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 hoangatg/ai-agent-toolkit --skill edge-computinggit clone --depth 1 https://github.com/hoangatg/ai-agent-toolkitWrote 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/hoangatg/ai-agent-toolkit/edge-computing)<a href="https://agentmods.dev/skills/hoangatg/ai-agent-toolkit/edge-computing"><img src="https://agentmods.dev/badge/skills/hoangatg/ai-agent-toolkit/edge-computing/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/hoangatg/ai-agent-toolkit/edge-computing"><img src="https://agentmods.dev/badge/skills/hoangatg/ai-agent-toolkit/edge-computing.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 | $0.00040 | $0.00353 |
| Opus 5 | $0.00020 | $0.00177 |
| Sonnet 5 | $0.00008 | $0.00071 |
| Haiku 4.5 | $0.00004 | $0.00035 |
Grade A, and why
edge-computing 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 8d 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
Edge Computing
Run code at the edge — closest to users. Sub-10ms cold starts, global distribution.
Platform Comparison
| Platform | Runtime | Cold Start | Limits |
|---|---|---|---|
| Cloudflare Workers | V8 isolates | < 5ms | 128MB RAM |
| Vercel Edge Functions | V8 isolates | < 5ms | 128MB RAM |
| Deno Deploy | Deno | < 5ms | 512MB RAM |
| AWS Lambda@Edge | Node.js | 50-200ms | 128MB RAM |
| Fastly Compute | Wasm | < 1ms | 128MB RAM |
Edge-Compatible Patterns
| Pattern | Description |
|---|---|
| KV Storage | Key-value at the edge (Workers KV, Vercel KV) |
| Edge Databases | D1, Turso, PlanetScale, Neon serverless |
| Streaming | Response streaming with ReadableStream |
| Geolocation | Route by user location |
| A/B Testing | Feature flags at edge, zero client JS |
Edge Constraints
- No Node.js APIs (fs, crypto, net)
- Limited execution time (30s-60s)
- No native modules
- Must use Web APIs (fetch, Request, Response)
- Use edge-compatible ORMs (Drizzle, Prisma Edge)
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.
- 8d ago First seen · 39 lines · 40 tokens per session scan A 51bb328bf7f1
edge-computing is a skill published in the GitHub repository hoangatg/ai-agent-toolkit (1 stars, last pushed 5mo ago), licensed MIT. It adds 40 tokens to every session and 353 once invoked, about $0.0002 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 2026-09-03.
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