-rendering)<a href="https://agentmods.dev/skills/itallstartedwithaidea/agent-skills/edge-rendering"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/edge-rendering.svg" alt="Measured on agentmods" 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 | $0.00034 | $0.01476 |
| Opus 5 | $0.00017 | $0.00738 |
| Sonnet 5 | $0.00007 | $0.00295 |
| Haiku 4.5 | $0.00003 | $0.00148 |
Grade A, and why
edge-rendering 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 5d 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.
async fetch(request: Request, env: Env, ctx: ExecutionContext): Promise<Response> { How it starts
The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Edge Rendering
Part of Agent Skills™ by googleadsagent.ai™
Description
Edge Rendering generates and serves dynamic pages at the network edge, eliminating origin round-trips for content that varies by city, service, or user segment. This skill powers googleadsagent.ai™'s system of 18,000+ pages generated from a matrix of 116 services across 155+ cities, each with unique content, structured data, and SEO metadata—all rendered at the edge with sub-50ms TTFB globally.
The city × service page matrix demonstrates the power of edge rendering at scale. Rather than pre-building 18,000 static pages or routing every request to a centralized origin, Workers generate each page on demand using templates, city-specific data from KV, and service metadata from D1. Rendered pages are cached at the edge with stale-while-revalidate semantics, providing instant responses while keeping content fresh.
This pattern extends beyond SEO landing pages to any content that follows a combinatorial template: product × location pages, event × venue pages, or service × industry pages. The edge rendering pipeline handles template resolution, data injection, structured data generation (JSON-LD), meta tag construction, and cache management as a unified system.
Use When
- Generating pages from a combinatorial matrix (city × service, product × category)
- Serving SEO-critical content that must have fast TTFB globally
- Building landing page systems with thousands of unique URLs
- Replacing static site generation that takes hours to build
- Implementing stale-while-revalidate caching at the edge
- Rendering structured data (JSON-LD) dynamically per page
How It Works
graph TD
A[Request: /google-ads/chicago] --> B[Worker: Parse city + service]
B --> C{Edge Cache Hit?}
C -->|Hit| D[Return Cached HTML]
C -->|Miss| E[Fetch City Data from KV]
E --> F[Fetch Service Data from D1]
F --> G[Render Template]
G --> H[Inject JSON-LD Structured Data]
H --> I[Generate Meta Tags]
I --> J[Cache at Edge]
J --> K[Return Fresh HTML]
D --> L[Background: Revalidate if Stale]
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.
- 5d ago First seen · 151 lines · 34 tokens per session scan A 4ca65d541215
edge-rendering is a skill published in the GitHub repository itallstartedwithaidea/agent-skills (36 stars, last pushed 4mo ago), licensed MIT. It adds 34 tokens to every session and 1,476 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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